OKDES
Volume III-D
Special Study Report
Social Aspects of Power Plant Siting
Sue Johnson and Esther Weil
University of Kentucky
May 15. 1977
PHASE
OHIO RIVER DASIN ENERGY STUDY
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OHIO RIVER BASIN ENERGY STUDY
Volume III-D
SPECIAL STUDY REPORT
SOCIAL ASPECTS OF POWER PLANT SITING
Sue Johnson
Esther Weil
University of Kentucky
May 15, 1977
Prepared for
Office of Energy, Minerals and Industry
Office of Research and Development
U.S. Environmental Protection Agency
Washington, D.C.
Grant Number R804817-01-0
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PREFACE
This Special Study had somewhat global aims at its inception,
the major goal of which was to try to assess, using secondary data,
what kinds of environmental orientations were likely to be present in
counties where power plants, both nuclear and coal-fired, are planned
or projected. It is a qualitative analysis guided by a theoretical
paradigm of environmental orientations which seeks to describe, at
the county level, what we speculate the likely impact of a power
plant to be. We have also tried to relate what we think the prevailing
environmental orientation of a county to likely reaction of the county's
residents to this kind of developmental change.
The entire analysis is carried out as if all events were happening
in the present or near future; no attempt has been made to speculate
as to a county's destiny between now and the year 2000. This limi-
tation is an important one, yet, when we are forced to rely on existing
data and literature in the general area of social aspects of the siting
of large facilities in communities, it seems a reasonable method of
provoking the reader to at least think a bit about what the social
impact of a power plant could actually be.
This report contains a description of the theoretical paradigm
we have followed; a series of hypotheses drawn from existing literature
as well as some of our own formulations, and these hypotheses are
classified by environmental orientation; and then, demographic profiles
of counties where power plants are planned or projected are presented.
From this basis, we then speculate as to what we think the dominant
environmental orientation(s) to be and what we think the likely
general impact of siting a power plant in a county to be, given the
information at hand. The demographic profiles are given in greater
detail than the impact assessment so that the reader may draw his/her
own conclusions concerning likely impact. Our goal, in the brief im-
pact assessments, is to present what we consider a plausible picture
of possible impacts of and the reaction of the host county to power
plant development; we make no claims for presenting an accurate
picture for only actual fieldwork and the future can tell us that.
This report reflects solely the views and conclusions of the
authors. These do not necessarily reflect the views of our sponsoring
agency, the U.S. Environmental Protection Agency, nor that of any
other agency of the U.S. Government.
III-D-iii
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CONTENTS
page
PREFACE III-D-iii
TABLES III-D-xv
APPENDIX - MAPS III-D-xxii
1. INTRODUCTION III-D-1
2. ENVIRONMENTAL ORIENTATION PARADIGM III-D-5
2.1. THE INSTRUMENTAL ORIENTATION III-D-5
2.2. THE TERRITORIAL ORIENTATION III-D-11
2.3. THE SENTIMENTAL ORIENTATION III-D-17
2.4. THE SYMBOLIC ORIENTATION III-D-22
3. METHODOLOGY III-D-35
3.1. INTRODUCTION III-D-35
3.2. METHODOLOGY OF DESCRIPTION III-D-36
3.3. SOURCES III-D-37
3.3.1. CENSUSES OF POPULATION
AND HOUSING III-D-37
3.3.2. CENSUS OF AGRICULTURE III-D-37
3.3.3. CENSUSES OF MANUFACTURING
AND GOVERNMENT III-D-38
3.3.4. COUNTY BUSINESS PATTERNS .... III-D-38
3.3.5. U.S. FOREST SERVICE FIGURES. . . III-D-39
3.3.6. INCOME DATA III-D-39
3.3.7. RECREATIONAL DATA III-D-39
3.3.8. BUREAU OF MINES PUBLICATIONS . . III-D-39
3.3.9. KENTUCKY STATE DOCUMENTS .... III-D-39
3.3.10. CULTURAL DATA III-D-39
3.3.11. SUPPLEMENTARY SOURCES III-D-40
3.4. LANGUAGE III-D-40
3.5. SCENARIOS III-D-40
III-D-v
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4. GENERAL CHARACTERISTICS OF THE ORBES REGION:
CURRENT SOCIAL, ECONOMIC AND LAND-USE STATUS. ... III-D-47
4.1. POPULATION CHARACTERISTICS III-D-47
4.1.1. DENSITY III-D-47
4.1.2. RURAL/URBAN CONFIGURATION III-D-47
4.1.3. STABILITY OF RESIDENCE III-D-48
4.1.4. MIGRATION III-D-49
4.1.5. AGE III-D-49
4.1.6. SEX COMPOSITION III-D-50
4.1.7. MARITAL STATUS III-D-50
4.1.8. ETHNIC COMPOSITION III-D-51
4.2. SOCIO-ECONOMIC CHARACTREISTICS III-D-51
4.2.1. INCOME III-D-51
4.2.2. THE FARM POPULATION III-D-53
4.2.3. SELECTED OCCUPATIONAL
CHARACTERISTICS III-D-54
4.2.4. UNEMPLOYMENT III-D-54
4.2.5. WOMEN IN THE LABOR FORCE . III-D-55
4.2.6. COMMUTING WORKERS III-D-55
4.2.7. EDUCATIONAL LEVELS III-D-55
4.2.8. HOUSING III-D-56
4.3. LAND USE III-D-57
4.3.1. COAL . III-D-57
4.3.2. FORESTS III-D-57
4.3.3. FARMLAND III-D-57
5. DEMOGRAPHIC PROFILES AND IMPACT ANALYSIS:
KENTUCKY. .... III-D-61
5.1. RUSSELL COUNTY III-D-61
5.1.1. LAND USE . III-D-61
5.1.2. RECREATIONAL AND CULTURAL
FACILITIES III-D-61
5.1.3. RESIDENCE III-D-61
5.1.4. AGE STRUCTURE III-D-62
5.1.5. EDUCATION III-D-62
5.1.6. HOUSING III-D-63
5.1.7. ECONOMIC ACTIVITY III-D-63
5.1.8. INCOME III-D-64
5.1.9. IMPACT ASSESSMENT III-D-65
III-D-vi
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5.2. TRIGS, LIVINGSTON, MARSHALL, BALLARD,
AND CARLISLE COUNTIES III-D-66
5.2.1. LAND USE III-D-67
5.2.2. RECREATIONAL FACILITIES III-D-67
5.2.3. RESIDENCE III-D-68
5.2.4. AGE STRUCTURE III-D-69
5.2.5. MARITAL STRUCTURE . . III-D-70
5.2.6. EDUCATION III-D-70
5.2.7. HOUSING III-D-70
5.2.8. ECONOMIC ACTIVITIES III-D-71
5.2.9. INCOME III-D-73
5.2.10. IMPACT ASSESSMENT III-D-73
5.3. HENDERSON, UNION, WEBSTER, MCLEAN AND
BUTLER COUNTIES III-D-75
5.3.1. 'LAND USE iii-D-76
5.3.2. RECREATIONAL AND CULTURAL
AMENITIES III-D-77
5.3.3. RESIDENCE III-D-78
5.3.4. AGE STRUCTURE III-D-79
5.3.5. MARITAL STRUCTURE III-D-80
5.3.6. 'EDUCATION III-D-SO
5.3.7. HOUSING III-D-80
5.3.8. ECONOMIC ACTIVITIES III-D-81
5.3.9. INCOME III-D-83
5.3.10. IMPACT ASSESSMENT III-D-84
5.4. MEADE AND BRECKINRIDGE COUNTIES III-D-85
5.4.1. LAND USE III-D-85
5.4.2. RECREATIONAL FACILITIES III-D-86
5.4.3. RESIDENCE III-D-86
5.4.4. AGE STRUCTURE III-D-86
5.4.5. MARITAL STRUCTURE III-D-86
5.4.6. EDUCATION III-D-87
5.4.7. HOUSING III-D-87
5.4.8. ECONOMIC ACTIVITIES III-D-87
5.4.9. INCOME III-D-88
5.4.10. IMPACT ASSESSMENT III-D-89
5.5. SCOTT COUNTY III-D-90
5.5.1. LAND USE III-D-90
5.5.2. RECREATIONAL AND CULTURAL
AMENITIES III-D-90
5.5.3. RESIDENCE III-D-90
5.5.4. AGE STRUCTURE III-D-91
5.5.5. MARITAL STRUCTURE III-D-91
Ilf-D-
vn
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5.5.6. EDUCATION III-D-91
5.5.7. HOUSING III-D-91
5.5.8. ECONOMIC ACTIVITY . III-D-92
5.5.9. INCOME III-D-93
5.5.10. IMPACT ASSESSMENT III-D-93
5.6. BOONE, CARROLL TRIMBLE, OWEN AND
GALLATIN COUNTIES III-D-95
5.6.1. LAND USE III-D-96
5.6.2. RECREATIONAL AND CULTURAL
AMENITIES III-D-96
5.6.3. RESIDENCE III-D-97
5.6.4. AGE STRUCTURE III-D-98
5.6.5. MARITAL STRUCTURE . . III-D-99
5.6.6. EDUCATION III-D-99
5.6.7. HOUSING III-D-99
5.6.8. ECONOMIC ACTIVITIES III-D-100
5.6.9. INCOME III-D-102
5.6.10. IMPACT ASSESSMENT III-D-102
5.7. BRACKEN, MASON, LEWIS, AND GREENUP
COUNTIES III-D-104
5.7.1. LAND USE III-D-104
5.7.2. RECREATIONAL AND CULTURAL
AMENITIES III-D-105
5.7.3. RESIDENCE III-D-105
5.7.4. AGE STRUCTURE III-D-106
5.7.5. MARITAL STRUCTURE III-D-107
5.7.6. EDUCATION III-D-108
5.7.7. HOUSING III-D-108
5.7.8. ECONOMIC ACTIVITY III-D-108
5.7.9. INCOME III-D-112
5.7.10. IMPACT ASSESSMENT . ...... III-D-113
5.8. JEFFERSON COUNTY III-D-115
5.8.1. LAND USE III-D-115
5.8.2. RESIDENCE III-D-115
5.8.3. AGE STRUCTURE III-D-116
5.8.4. MARITAL STRUCTURE III-D-116
5.8.5. EDUCATION III-D-116
5.8.6. HOUSING III-D-117
5.8.7. ECONOMIC ACTIVITIES III-D-117
5.8.8. INCOME III-D-110
5.8.9. IMPACT ASSESSMENT III-D-118
III-D-viii
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6. DEMOGRAPHIC PROFILES AND IMPACT ANALYSIS:
ILLINOIS ..................... III-D-119
6.1. MERCER, HENDERSON AND HANCOCK COUNTIES. . III-D-119
6.1.1. LAND USE ........... III-D-119
6.1.2. RESIDENCE ........... III-D-120
6.1.3. AGE STRUCTURE ......... III-D-121
6.1.4. MARITAL STRUCTURE ....... III-D-122
6.1.5. EDUCATION ....... .... III-D-122
6.1.6. HOUSING ........... III-D-122
6.1.7. ECONOMIC ACTIVITIES ...... III-D-123
6.1.8. INCOME ............ III-D-124
6.1.9. IMPACT ASSESSMENT ....... III-D-125
6.2. IROQUOIS, LIVINGSTON, GRUNDY, LASALLE,
MARSHALL AND DEWITT COUNTIES ....... III-D-126
6.2.1. LAND USE ........... III-D-127
6.2.2. RESIDENCE .......... III-D-128
6.2.3. AGE STRUCTURE ........ III-D-129
6.2.4. MARITAL STRUCTURE ....... III-D-129
6.2.5. EDUCATION ....... .... III-D-130
6.2.6. HOUSING ............ III-D-130
6.2.7. ECONOMIC ACTIVITIES ...... III-D-131
6.2.8. INCOME .............. III-D-133
6.2.9. IMPACT ASSESSMENT. ...... III-D-133
6.3. FULTON, SCHULYER, BROWN, CASS, SCOTT,
GREENE, AND JERSEY COUNTIES . ...... III-DJ35
6.3.1. LAND USE ........... III-D^36
6.3.2. RESIDENCE .......... III-DJ37
6.3.3. AGE STRUCTURE ........ III-D-T38
6.3.4. MARITAL STRUCTURE ...... III-D>138
6.3.5. EDUCATION .......... III-D-139
6.3.6. HOUSING ........... III-D-139
6.3.7. ECONOMIC ACTIVITIES ...... 111-0^141
6.3.8. INCOME ........... III-D-143
6.3.9. IMPACT ASSESSMENT ...... III-D-143
6.4. ST. CLAIR, WASHINGTON AND PERRY COUNTIES 111-0^45
6.4.1. LAND USE ........... III
6.4.2. RESIDENCE .......... III-D^46
6.4.3. AGE STRUCTURE ........ III-D-147
6.4.4. MARITAL STRUCTURE ...... III-D^48
6.4.5. EDUCATION .......... HI-0^48
6.4.6. HOUSING ........... III-D^48
6.4.7. ECONOMIC ACTIVITIES ..... III-D-149
6.4.8. INCOME ............ III-D-151
6.4.9. IMPACT ASSESSMENT ...... III-D-152
III-D-ix
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6.5. PULASKI COUNTY III-D-154
6.5.1. LAND USE III-D-154
6.5.2. RESIDENCE III-D-154
6.5.3. AGE STRUCTURE III-D-155
6.5.4. MARITAL STRUCTURE III-D-155
6.5.5. EDUCATION III-D-155
6.5.6. HOUSING III-D-155
6.5.7. ECONOMIC ACTIVITIES III-D-155
6.5.8. INCOME III-D-156
6.5.9. IMPACT ASSESSMENT III-D-157
6.6. HAMILTON, WHITE, LAWRENCE, JASPER AND
CLARK COUNTIES III-D-158
6.6.1. LAND USE III-D-159
6.6.2. RESIDENCE III-D-160
6.6.3. AGE STRUCTURE III-D-162
6.6.4. MARITAL STRUCTURE III-D-162
6.6.5. EDUCATION III-D-162
6.6.6. HOUSING III-D-163
6.6.7. ECONOMIC ACTIVITIES III-D-164
6.6.8. INCOME III-D-165
6.6.9. IMPACT ASSESSMENT III-D-166
1. DEMOGRAPHIC PROFILES AND IMPACT ANALYSIS: INDIANA III-D-167
7.1. JASPER COUNTY III-D-167
7.1.1. LAND USE III-D-167
7.1.2. RESIDENCE III-D-167
7.1.3. AGE STRUCTURE III-D-168
7.1.4. MARITAL STRUCTURE III-D-168
7.1.5. EDUCATION III-D-168
7.1.6. HOUSING III-D-169
7.1.7. ECONOMIC ACTIVITIES III-D-169
7.1.8. INCOME III-D-170
7.1.9. IMPACT ASSESSMENT III-D-171
7.2. TIPPECANOE, FOUNTAIN, WARREN AND VERMILLION
COUNTIES III-D-172
7.2.1. LAND USE III-D-172
7.2.2. RESIDENCE III-CM73
7.2.3. AGE STRUCTURE III-D-174
7.2.4. MARITAL STRUCTURE IIHW74
7.2.5. EDUCATION III-D^75
7.2.6. HOUSING III-D-175
7.2.7. ECONOMIC ACTIVITIES III-D-176
7.2.8. INCOME. . : III-D-178
7.2.9. IMPACT ASSESSMENT IIHH78
III-D-x
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7.3. SULLIVAN, GREENE, KNOX, DAVIESS, MARTIN,
GIBSON, PIKE AND DUBOIS COUNTIES III-D-180
7.3.1. LAND USE III-D-182
7.3.2. RESIDENCE III-D-183
7.3.3. AGE STRUCTURE III-D-184
7.3.4. MARITAL STRUCTURE III-D-185
7.3.5. EDUCATION III-D-185
7.3.6. HOUSING III-D-T86
7.3.7. ECONOMIC ACTIVITIES III-D-188
7.3.8. INCOME III-D-191
7.3.9. I/PACT ASSESSMENT III-D-191
7.4. LAWRENCE AND JACKSON COUNTIES ....... III-D-193
7.4.1. LAND USE III-D-193
7.4.2. RESIDENCE III-D-193
7.4.3. AGE STRUCTURE III-D-194
7.4.4. MARITAL STRUCTURE III-D-194
7.4.5. EDUCATION III-D-194
7.4.6. HOUSING III-D-195
7.4.7. ECONOMIC ACTIVITIES III-D-195
7.4.8. INCOME III-D-197
7.4.9. IMPACT ASSESSMENT III-D-197
7.5. POSEY, WARRICK, SPENCER, PERRY, CRAWFORD,
AND HARRISON COUNTIES III-D-198
7.5.1. LAND USE III-D-199
7.5.2. RESIDENCE III-D-200
7.5.3. AGE STRUCTURE III-D-201
7.5.4. MARITAL STRUCTURE III-D-202
7.5.5. EDUCATION III-D-202
7.5.6. HOUSING III-D-202
7.5.7. ECONOMIC ACTIVITY III-D-203
7.5.8. INCOME III-D-205
7.5.9. IMPACT ASSESSMENT III-D-206
7.6. CLARK, JEFFERSON, SWITZERLAND, OHIO AND
DEARBORN COUNTIES III-D-207
7.6.1. LAND USE III-D-208
7.6.2. RESIDENCE III-D-208
7.6.3. AGE STRUCTURE III-D-209
7.6.4. MARITAL STRUCTURE III-D-210
7.6.5. EDUCATION III-D-210
7.6.6. HOUSING III-D-211
7.6.7. ECONOMIC ACTIVITIES III-D-212
7.6.8. INCOME III-D-213
7.6.9. IMPACT ASSESSMENT IIT-D-214
III-D-xi
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8. DEMOGRAPHIC PROFILES AND IMPACT ANALYSIS: OHIO. . . . III-D-215
8.1. HAMILTON, BUTLER, WARREN, MONTGOMERY,
MIAMI, AND CLARK COUNTIES III-D-215
8.1.1. LAND USE III-D-216
8.1.2. RESIDENCE III-D-217
8.1.3. AGE STRUCTURE III-D-218
8.1.4. MARITAL STRUCTURE III-D-219
8.1.5. EDUCATION .... III-D-219
8.1.6. HOUSING III-D-219
8.1.7. ECONOMIC ACTIVITIES III-D-220
8.1.8. INCOME III-D-222
8.1.9. IMPACT ASSESSMENT III-D-222
8.2. ADAMS, CLERMONT AND BROWN COUNTIES .... III-D-223
8.2.1. LAND USE III-D-223
8.2.2. RESIDENCE III-D-224
8.2.3. AGE STRUCTURE III-D-225
8.2.4. MARITAL STRUCTURE III-D-226
8.2.5. EDUCATION III-D-226
8.2.6. HOUSING III-D-226
8.2.7. ECONOMIC ACTIVITIES III-D-227
8.2.8. INCOME III-D-228
8.2.9. IMPACT ASSESSMENT III-D-229
8.3. FRANKLIN, PICKAWAY, ROSS, PIKE AND SCIOTO
COUNTIES III-D-230
8.3.1. LAND USE III-D-230
8.3.2. RESIDENCE III-D-231
8.3.3. AGE STRUCTURE III-D-233
8.3.4. MARITAL STRUCTURE III-D-233
8.3.5. EDUCATION III-D-234
8.3.6. HOUSING III-D-234
8.3.7. ECONOMIC ACTIVITIES III-D-235
8.3.8. INCOME III-D-237
8.3.9. IMPACT ASSESSMENT III-D-238
8.4. LAWRENCE, GALLIA, MEIGS, ATHENS, WASHINGTON,
MONROE, BELMONT AND JEFFERSON COUNTIES . . III-D-239
8.4.1. LAND USE III-D-24Q
8.4.2. RESIDENCE III-D-242
8.4.3. AGE STRUCTURE III-D-243
8.4.4. MARITAL STRUCTURE III-D-243
8.4.5. EDUCATION III-D-244
8.4.6. HOUSING III-D-245
8.4.7. ECONOMIC ACTIVITIES III-D-246
8.4.8. INCOME III-D-249
8.4.9. IMPACT ASSESSMENT III-D-249
III-D-xii
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8.5. MORGAN, MUSKINGUM AND COSHOCTON COUNTIES III-D-251
8.5.1. LAND USE III-C-25T
8.5.2. RESIDENCE III-D-252
8.5.3. AGE STRUCTURE III-D-253
8.5.4. MARITAL STRUCTURE III-D-253
8.5.5. EDUCATION III-D-254
8.5.6. HOUSING III-D-254
8.5.7. ECONOMIC ACTIVITIES III-D-255
8.5.8. INCOME III-D-256
8.5.9. IMPACT ASSESSMENT III-D-257
8.6. MAHONING COUNTY III-D-258
8.6.1. LAND USE III-D-258
8.6.2. RESIDENCE III-D-258
8.6.3. AGE STRUCTURE III-D-258
8.6.4. MARITAL STRUCTURE III-D-259
8.6.5. EDUCATION III-D-259
8.6.6. HOUSING III-D-259
8.6.7. ECONOMIC ACTIVITIES III-D-259
8.6.8. INCOME III-D-261
8.6.9. IMPACT ASSESSMENT III-D-261
9. SUMMARY III-D-263
APPENDIX A III-D-267
MAP OF ORBES REGION III-D-268
INSTRUMENTAL ORIENTATION MAPS III-D-270
TECHNOLOGICAL FEASIBILITY SUB-ORIENTATION
ECONOMIC BENEFIT SUB-ORIENTATION
TERRITORIAL ORIENTATION MAPS III-D-277
SENTIMENTAL ORIENTATION MAPS III-D-283
PRIMORDIAL BELONGINGNESS SUB-ORIENTATION
PRESTIGE SUB-ORIENTATION
SYMBOLIC ORIENTATION MAPS. . . ' III-D-366
III-D-xiii
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TABLES
table page
III-D-1 THE PARADIGM FOR SOCIAL ECOLOGICAL
ANALYSIS III-D-2
III-D-2 FRAMEWORK FOR A TYPOLOGY OF CONFLICTS
BETWEEN ENVIRONMENTAL SUB-ORIENTATIONS. .... III-D-25
III-D-3 KY-1 FARMS BY TYPES III-D-63
III-D-4 KY-1 COUNTY BUSINESS PATTERNS, 1973 III-D-64
III-D-5 KY-2 LAND USE III-D-67
III-D-6 KY-2 DISTRIBUTION OF POPULATION III-D-68
III-D-7 KY-2 POPULATION SHIFTS III-D-68
III-D-8 KY-2 HOUSING, 1970 III-D-70
III-D-8 KY-2 FARMING, 1969 III-D-71
III-D-9 KY-2 COUNTY BUSINESS PATTERNS, 1973 III-D-72
III-D-10 KY-2 INCOME III-D-73
III-D-11 KY-3 POPULATION CENTERS III-D-76
III-D-12 KY-3 MINERAL PRODUCTION ,1973 III-D-77
III-D-13 KY-3 LAND USE III-D-77
III-D-14 KY-3 DISTRIBUTION OF POPULATION III-D-78
III-D-15 KY-3 POPULATION SHIFTS III-D-79
III-D-16 KY-3 RESIDENTIAL STABILITY III-D-79
III-D-17 KY-3 HOUSING CHANGES, 1960-70 . -. III-D-80
III-D-18 KY-3 HOUSING CHARACTERISTICS, 1970 ....... III-D-81
III-D-19 KY-3 FARMING, 1969 III-D-81
III-D-20 KY-3 COUNTY BUSINESS PATTERNS, 1973 III-D-82
III-D-21 KY-3 INCOME III-D-83
r.
III-D-xiv
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III-D-22 KY-4 COMMUNITIES OVER 1,000 III-D-85
III-D-23 KY-4 RECREATIONAL LAND USE III-D-85
III-D-24 KY-4 FARMING, 1969 IM-D-87
III-D-25 KY-4 COUNTY BUSINESS PATTERNS, 1973 III-D-88
III-D-26 KY-5 FARMING, 1969 III-D-.92
III-D-27 KY-5 COUNTY BUSINESS PATTERNS, 1973 III-D-93
III-D-28 KY-6 LAND USE III-D-96
III-D-29 KY-6 RECREATIONAL LAND III-D-97
III-D-30 KY-6 DISTRIBUTION OF THE POPULATION III-D-97
III-D-31 KY-6 RESIDENTIAL STABILITY III-D-98
III-D-32 KY-6 POPULATION SHIFTS III-D-98
III-D-33 KY-6 FARMING, 1969 III-D-100
III-D-34 KY-6 COUNTY BUSINESS PATTERNS, 1973 . III-D-10T
III-D-35 KY-6 INCOME III-D-102
III-D-36 KY-7 LAND USE III-D-104
III-D-37 KY-7 RESIDENTIAL STABILITY III-D-105
III-D-38 KY-7 POPULATION SHIFTS III-D-106
III-D-39 KY-7 HOUSING, 1970 III-D-108
III-D-40 KY-7 COUNTY BUSINESS PATTERNS, 1973 III-D-109
III-D-41 KY-7 FARMING, 1969 III-D-111
III-D-42 KY-7 TOTAL VALUE OF FARM PRODUCTS, 1969 III-D-112
III-D-43 KY-7 INCOME III-D-113
III-D-44 KY-8 POPULATION SHIFTS III-D-116
III-D-45 KY-8 COUNTY BUSINESS PATTERNS, 1973 III-D-117
III-D-xv
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III-D-46 IL-1 LAND USE III-D-llT
III-D-47 IL-1 DISTRIBUTION OF POPULATION. ...... III-D-120
III-D-48 IL-1 POPULATION SHIFTS III-D-120
III-D-49 IL-1 RESIDENTIAL STABILITY III-D-121
III-D-50 11-1 HOUSING, 1970 III-D-122
III-D-51 IL-1 COUNTY BUSINESS PATTERNS, 1973 III-D-123
III-D-52 IL-1 FARMING, 1969 III-D-124
III-D-53 IL-1 INCOME III-D-124
III-D-54 IL-2 LAND USE. III-D-127
III-D-55 IL-2 DISTRIBUTION OF POPULATION III-D-128
III-D-56 IL-2 RESIDENTIAL STABILITY III-D-128
III-D-57 IL-2 POPULATION SHIFTS III-D-129
III-D-58 IL-2 HOUSING, 1970 III-D-130
III-D-59 IL-2 FARMING, 1969 III-D-131
III-D-60 IL-2 COUNTY BUSINESS PATTERNS, 1973 III-D-132
III-D-61 IL-2 INCOME III-D-133
III-D-62 IL-3 LAND USE III-D-136
III-D-63 IL-3 RESIDENTIAL STABILITY III-D-137
III-D-64 IL-3 POPULATION SHIFTS III-D-137
III-D-65 IL-3 POPULATION DISTRIBUTION III-D-137
III-D-66 IL-3 HOUSING, 1970 III-D-140
III-D-67 IL-4 FARMING, 1969 III-D-14T
III-D-68 IL-5 COUNTY BUSINESS PATTERNS, 1973 III-D-142
III-D-69 IL-6 INCOME LEVELS III-D-143
III-D-70 IL-4 POPULATION SHIFTS III-D-146
III-D-71 IL-4 RESIDENTIAL STABILITY. ... III-D-147
III-D-72 IL-4 POPULATION DISTRIBUTION III-D-147
III-D-xvi
-------
III-D-73 IL-4 HOUSING, 1970 III-D-149
III-D-74 IL-4 COUNTY BUSINESS PATTERNS, 1973 . . III-D-150
III-D-75 IL-4 FARMING, 1969 III-D-151
III-D-76 IL-4 INCOME III-D-152
III-D-77 IL-5 COUNTY BUSINESS PATTERNS, 1973 . . III-D-156
III-D-78 IL-5 FARMING, 1969 III-D-156
III-D-79 IL-6 LAND USE III-D-160
III-D-80 IL-6 MINERAL PRODUCTION, 1973 III-D-160
III-D-81 IL-6 DISTRIBUTION OF POPULATION .... III-D-161
III-D-82 IL-6 RESIDENTIAL STABILITY III-D-161
III-D-83 IL-6 POPULATION SHIFTS III-D-162
III-D-84 IL-6 HOUSING, 1970 III-D-163
III-D-85 IL-6 COUNTY BUSINESS PATTERNS, 1973 . . III-D-164
III-D-86 IL-6 FARMING STATISTICS, 1969 III-D-165
III-D-87 IL-6 INCOME III-D-165
III-D-88 IN-1 POPULATION SHIFTS III-D-167
III-D-89 IN-1 COUNTY BUSINESS PATTERNS, 1973 . . III-D-169
III-D-90 IN-1 FARMING, 1969 III-D-170
III-D-91 IN-1 INCOME III-D-170
III-D-92 IN-2 LAND USE III-D-173
III-D-93 IN-2 RESIDENTIAL STABILITY ...... III-D-173
III-D-94 IN-2 HOUSING, 1970 III-D-175
III-D-95 IN-2 COUNTY BUSINESS PATTERNS, 1973 . . III-D-176
III-D-96 IN-2 FARMING, 1969 III-D-178
III-D-97 IN-2 INCOME III-D-178
III-D-98 IN-3 POWER GENERATING CAPACITY,
SOUTHWESTERN INDIANA III-D-TS1
III-D-xvii
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III-D-99 IN-3 LAND USE III-D-182
III-D-100 IN-3 DISTRIBUTION OF POPULATION III-D-183
III-D-101 IN-3 RESIDENTIAL STABILITY III-D-183
III-D-102 IN-3 POPULATION SHIFTS III-D-184
III-D-103 IN-3 HOUSING, 1970 III-D-187
III-D-104 IN-3 COUNTY BUSINESS PATTERNS, 1973. . . . .III-D-189
III-D-105 IN-3 FARMING, 1969 III-D-190
III-D-106 IN-3 INCOME III-D-191
III-D-107 IN-4 POPULATION DISTRIBUTION, SHIFTS
AND STABILITY III-D-194
III-D-108 IN-4 HOUSING, 1970 III-D-195
III-D-109 IN-4 COUNTY BUSINESS PATTERNS, 1973 III-D-195
III-D-110 IN-4 FARMING, 1969 III-D-196
III-D-111 IN-4 INCOME III-D-197
III-D-112 IN-5 POWER GENERATING CAPACITY III-D-199
III-D-113 IN-5 LAND USE III-D-200
III-D-114 IN-5 POPULATION DISTRIBUTION III-D-200
III-D-115 IN-5 POPULATION SHIFTS III-D-201
III-D-116 IN-5 RESIDENTIAL STABILITY .III-D-201
III-D-117 IN-5 HOUSING, 1970 III-D-203
III-D-118 IN-5 COUNTY BUSINESS PATTERNS, 1973 . . . .III-D-203
III-D-119 IN-5 FARMING, 1969 III-D-205
III-D-120 IN-5 INCOME LEVELS III-D-205
III-D-121 IN-6 POWER GENERATING CAPACITY III-D-207
III-D-122 IN-6 LAND USE III-D-208
III-D-123 IN-6 POPULATION DISTRIBUTION, 1970 III-D-208;
III-D-124 IN-6 POPULATION SHIFTS III-D-209!
III-D-xviii
-------
III-D-125 IN-6 RESIDENTIAL STABILITY III-D-209
III-D-126 IN-6 EDUCATION III-D-211
III-D-127 IN-6 HOUSING, 1970 III-D-211
III-D-128 IN-6 COUNTY BUSINESS PATTERNS, 1973 ..... III-D-212
III-D-129 IN-6 FARMING, 1969. ... III-D-213
III-D-130 IN-6 INCOME III-D-213
III-D-131 0-1 POWER PLANT DISTRIBUTION ........ III-D-215
III-D-132 0-1 LAND USE III-D-216
III-D-133 0-1 RECREATIONAL LAND III-D-217
III-D-134 0-1 POPULATION DISTRIBUTION III-D-217
III-D-135 0-1 RESIDENTIAL STABILITY III-D-218
III-D-136 0-1 POPULATION SHIFTS. . . . III-D-218
III-D-137 0-1 EDUCATIONAL LEVELS ... III-D-219
III-D-138 0-1 HOUSING, 1970 'iII-D-220
III-D-139 0-1 COUNTY BUSINESS PATTERNS, 1973 III-D-220
III-D-140 0-1 FARMING, 1969 III-D-221
III-D-141 0-1 INCOME LEVELS III-D-222
III-D-142 0-2 LAND USE III-D-224
III-D-143 0-2 POPULATION SHIFTS III-D-224
III-D-144 0-2 DISTRIBUTION OF POPULATION III-D-225
III-D-145 0-2 RESIDENTIAL STABILITY III-D-225
III-D-146 0-2 EDUCATIONAL LEVELS III-D-226
III-D-147 0-2 HOUSING PATTERNS, 1970 III-D-227
III-D-148 0-2 COUNTY BUSINESS PATTERNS, 1973 III-D-227
III-D-149 0-2 FARMING STATISTICS, 1969 III-D-228
III-D-150 0-2. INCOME . III-D-229
HI_D-xix
-------
III-D-151 0-3 LAND USE III-D-231
III-D-152 0-3 RECREATIONAL ACREAGE III-D-231
III-D-153 0-3 RESIDENTIAL STABILITY ... III-D-231
III-D-154 0-3 POPULATION SHIFTS III-D-232
III-D-155 0-3 POPULATION DISTRIBUTION III-D 232
III-D-156 0-3 EDUCATIONAL LEVELS • . III-D-234
III-D-157 0-3 HOUSING, 1970 III-D-235
III-D-158 0-3 COUNTY BUSINESS PATTERNS, 1973 III-D-235
III-D-159 0-3 FARMING, 1969 III-D-237
III-D-160 0-3 INCOME LEVELS III-D-237
III-D-161 0-4 PRESENT GENERATING CAPACITY III-D-239
III-D-162 0-4 GENERATING CAPACITY IN A.D. 2000 . . . III-D- 240
III-D-163 0-4 LAND USE . III-D 241
III-D-164 0-4 MINERAL PRODUCTION. . . III-D- 241
III-D-165 0-4 RESIDENTIAL STABILITY III-D-242
III-D-166 0-4 POPULATION SHIFTS. . . III-D- 242
III-D-167 0-4 DISTRIBUTION OF POPULATION III-D-243
III-D-168 0-4 EDUCATIONAL LEVELS III-D-244
III-D-169 0-4 HOUSING VALUES AND CHANGES . . . III-D-245
III-D-170 0-4 HOUSING CHARACTERISTICS, 1970 ..... III-D- 245
III-D-171 0-4 COUNTY BUSINESS PATTERNS, 1973 III-D-247
III-D-172 0-4 FARMING, 1969 III-D-248
III-D-173 0-4 INCOME III-D-249
III-D-174 0-5 LAND USE III-D- 251
III-D-175 0-5 MINERAL PRODUCTION III-D-252
III-D-176 0-5 POPULATION SHIFTS III-D-252
III-D-xx
-------
III-D-177 0-5 POPULATION STABILITY AND
DISTRIBUTION III-D-253
III-D-178 0-5 EDUCATIONAL LEVELS III-D-254
III-D-179 0-5 HOUSING, 1970 III-D-254
III-D-180 0-5 COUNTY BUSINESS PATTERNS, 1973. . . .III-D-255
III-D-181 0-5 FARMING, 1969 III-D-256
III-D-182 0-5 INCOME LEVELS III-D-256
III-D-xxii
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APPENDIX
MAPS
map page
III-D-1 OHIO RIVER BASIN STUDY (ORBES) REGION III-D-269
III-D-2 COAL PRODUCING COUNTIES, 1974 III-D-271
III-D-3 PERCENTAGE OF LAND IN FARMS, 1969 III-D-272
III-D-4 PERCENTAGE OF LAND IN FOREST III-D-273
III-D-5 SMSA'S, 1970 AND 1974 III-D-274
III-D-6 MAJOR HIGHWAY TRANSPORTATION ROUTES III-D-275
III-D-7 MAJOR RIVERS III-D-276
III-D-8 1975 GENERATING CAPACITY III-D-278
III-D-9 1985 GENERATING CAPACITY WITH SCENARIO I NEW III-D-279
UNITS
III-D-10 1985 GENERATING CAPACITY WITH SCENARIO II NEW III-D-280
UNITS
III-D-11 1985 GENERATING CAPACITY WITH SCENARIO III NEW III-D-281
UNITS
III-D-12 1985 GENERATING CAPACITY WITH SCENARIO IV NEW III-D-282
UNITS
III-D-13 RESIDENCE OF POPULATION IN 1970 ........ IH-D-284
III-D-14 POPULATION DENSITY III-D-285
III-D-15 PERCENTAGE OF POPULATION LIVING ON FARMS .... III-D-286
III-D-16 NET MIGRATION, 1960 - 1970 III-D-287
III-D-17 NET MIGRATION, 1970 - 1974 III-D-288
III-D-18 POPULATION CHANGE, 1960 - 1970 . . . III-D-289
III-D-19 PERCENTAGE CHANGE IN FARM POPULATION, 1960 - III-D-290
1970
III-D-20 PERCENTAGE CHANGE IN URBAN POPULATION, 1960 - III-D-291
1970
III-D-xxii
-------
map
III-D-21 PERCENTAGE CHANGE IN RURAL POPULATION, 1960 - III-D-292
1970
III-D-22 PERCENTAGE OF POPULATION FOREIGN BORN OR OF III-D-293
FOREIGN OR MIXED PARENTAGE
III-D-23 PERCENTAGE OF NATIVE POPULATION RESIDING IN III-D-294
STATE OF BIRTH
III-D-24 PERCENTAGE OF NATIVE POPULATION BORN IN NORTH- III-D-295
EAST . .
III-D-25 PERCENTAGE OF NATIVE POPULATION BORN IN THE III-D-296
SOUTH
III-D-26 PERCENTAGE OF NATIVE POPULATION BORN IN NORTH III-D-297
CENTRAL U.S
III-D-27 PERCENTAGE OF POPULATION RESIDING IN SAME III-D-298
COUNTY IN 1965
III-D-28 PERCENTAGE OF POPULATION RESIDING IN SAME III-D-299
STATE IN 1965
III-D-29 MEDIAN AGE, 1970 III-D-300
III-D-30 BIRTH RATE PER THOUSAND, 1968 III-D-301
III-D-31 DEATH RATE PER THOUSAND, 1969 III-D-302
III-D-32 PERCENTAGE OF POPULATION UNDER 18, 1970 .... III-D-303
III-D-33 PERCENTAGE OF POPULATION AGED 20 TO 29 III-D-304
III-D-34 PERCENTAGE OF POPULATION AGED 30 TO 54 III-D-305
III-D-35 PERCENTAGE OF POPULATION 65 OR OLDER, 1970 . . . III-D-306
III-D-36 MALES AS A PERCENTAGE OF POPULATION 18 OR III-D-307
OVER
III-D-37 SINGLE MEN AS PERCENTAGE OF MALE POPULATION III-D-308
14 OR OLDER
III-D-38 SINGLE WOMEN AS PERCENTAGE OF FEMALE POPULA- III-D-309
TION 14 OR OLDER
III-D-xxiii
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map
III-D-39
III-D-40
1 1 1-0-41
III-D-42
III-D-43
III-D-44
III-D-45
III-D-46
III-D-47
III-D-48
III-D-49
III-D-50
III-D-51
III-D-52
III-D-53
III-D-54
III-D-55
DIVORCED MEN AS PERCENTAGE OF MALES 14 OR
OVER
DIVORCED WOMEN AS PERCENTAGE OF FEMALES 14
OR OLDER
WIDOWED MEN AS PERCENTAGE OF MALES 14 OR
OLDER
WIDOWED WOMEN AS PERCENTAGE OF FEMALES 14
OR OLDER
MARRIED MALES AS PERCENTAGE OF MALE POPULA-
TION 14 OR OVER
MARRIED WOMEN AS A PERCENTAGE OF FEMALES 14
OR OVER
HUSBAND-WIFE FAMILIES AS A PERCENTAGE OF
TOTAL FAMILIES
PERCENTAGE OF FAMILIES WITH CHILDREN UNDER 18. .
PERCENTAGE OF FAMILIES WITH A FEMALE HEAD . . .
MEDIAN SCHOOL YEARS COMPLETED, POPULATION
OVER 25
PERCENTAGE OF PERSONS 25 OR OLDER WITH LESS
THAN FOUR YEARS OF HIGH SCHOOL, 1970
PAID CIVILIAN WAGE AND SALARY EMPLOYMENT
COVERED IN COUNTY BUSINESS PATTERNS, 1973. . . .
RATIO OF WORKERS IN COUNTY TO WORKERS RESIDING
IN COUNTY, 1970
PRIMARY ECONOMIC ACTIVITY •. . .
VALUE ADDED BY MANUFACTURE, 1972
FEMALES AS A PERCENTAGE OF CIVILIAN WORK
FORCE, 1970
PERCENTAGE OF FAMILIES WITH BOTH HUSBAND AND
WIFF IN WORK FORCE. 1970
III-D-310
III-D-311
III-D-312
III-D-313
III-D-314
III-D-315
III-D-316
III-D-317
III-D-313
III-D-319
III-D-320
III-D-321
III-D-322
III-D-323
III-D-324
III-D-325
III-D-326
III-D-xxiv
-------
map
III-D-56 UNEMPLOYED AS PERCENTAGE OF CIVILIAN WORK III-D-327
FORCE, 1970 . . . . :
III-D-57 PERCENTAGE OF EMPLOYED CIVILIAN LABOR FORCE III-D-328
IN PROFESSIONS OR MANAGEMENT
III-D-58 PERCENTAGE OF EMPLOYED CIVILIAN LABOR FORCE III-D-329
WORKING IN CONSTRUCTION, 1970
III-D-59 PERCENTAGE OF EMPLOYED CIVILIAN LABOR FORCE III-D-330
WORKING IN WHOLESALE AND RETAIL TRADE, 1970 . .
III-D-60 PERCENTAGE OF CIVILIAN LABOR FORCE EMPLOYED III-D-331
AS CRAFTSMEN OR FOREMEN, 1970
III^D-61 FEDERAL CIVILIAN EMPLOYMENT, DECEMBER 31, III-D-332
1974
III-D-62 PERCENTAGE OF EMPLOYED CIVILIAN LABOR FORCE III-D-333
IN GOVERNMENT, 1970
III-D-63 PERCENTAGE OF EMPLOYED CIVILIAN LABOR FORCE III-D-334
WORKING IN MANUFACTURING, 1970
III-D-64 PERCENTAGE OF EMPLOYED CIVILIAN LABOR FORCE III-D-335
IN EDUCATIONAL SERVICES, 1970
III-D-65 PERCENTAGE OF FARM OPERATORS WORKING 100 OR III-D-336
MORE DAYS OFF FARM, 1969
III-D-66 MEDIAN FAMILY INCOME, 1969 III-D-337
III-D-67 PERCENTAGE OF FAMILIES WITH INCOME OF $15,000 III-r-338
OR MORE, 1969
III-D-68 MEDIAN FAMILY INCOME FOR FARM POPULATION, III-D-339
1969
III-D-69 PER CAPITA MONEY INCOME FOR 1969 III-D-340
III-D-70 PER CAPITA PERSONAL INCOME, 1973 III-D-341
III-D-71 MEDIAN HOUSEHOLD EFFECTIVE BUYING POWER, III-D-342
1974
III-D-72 PERCENTAGE OF HOUSEHOLDS WITH EFFECTIVE BUYING III-D-343
POWER LESS THAN $3,000
III-D-xxv
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III-D-73 PERCENTAGE OF HOUSEHOLDS WITH EFFECTIVE BUYING
POWER OF $15,000 OR MORE, 1974 III-D-344
III-D-74 PERCENTAGE OF FAMILIES BELOW THE LOW INCOME
LEVEL IN 1969 III-D-345
III-D-75 PERCENTAGE OF LOW INCOME POPULATION 65 OR
OLDER, 1970 . . . . HI-D-346
III-D-76 PERCENTAGE OF LOW INCOME POPULATION UNDER 18,
1970 III-D-347
III-D-77 PUBLIC ASSISTANCE, FEBRUARY, 1972: PERCENTAGE
PAID FOR OLD AGE ASSISTANCE III-D-348
III-D-78 PERCENTAGE OF PUBLIC ASSISTANCE GOING TO
FAMILIES WITH DEPENDENT CHILDREN III-D-349
III-D-79 PERCENTAGE CHANGE IN NUMBER OF HOUSEHOLDS,
1960 - 1970 III-D-350
III-D-80 PERCENTAGE CHANGE IN NUMBER OF YEAR ROUND
HOUSING UNITS, 1960 - 1970 III-D-351
III-D-81 PERCENTAGE OF YEAR ROUND HOUSING UNITS BUILT
BETWEEN 1960 AND MARCH, 1970 III-D-352
III-D-82 HOME TENURE FOR YEAR ROUND HOUSING UNITS .... III-D-353
III-D-83 PERCENTAGE OCCUPIED HOUSING UNITS LACKING
SOME OR ALL PLUMBING FACILITIES, 1970 III-D-354
III-D-84 PERCENTAGE OF OCCUPIED HOUSING UNITS WITH 1.01
OR MORE PERSONS PER ROOM, 1970 III-D-355
III-D-85 PERCENTAGE OF YEAR ROUND HOUSING UNITS IN ONE-
UNIT STRUCTURES, 1970 III-D-356
III-D-86 MEDIAN VALUE OF OWNER-OCCUPIED SINGLE FAMILY
DWELLINGS, 1970 III-D-357
III-D-87 MEDIAN GROSS RENT FOR RENTER-OCCUPIED HOUSING,
1970 III-D-358
III-D-88 PERCENTAGE CHANGE IN NUMBER OF FARMS, 1964 -
1969 III-D-359
III-D-89 PERCENTAGE CHANGE IN FARM ACREAGE, 1964 -
1969 III-D-360
III-D-xxvi
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III-D-90 AVERAGE VALUE OF FARM LAND AND BUILDINGS PER
ACRE III-D-3'61
III-D-91 AVERAGE VALUE OF AGRICULTURAL PRODUCTS PER
ACRE III-D-362
III-D-92 AVERAGE NUMBER OF ACRES PER FARM III-D-363
III-D-93 PERCENTAGE OF FARMS WITH SALES OF $2,500 OR
MORE, 1969 III-D-364
III-D-94 PERCENTAGE OF CLASS I-V FARMS WITH SALES OF
$10,000 OR MORE, 1969 III-D-366
III-D-95 STATE AND NATIONAL OUTDOOR RECREATION AREAS . . HI-D-376
III-D-96 RANKING CHRISTIAN DENOMINATIONS, 1971. ..... IH-D-368
III-D-97 MUSEUMS LISTED IN THE 1975 OFFICIAL MUSEUM
DIRECTORY . . III-D-369
III-D-98 NATIONAL REGISTER OF HISTORIC PLACES, 1976 . . . IH-D-370
III-D-xxvii
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1. INTRODUCTION
The framework for analysis of likely impacts and reactions to
power-plant siting in the ORBES region is derived from a paradigm of
environmental orientations developed by Erik Cohen which is shown in
Table III-D-1, (1, p. 51). Each sub-orientation or "mode" has mappable
referents and a spatial analysis of the Ohio River Basin and the
varying environmental orientations within the region is made utilizing
secondary information. The maps are found in Appendix A. Mapping of
the referents associated with environmental orientations has the major
virtue of being a clear mode of presentation.
We have supplemented our analysis with a thorough review of the
literature on the impact of large installations on communities and
from this survey have collected a large number of hypotheses and generali-
zations pertinent to each orientation. It is assumed that knowledge of
prevailing orientations in a county will give us a basis from which to
predict likely impacts of power plant siting and community reaction to
these impacts. Conflicts between different orientations are also
likely, some more severe than others. Where we think conflicts possible,
this too is discussed.
We have then produced demographic profiles of counties which have
been chosen as likely sites for power plant development and tried to
create, utilizing our orientational framework, knowledge of the litera-
ture, and specific knowledge of the county, a plausible picture of
impact. This study makes no claim for accuracy, for only the future
can tell us if our predictions were correct; rather likelihood and
plausibility of our impact analysis has been the goal.
III-D-1
-------
Table III-D-1
THE PARADIGM FOR SOCIAL ECOLOGICAL ANALYSIS
Orientation
to
Environment
Purpose of
Orientation
Modes of
Orientation
Regulative
Mechanisms
and
Processes
Types of
Environ-
mental
Organization
Institutions
Functional
Sphere
Instrumental
Resources
Technologi-
cal Feasi-
bility
Knowledge
Exploitative
Potentiali-
ties
Techniques
and Tech-
nology
Economic
Benefit
Market
Exchange
Land and
Property
Values
Economic
Adaptation
Territorial
Control
Strategic
Domi -
nance
Tactics
Strategy
Tactical
Stra-
tegic
Value
Military
Political
Organi-
zation
Decision-
making
Territor-
ial
Rights
and
Bound-
aries
Political
Goal Attainment
Sentimental
Attachment
Primordial
Belonging
Identi-
fication
Extent of
Belong-
ingness
Solidary
Social
Prestige
Social
Evalua-
tion
Prestige
Area
Strati-
fication-
al
Integration
Symbolic
Significance
Aesthetic
Enjoyment
Taste
Forma-
tion
Aesthetic
Value
Artistic
Moral
Religious
Meaning
Stratifi-
cation
Sacred and
Secular
Places
Moral-
Religious
Pattern Maintenance
o
PO
Within each orientation, the first mode is the less institutionalized of the two.
-------
REFERENCES
Erik Cohen. "Environmental Orientations: A Multidimensional
Approach to Social Ecology." Current Anthropology, Vol. 17,
No. 1:(1976):49-70.
III-D-3
-------
2. ENVIRONMENTAL ORIENTATION PARADIGM
2.1. THE INSTRUMENTAL ORIENTATION
Within this orientation, the environment has no value in itself,
rather it is seen as a means to an end. Therefore, the development of
resource potentials depends on what is technically feasible or economi-
cally profitable. "Natural" resources then are those which hold instru-
mental value to some person, group of persons, or other species.
"Location" of natural resources is important only in terms of their
accessibility and perceived utility.
Sub-orientations within this basic orientation are technical
feasibility and economic benefit. Features of the environment become
resources when some instrumental purpose is found for them. The techni-
cal sub-orientation leads to a perception of the environment as "exploi-
tative" potential, but is non-economic in nature. The definition of
potential depends on the state of knowledge about possible uses of
the environment, that is, on existent technology.
Knowledge in the "technical" sub-orientation is the regulatory
mechanism that organizes the environment in terms of its potential for
exploitation. Differences in knowledge concerning the environment
lead to differing definitions of its potential use. Technological
competition, or "biological economics" expresses itself in the ability
of different groups to take greater advantage of a given environment
than other groups because of their greater knowledge. Competition
concerning utilization of the environment may nor may not be directly
"social," and often is not, whereas it is in economic competition.
Knowledge of exploitative possibilities of the environment sets limits
on economic activity. Resource maps of the area will depict the resource
utilization possibilities within each domain of knowledge. Future
proposed development will alter the resource map in that resources
hitherto unexploited may take on new meaning as new facilities are
constructed. This sub-orientation is also limited by the other
orientations.
The "economic" sub-orientation is the perception of the environ-
ment in terms of the relative economic benefits that can be gained
from utilization of environmental locations or features to meet a
variety of goals. The "location" of an environmental feature or space
is important to this sub-orientation, i.e., with reference to population
centers, other resources, production and transportation facilities. The
primary economic consideration is, of course, cost. Space, then,
becomes an economically-valued entity, for it enhances or impedes access
to resources and their production potential. The point of greatest
accessibility therefore becomes the most economically valuable, and
this relative value is expressed in terms of price.
III-D-5
-------
/\
Land and property values and the institutionalized mechanism of
open-market economic exchange then are the key "regulatory" mechanisms
in this sub-orientation. Natural resources are seen as a commodity.
Although "pure" economic competition is rarely seen (other orientations
that are non-economic interfere), it is nonetheless the basic dynamic
underlying this sub-orientation and is expressed by participants'
ability to pay, their desire for a specific location which determines
its' market price and therefore, the use to which the environmental
location and/or feature will be put. Land-use maps are the operationali-
zation of this orientation (see Appendix A).
This orientation, of course, is characteristic of the utility
companies and their supporting and related industries. It is also
characteristic of highly industrialized communities. We, being
responsible for the human and community impact analysis have accordingly
not paid a great deal of attention to what the orientation of utility
companies is save to note its character and to present three related
generalizations and hypotheses that fall under the technological
feasibility sub-orientation;
1. Power plants will be sited where there is adequate access to
water, transportation and the raw product needed to produce
electricity. Nuclear power plants also must be sited in areas
that are not densely populated and which are not near earth-
quake zones. (1)
2. As techniques for dealing with high sulfur coal, coal gasifi-
cation and liquefaction become useable, we will see plants
sited with access to coal being a primary determinant of
location. Mining activity will usually be associated with
the development of these plants. (2)
3. Where exploitative potentialities exist, power companies in
conjunction with governmental energy organizations will be
present with development plans. (3)
The economic sub-orientation yields a great many more hypotheses
and generalizations and is more germane to our interests here. Three
basic generalizations are presented here and a number of related hypo-
theses.
4. Land values will fluctuate due to power plant development. (4)
5. A proposed site 'for a power plant which meets all technical
siting qualifications will be purchased providing existing
land use is not more valuable (in dollar terms) than what the
conversion of the property to power plant useage would be. (5)
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6. Q Plants will tend to be sited where the relative costs of pro-
ducing electricity are the lowest and profit margins highest.
As new technologies become available, they will be brought on
line when profitmaking becomes possible (the technology becomes
competitive with existing technologies). (6)
With regard to land use changes due to power-plant siting, we
offer the following hypotheses:
7. Land use due to power plant development tends to move from
less intensive to more intensive use. (7).
8. Open idle land experiences most dynamic development although
land also tends to move from cropland, pasture and rangeland
to some other use due to urban and industrialization pressures.
(8)
9. Land prices vary directly with the size of the influx of
outsiders coming to work in or on the plant. (9)
10. If a housing shortage exists in the host community, some land
will be devoted to temporary housing communities. (10)
11. The value of land will be in part a function of the concentra-
tion of population growth and the proportion of the host
county's population living in places of 2,500 or more is
increased by industrial development, with some growth also in
hamlets and the open country. Moreover, the population growth
effect of a new plant is concentrated in villages and towns
near the plant site. (11)
The market exchange aspect of the economic sub-orientation suggests
the following hypothetical trade-off possibilities as a result of power
plant development.
12. Communities too small to support most of the construction
phase population will benefit only a little from development.
(12)
13. Increase in the fiscal resource base of the local community
often is outweighed by increased costs of providing services
to the new industry and the community. (13)
14. A community can accommodate some influx of new population
without "significant" disruption given a certain level of
social, political and economic development as indicated by
size, level of services, location, etc. (14)
15. Demand for land is related to the size of the project. (15)
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The economic benefits (and costs) aspect due to power plant siting
is, of course, complex and dependent on many variables, such as loca-
tion of the site, prevailing land use, size and distance of host
community and characteristics of the indigenous labor force as well as
characteristics of whatever immigrants the project might bring. Also
important here is whether a community experiences boom-town effects
due to plant siting and what community attitudes toward development
are.
16. Only activities which provide a continuing basis for regional
exports generate compensating local benefits. (16)
17. Net fiscal gains to the local government do occur. This
usually is when no local subsidy was offered the industry,
or the plant work force is hired locally, or large proportions
of the plant work force live outside the community and commute
to work. (17)
18. If substantial numbers of construction workers relocate to
the site, substantial economic effects through payroll
infusions to local economy are created. (18)
19. Development tends to help local businessmen. (19)
20. Development is associated with higher labor costs for local
business. (20)
21. Development is associated with increased employment oppor-
tunities. (21)
22. If development pulls men from old jobs to new ones, there
will be increased employment opportunities for women. (22)
23. Impact of power plant siting is inversely related to the local
unemployment rate. (23)
24. Acceptance of development and associated changes vary directly
with perceived profitability to the individual. (24)
25. Local acceptance varies directly with actual or anticipated
economic benefits. Lack of actual or perceived economic
benefits means lowered acceptance or increased opposition.
(25)
26. Anticipated benefits to the local community generally exceed
perceived benefits after development. Even so, the percent-
age of local citizens perceiving benefits outweighs those
expressing negative opinions. Those not perceiving personal
benefits are heavily concentrated among the old, the ethnic and
racial minorities, the unemployed and farmers. (26)
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27. During the operating phase, if utility property tax payments
from thie nuclear plant siting go directly to the local
municipality, then the major impact of the operating power
plant is the augmented tax base. (27)
28. When utility property tax payments go directly to the local
municipality, then new economic-fiscal options include the
choice between recovering money benefits in the private sector
through lowered tax rates, recovering money benefits through
the public sector with increased services, or some combina-
tion of these two. (28)
With regard to impacts on the labor force, the following generali-
zations and hypotheses are offered:
29. Preferences for male versus female employees are related to
the type of industry, with males predominating the heavy
manufacturing industries and females being favored in the
light industries such as apparel, textile, and appliance
assembly plants. The latter are low-skilled, low-wage indus-
tries. (29)
30. There is considerable evidence that nonwhites are under-
represented in the work forces of nonmetropolitan industrial
plants. Where they are hired they are concentrated in un-
skilled and semi-skilled jobs. This situation may indicate
outrignt discriminatory hiring practices, or insufficient
skill level among local nonwhites, or both. (30)
31. New jobs often do not go to the local unemployed, underemployed,
minorities, and marginally employable persons likely to be
near or below the poverty level. (31)
32. High-skill, high-wage industries, such as an operating power
plant, which are most likely to increase the aggregate income
and raise the percentage of families above the poverty level,
are least likely to hire local disadvantaged. The apparent
gains in aggregate income and unemployment rate often hide
the failure to aid the local disadvantaged. (32)
33. Low-skill, low-wage industries are more likely to employ the
disadvantaged. (33)
34. The labor sheds of nonmetropolitan industrial.plants are often
larger than those in metropolitan areas, their size depending
on many factors including size of towns near the plant, local
highway system, wage differentials between the plant and other
local employers and personal attributes of the workers. (34)
III-D- 9
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35. Employers prefer younger workers although in some instances,
skill gained through experience may be competitive with youth.
(35)
36. The female labor market is generally unaffected by coal
development. (36)
Potential boomtown conditions and impacts include the following:
37. The lower the overall population density of the area, the
greater the disruptions due to power plant development. (37)
38. The rate of inflation varies inversely with the degree of
present economic diversification. (38)
39. If the size of the host community is held constant, social
and economic disruption will be directly related to the size
and suddenness of development. (39)
40. The higher the skill requirements of the incoming power plant
the greater the disruption to the community. (40)
41. Impact is directly proportionate to the number of new persons
entering the area and will vary with unemployment rate outside
region and general notoriety of project outside region. (41)
42. Those most negatively impacted are the lower class, less
educated people with a stable history, also those on fixed
incomes or salaries. (42)
43. Where new industry is accompanied by population growth it
often strains existing basic service delivery systems. (43)
44. Communities that experience a boom during the construction
phase will usually have insufficient revenues to finance
needed expansion. (44)
45. There is usually a lag between the demand for services and
the ability to provide them and is directly related to downturn
in quality of life for affected residents, old and new alike.
(45)
46. The rapidity of population buildup is inversely related to the
communities' ability to provide services and amenities. (46)
47. Where workers can commute during the construction phase,
impact is rather minimal except for construction worker
traffic. (47) °
"\
48. A commuting labor force generates minimal fiscal, social or
political impacts on the host community. (48) =
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49. If a nuclear plant is sited in or near a metropolitan area,
the likelihood of access to an adequate labor force increase
and boomtown effects are unlikely to occur. (49)
50. Public investment is most likely to occur after the peak of
the boom has been reached when a clear tax and revenue base
has been established. (50)
51. The larger the influx of outside workers the smaller the
receiving community, the greater the social disruptions,
provided its population is larger than 1,000-2,500. (51)
52. Boom affects housing, related services, health and educationa'
institutions as well as mental health services. (52)
53. The larger the host community, the easier the adjustment to
development. (53)
54. The more industrialized the community, the lesser the social
impact of development. (54)
55. There is an incentive to use labor late in the construction
process and to shorten the overall construction process as
much as possible, intensifying boomtown effects. (55)
56. The rate of population growth clearly is a function of the
size of the industrial firm. (56)
57. In a clear majority of plant locations, the host community
experiences population growth. (57)
58. Wages paid in boomtowns do not fully compensate for dis-
amenities. (58)
The hypotheses and generalizations presented here regarding the
instrumental and other orientations are not anywhere near exhaustive,
however, they do provide us with a literature and theory-grounded
framework to classify and predict likely impacts of power plant con-
struction in the ORBES region.
2.2 THE TERRITORIAL ORIENTATION
Control of space is the focus of this orientation and the struggle
for control the basic ecological process. The two modes or sub-
orientations of territorial control are strategic (physical dominance)
and political (decision-making by legitimate authority). The former
applies primarily to "unsettled" conditions where the latter refers to
stabler conditions such as that provided by institutionalized govern-
ment.
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The strategic sub-orientation relates to the environment in terms
of whether physical control over territory is facilitated or obstructed.
The relative "vulnerability" or "suitability for offensive or defensive
purposes" of the territory is important here. This value attached to
the environment is not objectively given and rests on the strategic
doctrine held by an individual, group, or society. This doctrine, then,
is the regulatory mechanism in this sub-orientation and defines the
evaluation and organization of space. Strategic doctrines range from
animals' defense of their living space to geopolitics. While this
orientation falls most obviously in the military domain, this basic
mechanism of territorial control by strategic location can be found at
most levels of human behavior. Siting criteria and maps of present
and possible sites of energy facilities are substituted here because
this too is a form of territorial control.
The political sub-orientation is the organization of space by the
establishment of recognized territorial boundaries over which some
authority enjoys rightful control. This authority is hierarchical,
ranging from that of an individual over his space to state sovereign!ty
over national territory. Each level in the hierarchy of control
enjoys some rights as to how the territory is used, but all are subject
to regulations by some higher authority. Political organization of
space then is usually not isomorphous with private property in the
micro-political sphere, but rather finds its definition from its place
in the hierarchy of control.
Political organization of space may range from the fluid defini-
tions of nomadic tribes to the precisely sub-divided system of the
modern nation-state. Modern governmental machinery and its formal
proceedings represent the most autonomous aspect of the political
decision-making process and is theoretically equivalent to the market
mechanism in the economic sphere. However, the end result of the
process is not a structure of property rights and values but a hierarchy
of territorial rights and boundaries.
Boundaries set in the political sphere correspond to price in
the economic sphere and are the end-product of a bargaining process
that represents the agreed-upon division of a territory between
competing groups or interests. Some go so far as to argue that the
basic ecological pattern of the contemporary city is determined.by
the power conflicts between interest groups and no longer by the
economic process of market allocation.
Political organization of space goes beyond mere limit-seeking;
it excludes unauthorized personnel from areas and authorizes, encourages
and often determines to what use a given territory will be put, i.e.
through zoning, master plans and the like. The political orientation
is also, at least implicitly, collective in orientation and is'related
to the broader goals of the collectivity. In principle, space is
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organized with a view of these goals. Zoning maps and Regional ^
Planning Commission Master Plans are the product here. Data to map
this orientation were not available in a comparable form for the ORBES
region and hence are not presented. However,
-------
The political sub-orientation refers basically to decision-making
processes within the community with regard to power plant siting.
Considerations hypothesized or generalized about here include political
structure of the community, including which groups are likely to have
some real influence on decisions, and the community's structural
amenability to development.
68. Community growth is a function of many interrelated variables
of which a nuclear plant is only one. If certain planning
and zoning conditions exist, then a nuclear power generating
station can act as a powerful catalyst to community growth
and development. If planning and zoning do not exist, they
are unlikely to be implemented until after the community has
experienced substantial impact from the new development
because:
a) anti-zoning attitudes prevail in many parts of rural
America.
b) planning and implementing bodies for land use control
are often separate and on different local levels, e.g.
community, county, township, area.
c) local officials are often loath to cooperate at a
higher Jevel unless need is clear or pressure is exerted.
(65, 66)
69. Vertical community structures (e.g. branches of national
industries) where power is based outside the community with
community representatives who wield economic sanctions but
who are not broadly integrated into civic, educational or
government subspheres are more amenable to outside manipu-
lation. (67)
70. Horizontal community structures where local autonomous
leaders are influential in economic, civic, educational and
government decision-making time, are less amenable to outside
manipulation. (68)
71. The more rational and bureaucratized the host community, the
greater the ease in coping with the development impacts.
72. The more rational and bureaucratized the local government,
and the better equipped it is to provide needed services for
power plant development, the more receptive to development.
73. Developing communities tend to lose economic and governmental
self-sufficiency. (69)
74. Rapid development and urbanization is related to loss of
local autonomy, increased norm-conflict and specilaization
and differentiations of interest and associations (fragmen-
tation). (70)
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75. If an increasing construction population demands major
increased public services, then major political impacts upon
local governments will occur. (71)
76. If a community lacks revenue, staff, planning capability,
experience or the administrative infrastructure needed for
dealing with sudden growth, then these inadequacies will
exacerbate the need to deal with immediate problems and
intensify social and political impacts. (72)
77. The more personal the governmental relationship is in a
developing community, the more difficulty in coping with
structural and political changes due to development.
78. Projects legitimized by local influentials tend to be
accepted. (73)
79. Catalysts for change are often relative newcomers (few
year's residence) rather than oldtimer locals. (74)
80. Communities which are fragmented and subject to outside
control will have either low opposition to development or
lack the ability to oppose.
81. There is some evidence that choices of types of organizations
in which to be involved differ between newcomers and long-
* term residents. The in-migrants show a propensity to favor
business, professional, and labor organizations which appears
to reflect their educational and occupational characteristics.
(75)
82. The less structured land use controls, the more likely the
siting of a power plant.
83. If an operating nuclear reactor pays property taxes directly
to the local municipality, then the available economic and
fiscal options present public officials with a variety of
growth-no-growth options. If augmentation of the local
tax base occurs, then siting of a nuclear generating station
alters the relationships of the host community with neigh-
boring towns, the region, and the state.
a. Neighboring towns may become resentful or antagonistic
over the favored status and resources of the host
community.
b. Efforts will be initiated or intensified on the state
• level to redistribute the utility tax payments so
that more revenues go to the state or region involved.
(76)
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84. If a host community develops and enforces strict zoning and
land use regulations prior to the siting of a nuclear reactor
from which it will derive massive economic benefits, 1) the
chances for major changes in the social and political compo-
sition of that community will decrease, and 2) the community
will have a mechanism for controlling the rate and direction
of population increase. (77)
85. Unless a nearby operating nuclear plant has an accident,
spill, or release, or a concerned citizens group brings
attention to possible hazards, residents are generally
unaware or unconcerned about the power plant. (78)
86. Communities without a history of zoning tend to be reluctant
to invoke it when development occurs. (79)
87. The more centralized the local government is, the more likely
a plant can come into the community providing the leaders are
in favor of it.
88. Pro-development activity tends to be clustered in the business
segment of the population and with local government officials,
as well as utility company people. (80)
89. Anti-development activity tends to come from oldtimer women,
those with a high attachment to place and a vested interest
in keeping things as they are, older segments of the popu-
lation, and isolated rural type of person. (81)
90. If an operating nuclear reactor pays property taxes directly
to the local municipality, then new options offered by the
augmented tax base include needs and opportunities to 1)
professionalize and develop administrative infrastructures,
and 2) develop and/or alter political and decision-making
structures. (82)
91. Participation rates of industrial workers in voluntary
organizations (churches, civic clubs, recreational) are
similar to other community residents. (83)
92. Newcomers who expect to stay a while tend to try to get
involved in community affairs and politics. (84)
93. If the level of knowledge about impending development is low,
people tend to let utility companies make all the major
decisions. (85)
94. One possible effect of decision-making is that: Attempts
to broaden the tax base often mean, after the construction
boom, taxes remain high and the environment is degraded. (86)
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2.3 THE SENTIMENTAL ORIENTATION
This orientation refers to the environment in terms of attachment.
Cohen argues that this sentimental attachment to space first elaborated
by Firey (87) is part of a general tendency found in traditional
societies to pervasively and systematically organize the whole environment
in sentimental terms. The two sub-orientations are the mode of
primordial belonging and the mode of prestige associated with a
territory. The former sub-orientation is rooted in birth or tradition,
the latter representative of social sentiments as to the relative
worth of a space derived from the worthiness of those associated with
it.
The primordial sub-orientation, the less institutionalized of the
two, is expressed by a subjective "sense of belonging," that is,
environmental features are given intrinsic significance by an indi-
vidual or group apart from instrumental or symbolic value. The process
is "identification" by which an individual organizes his whole
environment in terms of the "extent of belongingness" and each point
or space in the environment possesses a certain "belongingness value."
The institutional aspect of the primordial sub-orientation is not
so clear as for other sub-orientations, but "solidary institutions" are
the referent. This is the "nexus of values and norms regulating
relationships of solidarity and attachment between people like kinship,
friendship, neighboring, etc." This sense of belongingness performs
an integrative function by providing emotional anchorage for individuals
and groups. One means of mapping this sub-orientation without recourse"
to primary data-gathering is to map stability of the population and
its basic demographic characteristics so as to get a feel for the
kind of people who reside in an area. These maps are in Appendix A
and classified under "Sentiment".
The prestige sub-orientation is the relationship to the environment
in terms of the social evaluation accorded to its features and is
derived from the worthiness of the people associated with given
environments. The prestige of an area is a product of the gradual
emergence and crystallization of consensus as to the relative worth
of a place or area. The process here is social evaluation and is
analogous to the process by which land and property values are
determined or territorial rights delineated.
In a sense, if people live where they "belong" then the prestige
of an area will reflect the social status of its inhabitants. In other
words, the primordial sub-orientation is ideal-typically "objectified"
into the prestige of an area. The status value or prestige of areas
then, is another mode of organizing the environment. This is the spatial
component of social stratification. A mappable referent here is value
of land and housing. These maps are in the "Sentiment" section in *
Appendix A.
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Though we have been plagued with difficulties concerning a lack
of direct information about this orientation, it is also the one most
of interest for it most directly concerns the lives of residents in
the ORBES region. Also, our literature search has yielded a rich
collection of hypotheses and generalizations concerning both the
primordial and the prestige suborientations.
Hypotheses concerning the primordial suborientation follow:
96. The more people who reside in an area slated for power plant
development who consider it "home" (never lived anyplace
else), the less likely they will be receptive to development.
(88)
97. Residents with deep and enduring ties to land and lifestyle
will generally be opposed to development if it threatens their
lifestyles. (89)
98. The greater the attachment to place and lifestyle on the part
of residents, the greater the experience of discomfort from
development. (90)
99. The more isolated the community from urban centers, the greater
the impact of development.
100. The greater the difference between the oldtime residents and
newcomers in terms of lifestyle and value the greater the
impact of development.
101. Communities which have experienced previous rapid development
tend to be less favorable and more cautious about further
rapid development. (91)
102. A developing community is moving from homogeneity to hetero-
genity. (92)
103. The more people who identify with an area slated for power
plant development (whether newcomers who chose to reside
there or oldtime residents), the less likely they will be
receptive to development.
104. If the oldtimer's social network is one based on kin, length
of relationships, neighbor-based and cuts across generational
lines,the newcomers will have a hard time being taken in. (93)
105. People in the later stages of the life cycle are generally
less adaptable to forced change than are younger members.
(94)
106. Assumptions and values of oldtimers tend to be'questioned by
newcomers. (95)
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107. The more transitory the labor force, the less it will be
absorbed into the community. (96)
108. The more transitory the labor force, the greater the social
instability of families. (97)
109. Newcomers have little sense of community. (98) ^
110. Newcomers are more favorably disposed toward development than
old timers. (99)
111. Residents of temporary housing communities tend to be
socially isolated, demoralized, and subject to high rates
of mental illness, alcoholism, and marital instability as
well as child neglect and abuse.
a. The crime rate increases with development.
b. The divorce rate increases with development.
(100, 101, 102)
112. People in temporary communities are lacking in recreational
and social outlets as well as places to put constructive use
of leisure. (103)
113. The depth of ties to an area slated for power plant develop-
ment is related to receptiveness to development.
114. The impact of a power plant is inversely proportionate to the
percentage of the population aged 18-35, and directly propor-
tionate over 55. (104)
115. The higher the number of jobs going to persons already
living within the area, the lower the disruptions to the
community. (105)
116. Nonmetropolitan industrial workers have larger households
than the local area residents generally. This appears to
be a function of their age relative to the local population;
more are in the child rearing stages of the family cycle.
(106)
117. The majority (2/3 to 3/4) of immigrants move no farther
than 50 miles. Those who move farther are probably managers
and technical personnel. (107)
118. The initial source of population growth is likely to be
increased in-migration coupled with unchanged or decreased
outmigration. (108)
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119. Nonmetropolitan industrial workers, as a group, are residen-
tially more mobile than rural dwellers generally. Nonmetro-
politan workers often commute long distances for a period of
time after employment, but in the long run they move closer
to their place of work, or change jobs. (109)
120. Women and children of boom-town, temporary employees suffer
disproportionately. (110)
121. The children of the geographically mobile tend not to do as
well in school (all phases) as those from a more stable
population. (Ill)
122. Oldtimers will experience a loss of autonomy during develop-
ment. (112)
123. The degree of fami!ism is related to mental health. (113)
124. Individuals will exhibit more positive attitudes about
accepting technological change than sociological change.
(114)
125. If social changes are desired by an affected group, then
the changes can be assimilated with little social disrup-
tion. (115)
126. Group members attitudes toward the changing community and
the project should reflect the impact of change upon the
group. (116)
127. People to be relocated tend to view project negatively and
have negative consequences in readjustment. However, people
who are to be relocated will have more positive attitudes
toward the development if the negotiators for their land
have exhibited tact, consideration for their problems in
relocating and a willingness to compensate them for enduring
a disproportionate share of the impact. (117)
The prestige suborientation yields the following hypotheses:
128. If an area is seen by residents as lacking in prestige or
usefulness, the more likely development will be allowed to
occur without protest. The more valuable the area slated for
development, the less likely development will occur.
129. Power plant development changes social stratificational
patterns. (118)
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130. Power plants tend to be sited in areas where existing land
useage provides marginal returns.
131. Power plants tend to be sited where poorer people live.
132. Residents of temporary housing communities tend to be seen
as a social class apart and generally are negatively valued
by old-time residents. (119)
133. People on fixed incomes (retired, working poor) suffer
disproportionately from development-induced inflation. (120)
Power plant development also causes change in populations and
labor force composition that indirectly affect the prestige sub-orienta-
tion:
134. If a large, temporary population increase occurs during
construction, then major changes in social composition and
organization of the host community will occur. (121)
135. Power plant development brings changes in the age and sex
structure of the community, usually dropping median age,
increasing the proportion of single men and increasing the
number of pre-school and school age children. (122, 123)
\
136. The higher the wages in the developing industry, the more
likely there is to be a labor shortage in other areas of
the economy. (124)
137. Most male workers expect to seek other industrial work if
laid off. Few would consider returning to farm work. Moving
to another community to secure employment is an undesirable,
but viable alternative. (125)
138. There is virtually no evidence that industrial development
increases the level of educational attainment in the host
community. Where it does occur the evidence suggests it is
due to changes in the age structure, younger adults generally
having completed more years of schooling. (126)
139. Developing communities show an increased division of
labor. (127)
140. The proportion of newcomers who bring their families depends
on wages, length of job and perceived amenities of the
community as well as distance from "home." (128)
141. Newcomers tend to be better educated, younger and more
highly skilled than old-timers. (129)
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142. Old time residents generally bear more of the social and
economic costs of development than do transient workers.
143. Communities with high unemployment rates tend to welcome
development. (130)
144. Newcomers tend to have higher expectations about community
services and amenities than do oldtimers. (131)
145. Newcomers tend to try to p.lace themselves in the social
stratification system by the church they choose to attend.
(132)
146. In-migrants express more dissatisfaction with the local
community services than long-term residents, particularly
when the in-migrants are of higher skill and income levels
than the host community residents. (133)
147. Development tends to make everyday life more unpleasant
for consumers of services and retail stores, etc. (134)
148. Rapid growth frequently increases faster than benefits
gained from new services made available. (135)
149. If a proposed power plant is seen by residents as enhancing
the relative value and prestige of an area, it will be
promoted.
150. The number and kind of newcomers to a developing area has
a direct relationship to the magnitude and kind of impact
to be expected. (136)
151. Development tends to increase urbanization. (137)
152. The greater the influx of newcomers, the more likely the
emergence of a highly stratified class system and personal
awareness of same. (138)
2.4. THE SYMBOLIC ORIENTATION
To the extent that the environment "means" something to an indi-
vidual, group or society, it can be said to have symbolic significance,
i.e., the environment expresses or represents human values. Meaning
is extrinsically imposed upon the environment by culture and may be
totally independent of its objective features. Cohen's two sub-orienta-
tions here are moral-religious and aesthetic.
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The aesthetic sub-orientation is the less institutionalized and
organizes the environment in terms of the aesthetic enjoyment that can
be derived from it. Aesthetic judgement is, of course, subjective and
subject to much variation. The regulative mechanism in the sub-orienta-
tion is "taste formation" and to the extent aesthetics are formalized,
it may be seen as represented by artistic institutions. Parks and
national forests, historic places, public gardens, etc. are the mappable
referent here.
The moral-religious sub-orientation is the organization and
evaluation of the environment in terms of its "nearness of the sacred"
or the degree to which an environmental feature symbolizes the sacred.
Socio-religious space is heterogeneous and varies in its relative
sacredness. The process here is "sanctification." The degree of
"religiousity" in a society will determine the extent to which space
is organized according to its sacredness. The institutions here are
religious-moral ones which represent the process of sanctification and
give it a spatial referent. Cemetaries, churches, and church property
such as schools, camp grounds, and the like can be mapped along with
the aesthetic dimension. We have, however, substituted a map of
predominant religion orientation because the other mappable referents
are not readily available.
A few hypotheses are offered about the aesthetic and moral-
religious sub-orientations. The effect of these orientations are
basically self-explanatory with regard to power plant siting for it is
unlikely that areas with these meanings attached would be chosen as
a plant site.
153. Power plants will generally not be sited in areas primarily
valued and used for aesthetic purposes.
154. Areas which have been formally designated as aesthetic areas
will not be potential sites for power plant development.
155. The middle class is more environmentally concerned. (139)
156. Middle and upper classes will tend to take advantage of
cultural amenities. (140)
157. Newcomers (those without established social networks) make
greater demands on recreational facilities than those with
well established social networks. (141)
158. An area that has been given moral-religious meaning will not
be viewed as a potential power plant site.
159. Regard.less of religious source, an area which is seen as
sanctified will not be developed.
III-D- 23
-------
160. Areas which have been given meaning, either religious,
historic, recreational, or other, will not be seen as
appropriate for development.
161. Public parks and recreation places serve as places for (142)
informal social groups and family and friends to recreate.
162. Those with high incomes, occupational prestige and higher
educational attainment participate in recreation most,
usually within 2 miles of home. This is correlated with
time available, stage of life cycle and preferences are for
swimming, sightseeing, picknicking. (143)
163. Rural people recreate less than urban people. (144)
164. The poor recreate less due to money and transportation
constraints. (145)
Though environmental orientations can be analytically separated
and examined in terms of what each orientation's likely impact on a
given environment would be, actual utilization of the environment is
usually a mix of different orientations. Moreover, the four orientations
and their eventual ecological consequences on the environment are
generally in conflict as shown in Table III-D-2. Cohen argues that
any environmental use is a result of ecological institutionalization
where limits are set on the spheres of influence each orientation would
have. This is a trade-off process and the outcome seems to be predict-
able in a given case from 1) knowledge of the environmental impact of
each orientation, 2) the "mix" of orientations present and 3) the
"overall value system" of the impacted area. The latter will determine
in part the priorities of different orientations and therefore eventual
use of the environment.
Of all the possible conflicts between environmental orientations,
the most severe are probably the instrumental orientation which views
the environment basically as a commodity and the sentimental and
symbolic orientations which imbue the environment with human meaning.
Particularly acute conflict may emerge between the economic benefit
and the primordial belonging, moral-religious, and aesthetic sub-
orientations. The territorial orientation may be seen, in this light,
as a mediating orientation between the instrumental and sentimental
and symbolic orientations, for this crucial orientation basically
determines, in interaction with the others, what the final outcome
is with regard to use of the environment.
III-D-24
-------
Table III-D-2
FRAMEWORK FOR A TYPOLOGY OF CONFLICTS BETWEEN ENVIRONMENTAL SUB-ORIENTATIONS
Techno-
logical
Technical X
Economic
Strategic
Political
Primordial
Belonging
Prestige
Aesthetic
Moral -
Religious
Pri-
mordial
Eco- Stra- Poli- Belong-
nomic tegic tical ing
T/E T/S T/P T/PB
X E/S E/P E/PB
X S/P S/PB
X P/PB
X
Pres- Aesthe-
tige tic
T/SP T/A
E/SP E/A
S/SP S/A
P/SP P/A
PB/SP PB/A
X SP/A
X
Moral -
Religious
T/MR
E/MR
S/MR
P/MR
PB/MR
SP/MR
A/MR
X
SOURCE: Cohen, Erik. "Environmental Orientations: A Multidimensional
Approach to Social Ecology." Current Anthropology, Vol. 17,
No, 1, 1976, p. 58.
. III-D-25
-------
REFERENCES
1. Ohio River Basin Energy Study. Task I Report, Subtask IE.
2. R. G. Edwards, A. B. Broderson and W. P. Houser, (AME Techno-
logy, Inc). Social, Economic and Environmental Impacts of
Coal Gasification and Liquefaction Plants. Lexington, Kentucky:
Institute for Mining and Mineral Research, Report No. Immr
14-GR2-76 (1976).
3. ORBES. Task I Report.
" npj
"be
4. Gerald Breese et. al., The Impact of Large Installations on
Nearby Areas: Accelerated Urban Growth. Beverly Hills:Sage
Publications, Inc., 1965.
5. Edwards et.al. Impacts of Coal Gasification and Liquefaction
Plants.
6. Ibid.
7. Sue Johnson. "Measuring the Social Costs of Energy Production
in Coal and Hydroelectric Production Regions." Panel presenta-
tion for the Annual Meetings of the American Sociological Asso-
ciation Session on Conservation and Environmental Problems, New
York, August, 1976.
8. Kathryn A. Zeimetz, Elizabeth Dillon, Ernest E. Hardy and
Robert C. Otte. Dynamics of Land Use in Fast Growth Areas.
U. S. Department of Agriculture, Economic Research Service,
Agriculture Economics Report No. 325 (1976).
9. Raymond L. Gold. "Social Impacts of Strip Mining and Other
Industrializations of Coal Resources." C. P. Wolf; ed., Social
Impact Assessment, EDRA 5 Conference Proceedings, 1974.
10. U. S. Department of Housing and Urban Development. Rapid Growth
From Energy Projects: Ideas for State and Local Action, A Pro-
gram Guide.Office of Community Planning and Development,
HUD-CPD-140 (1976).
11. Gene F. Summers, Sharon D. Evans, Frank Clemente, E. M. Beck
and Jon Minkoff. Industrial Invasion of Nonmetropolitan
America: A Quarter Century of Experience.New York:Praeger,
1976.
III-D-26
-------
12. Stan L. Albrecht. "Sociological Aspects of Power Plant Siting.
Paper presented at a conference on Developing Utah's Energy
Resources, Salt Lake City, Utah, May 25, 1972.
13. Gene F. Summers et.al. Industrial Invasion of Nonmetropolitan
America; A Quarter Century of Experience. New York: Praeger.
__
14. Elizabeth Peelle. "Socioeconomic Effects of Operating Reactors
on Two Host Communities: A Case Study of Pilgrim and Millstone.
Paper presented at conference on Land Use and Nuclear Facility
Siting: Current Issues, Denver Colorado, July, 1976.
15. Gold. "Social Impacts."
16. Berry Ives, William Schulze and David Brookshire. "Boomtown
Impacts of Energy Development in the Lake Powell Region."
Draft Lake Powell Research Project Bulletin, March, 1976.
17. Summers. Industrial Invasion.
18. Peele. "Socioeconomic Effects."
19. Institute for Social Science Research. A Comparative Case
Study of the Impact of Coal Development on the Way of Life' of
People in the Coal Areas of Eastern Montana and Northeastern
Wyoming.Final Report, Missbifla, University of Montana, June,
1974, 2nd Ed.
20. Ibid.
21. Ibid.
22. Ibid.
23. William R. Freundenburg. "The Social Impact of Energy Boom
Development in Rural Communities: A Review of Literatures and
Some Predictions." Paper presented at the Annual Meetings of
the American Sociological Association, New York, August, 1976.
24. Sue Johnson and Rabel J. Burdge. "An Analysis of Community and
Individual Reactions to Forced Migration Due to Reservoir Con-
struction." In D.R. Field, J. C. Barren and B.L. Long, eds.
Water and Community Development, Ann Arbor: Ann Arbor Science
Publications, Inc.,1974.
III-D- .27
-------
25. Peelle. "Socioeconomic Effects."
26. Summers. Industrial Invasion.
27. Peelle. "Socioeconomic Effects."
28. Ibid.
29. Summers. Industrial Invasion.
30. Ibid.
31. Ibid.
32. Ibid.
33. Ibid.
34. Ibid.
35. Ibid.
36. Institute for Social Science Research. A COmparative Case Study.
37. Freundenburg. "Social Impact."
38. Sue Johnson and Alan Randall. "Research Needs on Social, Poli-
tical and Institutional Aspects of Coal Utilization." Proceed-
ings of the Workshop on Research Needs Related to Water for
Energy. Research Report No. 93. Urbana-Champaign: University
of Illinois Water Resources Center, 1974.
39. Freundenburg. "Social Impact."
40. Ibid.
41. Ibid.
42. Ibid.
43. Summers. Industrial Invasion.
44. Northern Great Plains Resource Program. "Socio-Economic and
Cultural Aspects." Work Group Report. Denver: MGPRP, 1974.
45. Ibid.
III-D-28
-------
46. Ibid.
47. Peelle. "Socioeconomic Effects."
48. Ibid.
49. Ibid.
50. Ives. "Boomtown Impacts."
51. Freundenburg. "Social Impact."
52. N. Great Plains Resource Program. Work Group Report.
53. Institute for Social Science Research. A Comparative Case Study.
54. Johnson and Randall. "Research Needs."
55. Ives. "Boomtown Impacts."
56. Summers. Industrial Invasion.
57. Ibid.
58. Ives. "Boomtown Impacts."
59. Summers. Industrial Invasion.
60. Richard C. Schuller et.al. Citizen's Views about the Proposed
Hartsvilie Nuclear Power Plant; A Preliminary Report of Poten-
tial Social Impacts.ORNL-RUS-3 (1975).
61. Ibid.
62. Ibid.
63. Ibid.
64. Ives. "Boomtown Impacts."
65. Peelle. "Socioeconomic Effects."
66. N. G. P. Krausz. "Local Government Action for Rural Develop-
ment." Illinois Research. Vol. 16, No. 4 (1974):6-7.
67. C. William Given and John B. Mitchell. "Community Power Struc-
ture: A Methodological Analysis and Comparison." Ohio Agri-
cultural Research and Development Center, Research Bui. 1046
(1971).
III-D-29
-------
68. Given and Mitchell. "Community Power Structure."
69. Audie L. Blevins,; James G. Thompson and Carl Ellis. Social
Impact Analysis of Campbell County Wyoming. Wyoming Environ-
mental Institute, December, 1974.
70. Ibid.
71. Peelle. "Socioeconomic Effects."
72. Ibid.
73. J. B. Mitchell and E. D. LaFontaine. "A Study of Leadership in
Small Communities." Ohio Report. Ohio Agricultural Research
and Development Center, Vol. 58, No. 5 (1973):108-110.
74. Institute for Social Science Research. A Comparative Case Study.
75. Summers. Industrial Invasion.
76. Peelle. "Socioeconomic Effects."
77. Ibid.
78. Ibid.
79. Institute for Social Science Research. A Comparative Case Study.
80. Schuller et.al. Citizen's Views.
81. Ibid.
82. Peelle. "Socioeconomic Effects."
83. Summers. Industrial Invasion.
84. Lee Nell is. "What Does Energy Development Mean for Wyoming?"
Human Organization, Vol. 33, No. 3 (Fall, 1974):229-238. and
Institute for Social Science Research. A Comparative Case Study.
85. Summers. Industrial Invasion. ^
86. Albrecht. "Sociological Aspects."
87. W. Firey. "Sentiments and Symbolism as Ecological Variables."
American Sociological Review. 10 (1945):140-48.
»
88. Johnson and Burdge. "Reactions to Forced Migration."
III-D-30
-------
89. Ibid
90. Ibid.
91. W. Cris Lewis and Stan L. Albrecht. "Attitudes toward Accele-
rated Urban Development in Low-Population Areas." Growth and
Change. Vol. 8, No. 1.(1977):22-28.
92. Blevins. "Campbell County, Wyoming."
93. Institute for Social Science Research. A Comparative Case Study.
94. Burdge and Johnson. "Reactions to Forced Migration."
95. Institute for Social Science Research. A Comparative Case Study.
96. Gold. "Social Impacts."
97. Ibid.
98. Institute for Social Science Research. A Comparative Case Study.
99. Nell is. "Energy Development for Wyoming." and Institute for
Social Science Research. A Comparative Case Study.
100. Ives. "Boomtown Impacts", and Nell is. "Energy Development for
Wyoming." and HUD-CPD. Rapid Growth.
101. Institute for Social Science Research. A Comparative Case Study.
102. Ibid.
103. Ibid.
104. Freundenburg*. "Social Impact."
105. Ibid.
106. Summers. Industrial Invasion.
107. Ibid.
108. Ibid.
109
109. Ibid.
110. Ives. "Boomtown Impacts."
111. Institute for Social Science Research. A comparative Case Study.
III-D-31
-------
112. N. Great Plains Resource Program. Work Group Report.
113. Peter L. Heller. "Familism, Alienation and Mental Health with-
in a Rural Community." Virginia Purtle Steelman, ed. Rural
Sociology in the South. Proceedings of the Rural Sociology
Section, SAAS, Mobi1 e, Alabama, February, 1976.
0
114. Ted L. Napier and Cathy J. Wright. "Implications for Rural
Development Programs." Ohio Report, Ohio Agricultural Research
and Development Center, Vol. 57, No. 6 (1972):83-85.
115. "A Longitudinal Analysis of Rural People to Natural
Resource Development: A Case Study of the Impact of Water
Resource Development." Ohio Agricultural Research and Develop-
ment Center, Research Bui. 1083 (1976).
116. Ibid.
117. Ibid. ^An Evaluation of Forced Relocation of Popu-
lation of Population due to Rural Community Development."
Ohio Agricultural Research and Development Center, Research
Bui. 1073 (1974).
118. Gold. "Social Impacts."
119. Institute for Social Science Research. A Comparative Case Study.
120. Johnson. "Social Costs."
121. Peelle. "Socioeconomic Effects."
122. HUD-CPD. Rapid Growth.
123. John S. Gilmore and Mary K. Duff. "The Sweetwater County Boom:
A Challenge to Growth Management." University of Denver Research
Institute, July, 1974.
124. Institute for Social Science Research. A Comparative Case Study.
125. Summers. Industrial Invasion.
126. Ibid.
127. Blevins et al. Campbell County, Wyoming."
128. Ives et.al. "Boomtown Impacts."
129. Nell is. "Energy Development for Wyoming."
130. Freundenberg. "Social Impacts."
III-D- 32
-------
131. Nell is, "Energy Development for Wyoming."
132. Institute for Social Science Research, A Comparative Case Study.
133. Summers. Industrial Invasion.
134. Institute for Social Science Researcch, A CdmparatiVe Case Study.
135. Albrecht, "Sociological Aspects."
136. Freundenberg, "Social Impacts."
137. HUD-CPD, Rapid Growth. John S. Gilmore, "Boom Towns May Hin-
der Energy Resource Develppment." Science 191 (1976):535-540.
138. Gold, " Social Impacts."
139. Thomas K. Pinhey and Michael D. Grimes. "Outdoor Recreation and
Environmental Concern: A Replication and Extension." Virginia
Purtle Steel man, ed. Rural Society in the South, Proceedings of
the Rural Sociology Section, SAAS, Mobile, Alabama, Feb., 1976.
140. Gerald P. Owens. "Outdoor Recreation: Participation, Charac-
teristics of Users, Distances Traveled and Expenditures. Ohio
Agricultural Research and Development Center, Research Bui. 1033
(1970).
141. Neil H. Cheek, Jr., Donald R. Field and Rabel J. Burdge.
Leisure and Recreation Places. Ann Arbor: Ann Arbor Science
Publishers, Inc., 1976.
142. Ibid.
143. Owens, "Outdoor Recreation."
144. Cheek et.al., Leisure
145. Hugh C. Davis. "Technological Change and Recreation Planning."
B. L. Driver, ed., Elements of Outdoor Recreation Planning.
Ann Arbor: University of Michigan Press, 1970.
III-D-33
-------
3. METHODOLOGY
3.1. INTRODUCTION
In attempting to assess the impact of any future energy develop-
ment upon people and social institutions, two questions must be asked
about each proposed site. First, will a "boomtown" syndrome be pro-
duced and if so, how large and what particular characteristics will
be most .significant? Second, what is the prevailing environmental
orientation or mix of orientations in the county and how does this
affect receptiveness to power plant development?
It must be clearly understood, however, that until the develop-
ment actually occurs, it is impossible to know what the impacts will
be. We can only suggest a plausible course of events based on 1) an
understanding of the particular impact situation, 2) reports of the
consequences of similar developments, and 3) general knowledge of
human behavior. We recognize that there are gaps and inaccuracies in
our knowledge of all three of these factors.
In a study with the scope of the ORBES project, there is a man-
date to go beyond multiple impact assessments. The assessment is,!
first of all, relative: counties have been grouped where geographical
proximity exists and the prevailing trends of the ORBES region have
been taken into account. Second, in attempting to assess the impact
or interactional consequences of simultaneous energy developments in
groups of adjacent or nearby counties and in other parts of the region,
we hope to provide some insight for decision making at a higher policy
level and to delineate, in the summary section, what we think the
approximate magnitude of these interactive effects would be.
The rather voluminous literature we have cited here gives us very
little help in this kind of interactive assessment because most of the
studies are case studies and very little, also, is known about the
effects of plants in the operating phase. Following this introduction
is a description of the ORBES negion in general and then more detailed
descriptions of those counties which would experience primary impacts,
divided by state. t Rather than treat each county separately, they will
be described in clusters of contiguous or nearby counties. There were
several reasons for this decision: 1) on the map of the scenarios,
it is evident that the counties do cluster, usually around a water
course; 2) the variation among counties which are all part of a
particular sub-region can be better illustrated; 3) interactional
impacts, both within the cluster and between clusters can be more
easily discussed; and 4) ease of comprehension.
,An impact assessment of each cluster will follow a description
of the cluster, relating it to the typology. Subsequently, in the
Summary Section we will also indicate any perceived regional or inter-
actional impacts.
III-D-35
-------
Delineation of the clusters has been somewhat arbitrary and was
based primarily on geographic contiguity and sub-regional divisions
as indicated by the description of the ORBES region in general. All
counties in a single cluster are in the same state, even though there
may be counties in the adjacent state which are part of the same sub-
region. Differences among states in legal and organizational as-
pects plus some variation in: data bases were the reasons for this.
The information about size of plant and other technical in-
formation was supplied by the report of the Task I team or other
team members. At present the information on the construction
schedule is very sketchy and as a consequence, only broad generali-
zations could be attempted, even if the sociological data were
more complete.
3.2. METHODOLOGY OF DESCRIPTION
Descriptions are based exclusively on secondary data. We recog-
nize the limitations: 1) information is not up to date and for some
counties which have experienced much recent change, may present an
erroneous picture; 2) the data are not synchronic, e.g. agricultural
data are from 1969, population and housing data from 1970, industrial
data from 1972, and various other sources cover periods as late as
1975; 3) data were not collected for our purposes so the available
information often only indirectly bears on the questions we ask; and
4) collection methods vary. This is not an apology, but a statement
of the necessary conditions prevailing at this preliminary stage of
research. Any conclusions or evaluations drawn at this stage are
necessarily hypothetical and should be viewed with a skeptical mind.
The goal of any subsequent research must be to amplify, clarify,
correct and refine the baseline data in addition to testing hypotheses
suggested by the present state of the research.
Nevertheless, we do feel that the available information allows
for a description of the region and counties, delineation of sub-
regions, and a reasonably accurate picture of the nature of the
population and the quality of their lives which, although inaccurate
in detail, is not grossly untrue and which reflects sub-regional
variation. It is true that measures of affluence such as income and
housing values have almost certainly increased greatly since 1970, but
it is unlikely that later housing,and income figures would greatly
alter a qualitative assessment of life in these counties.
Efforts to enlarge and update the scope of the baseline data by
using state documents were abandoned after it was found that the
difficulties of uncovering comparable data for all counties in the
four state region were unlikely to be balanced by the increased under-
standing they provided.
The maps in Appendix A represent the spatial referents of the
demographic data we have used. We urge the reader to consult them
frequently while reading this report for we think them to serve a
clarification function.
III-D-36
-------
A qualitative evaluation of life in each major impact county, as
compared with life in another county is the purpose* of these descrip-
tions or "profiles". The focus is on people, the environment in which
they live, those with whom they may come into contact, the opportunities
and the options provided them.
The county profiles present a verbal picture of the societal as-
pects of county life distilled from the various data sources. Although
the same broad format was used for all profiles, there is some variation
because of the desire to emphasize some feature of the profile considered
to be significant from the interpretation of the data.
There was no statistical correlation of data items. The aim was
to compare and relate holistically the patterns evident in a variety
of social spheres.
3.3. SOURCES
In order to make the report concise and to promote ease of reading,
each of the major sources of data will be discussed in the following
section. Since the profiles will not discuss limitations of the source
or ways in which the information has been handled, this section should
be read before reading the profiles or assessments. Otherwise mis-
understanding is almost certain to occur.
3.3.1.s CENSUSES OF POPULATION AND HOUSING, 1970 (1, 2)
The largest part of our data comes from these reports which have
the advantages of complete coverage of the region, simultaneous and
uniform data collection. Frequently the information was taken from
the City-County Data Book, 1972 because of the reporting form but it
is census data (3).In almost all cases the figures have been con-
verted to percentages if they were not already in that form. The
reason for this was to show composition rather than magnitude and to
allow for comparability among counties. For this reason the reader
should note the county population size listed at the beginning of
each profile in order to make the mental adjustments necessary to
a full understanding of the profiles. When the authors felt that
biases introduced by this approach merited special notice, both the
figures and the percentages were dealt with in the text. The major
limitation of these data are that they are seven years out of date.
A second, minor problem is that some of the figures reflect a full
count of the population and others are statistics, that is numerical
inferences based on random sampling. However, very little sociological
data is not statistical so this is discounted. When figures are
quoted, it should be recognized that they are 1970 figures. We have
cited these,major sources only once for they reflect our primary
data base.
3.3.2. CENSUS OF AGRICULTURE, 1969 (4)
The data from this source, although close in time to the decennial
census, is eight years out of date. A more recent agriculture census
III-D-37
-------
was carried out in 1974 but the reports were not out in time for in-
corporation in this report. This updated information should be
consulted before proceeding into the second phase of research.
Farms covered by the census are classified and divided into two
groups. This division has been used in the tables on farming. Class
I-V farms include all farms with actual or potential sales of $2,500
or more in 1969. "Other" farms includes part-time or part-time re-
tirement farms which have sales of $50 to $2499 in 1969 as well as
Class VI farms which earned less than $50 or are under 10 acres and
earned less than $250. ClassI-V farms are the referent for "potentially
full-time farms."
3.3.3 CENSUSES OF MANUFACTURING AND GOVERNMENT, 1972 (5,6)
Because of the type of information and the form in which it has
been reported, these data have been used primarily to check the picture
of economic activities presented in other sources.
3.3.4 COUNTY BUSINESS PATTERNS, 1973 (7)
This governmental publication is a "statistical byproduct" of
business information reported to the Social Security Administration
which collaborates with the Bureau of the Census to assemble the
data. There are a number of limitations in the information: 1) The
data only onclude about 76.5 % of the total paid civilian wage and
salary employment. Excluded are the self-employed (approximately
9%), those in agriculture, domestic service, government, railroad
employment and a few others. This problem is compounded when attemp-
ting to describe economic activity at the county level because these
percentages are national averages and probably vary considerably
from county to county. For this reason the figures quoted from this
source are only given to provide a rough estimate of the types and
numbers of jobs which might be available to the ordinary person in
the county. An additional problem is that this publication
suppresses information which discloses operations of an individual
employer. Industries with less than 100 employees or 10 reporting
units are not reported. For this reason a certain amount of cross
checking among tables in this publication and between publications
was necessary. This involved further differences in dates and re-
porting methods. However, this publication was felt to give the
clearest indication of occupational diversification and opportunity.
The figures quoted only provide an indication for a point in time
three years after the census, and should only be used in a comparative
context. This source covers jobs within the county as opposed to
the U.S. Census which describes occupations of the resident population.
III-D-38
-------
3.3.5. U.S. FOREST SERVICE FIGURES (8, 9, 10, 11)
Estimates of the land in forest are carried out for each state at
irregular intervals. The dates of the survey for each state should be
kept in mind when examining this information. The reader should also
recognize that farm land and forested land are not mutually exclusive.
3.3.6. INCOME DATA
Updated income data came from two sources: 1) the Survey of
Current Business (12) which provides figures on per capita income, and
2) Sales Management (13) which provides a measure of "effective buying
power," shortened to "EBI" in the text and tables.
3.3.7. RECREATIONAL DATA
Data on parks (14, 15, 16, 17) were collected from each state and
vary as to date of collection and content.
3.3.8. BUREAU OF MINES PUBLICATIONS
The Minerals Yearbook and Mineral Industry Surveys (18, 19) were
the primary sources for mineral production.Another publication on
future fuel related projects for the eastern United States (20) was of
help in locating some of the sites for planned power units and in
estimating the work force.
3.3.9. KENTUCKY STATE DOCUMENTS
The Annual Directory of Manufacturers (21), the Annual Report of
the Kentucky State Departmient of Mines and Minerals (22} and the River~
Basin Water Quality Management Plan for Kentucky (23) were used to
elaborate or update certain aspects of the profiles for Kentucky counties.
Similar information was not attempted for the other states in the
ORBES region since this is the kind of library research that involves
hours of searching, many small judgements and the assistance of the
library staff. It could not reasonably be requested of members of
the other teams in the other states. The return does not warrant this
expenditure of time and expense.
3.3.10. CULTURAL DATA
The 1975 Official Museum Directory (24) of the American Association
of Museums and the National Register of Historical Places (25) as well
as a map on "Ranking Christian Denominations" (26) were the primary
sources of information on cultural amenities.
III-D-39
-------
3.3.11 SUPPLEMENTARY SOURCES
A miscellany of other sources were used to prepare the profiles
and all are listed as references. For the most part they are sources
come upon in the process of library search and felt to be of some sig-
nificance. However, they were not used consistently in every profile
and were mainly of assistance in clarifying, or interpreting the
profiles for some counties. (27-52)
3.4. LANGUAGE
In the interests of consistency several conventions have been used
in the prose descriptions of the profiles. Most of the maps have five
categories. The terms "high" or "low" refer to the categories at the
appropriate end of the continuum. The terms "relatively high" or
"relatively low" refer"to the categories adjacent to the "high or low"
categories. Where there are six or seven categories on the map, the
terms "slightly above" or "slightly below" average were used to denote
those categories closest to the middle of the continuum.
It is hoped that use of the above conventions would allow the
reader to mentally place the county within the ORBES region without
constantly referring to the maps.
3.5. SCENARIOS
The four scenarios represent two levels of energy production,
high and low. The first two scenarios are based on a 1975 Bureau of
Mines study (53), the third and fourth scenarios on a 1974 study
sponsored by the Ford Foundation (54).
The high energy scenarios are based on the assumption that
net energy consumption will almost double by the year 2000 due to
greater per capita energy use and increased dependence on secondary
energy sources with the concomitant conversion losses (55, p. 3).
Scenarios'I and II differ in the mix of coal and nuclear-fueled
plants. Scenario I posits an 80% coal/20% nuclear mix while Scenario II
posits a 50% coal/50% nuclear mix.
The third and fourth scenarios are based on low growth
assumptions about future energy use. The assumptions are that conser-
vation practices, slight reductions in real incomes and outputs will
allow for more than halving the rate of energy growth "without re-
quiring major sacrifices in real income growth." (56, p.511).
Scenario III assumes that all plants will be coal-fired, Scenario
IV that plants will all be nuclear-fueled.
III-D-40
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REFERENCES
1. U. S. Bureau of the Census. Census of Population, 1970.
Vol. I, Parts 15, 16, 19 and "ST. Washington, D.C: U. S.
Government Printing Office, 1973.
2. Census of Housing. 1970. Vol. I, Parts 15, 16,
19 and 37. Washington, D. C: 07~S. Government Printing Office,
1972.
3. _ City County Data Book. 1972. Washington D. C: U. S.
Government Printing Office, 1973.
4. _ _ Census of Agriculture, 1969. Vol. I, Area Reports,
Parts 10, 11, 12 and 30. Washington D. C: U. S. Government
Printing Office, 1972.
5- Census of Manufacturing, 1972. Area Series: MC72(3)-14,
MC72(3)-15, MC72(3)-18 and MC72(3)-36. Washington D. C: U. S.
Government Printing Office, 1975.
6. _ Census of Government, 1972. Washington D. C: U. S.
Government Printing Office, 1974.
7. _ County Business Patterns. 1973. CBP 73-15, CBP 73-16,
CBP 73-19 and CBP 73-37. Washington D. C: U. S. Government
Printing Office, 1974.
8. Burton L. Essex and David A. Gansner. Illinois' Timber Resources.
Lake States Forest Experiment Station, U. S. Forest Service
Resource Bel. LS-3 , 1965.
9. John S. Spencer Jr. Indiana's Timber. N. Central Forest Experi-
ment Station, U. S. D. A. Forest Service Bui. NC-7, 1969.
10. Neal P. Kings ley and Carl E. Mayer. The Timber Resources of Ohio.
Northeast Forest Experiment Station, U. S. D. A. Forest Service
Bui. NE-19, 1970.
11. U.S.D.A. Forest Service. "Kentucky Forest Survey, 1975: Pre-
liminary Data." Northeast Forest Experiment Station, (unpublished),
12. U. S. Department of Commerce. Survey of Current Business.
April, 1975: 39 - 48.
13. "1975 Survey of Buying Power." Sales Management. July 21, 1975:
32 - 78.
III-D-.-41
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14. Illinois Bureau of the Budget. Statistical Abstract. Tables 506
and 507. Springfield, 1973. *
15. Indiana Department of Natural Resources. Annual Report, Fiscal
Year Ending June 30, 1973.
16. Kentucky Department of Parks. " 1975 Kentucky Outdoor Recreation
Inventory." Unpublished data.
17. Ohio Department of Natural Resources. "Ohio Outdoor Recreation . :
Plan." (unpublished)
18. U. S. Department of the Interior, Bureau of Mines. Minerals
Yearbook. 1973. Vol. II. Washington D. C: U. S. Government
Printing Office, 1976.
19. Mineral Industry Surveys: Coal— Bituminous and Lignite
in 1974. (Preliminary)Washington D. C:U. S. Government
Printing Office, 1976.
20. U. S. Department«of the Interior. Projects to Expand Fuel
Sources in Eastern States. Bureau of Mines Information Circular
IC8725 (1976).
21. Kentucky Department of Commerce. Annual Directory of Manufac-
turers . 1975 and 1976.
22.. Kentucky State Department of Mines and Minerals. Annual Report,
1973.
23. Kentucky Department for Natural Resources and Environmental
Protection. The River Basin Water Quality Management Plan for
Kentucky, Volumes I - X, 1976.
24. American Association of Museums. Official Museum Directory, 1975.
National Register Publishing Co., Inc.
25. U. S. Department of the Interior. The National Register of Histo-
ric Places, 1976. Washington D. C: U. S. Government Printing
Office, 1976.
26. Glenmary Research Center. "Ranking Christian Denominations:
1971." Map. Washington, D. C.
27. 0. G. Bentley. "Rural Development in Illinois." Illinois Research.
Vol. 16, No. 4 (1974): 3-4.
28. David Bjornstad. "How Nuclear Reactor Siting Affects Local
Communities." Survey of Business. Vol. 11, No. 5 (1976).
. III-D-42
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29. Fiscal Impacts Associated with Power Reactor Siting:
A Paired Case Study. QRNL/NUREG/TM-86 (1977).
30. John C. and Jacqueline G. Callahan. "Effects of Strip Mining and
Technological Change on Communities and Natural Resources in
Indiana's Coal Mining Region." Lafayette, Indiana: Purdue
Agricultural Experiment Station, Research Bui. 871 (1971).
31. Luther J. Carter. "Failure Seen for Big Scale, High-Energy
Plans." Science, Vol. 195, No. 4280 (1977): 764.
32. Milton C. Coughenour. "Measuring the Quality of Life for Rural
Families." Appalachia. Vol. 9, No. 4 (1976).
33. "Quality of Life of Country Families in Four Eastern
Kentucky Counties: Change and Persistent Problems, 1961 and
1973." Lexington: University of Kentucky College of Agricul-
ture, Agriculture Experiment Station, Department of Sociology,
RS-46 (1975).
34. Forrest A. Deseran. "Age and Definitions of Community Situations:
A Comparative Analysis." Proceedings of Rural Sociology Section,
SAAS, Mobile, Alabama, Feb., 1976.
35. Thomas R. Ford and Gerry M. Arthur. "The Prediction and Explana-
tion of County Net Migration Rates in Kentucky: An Exploratory
Study." Department of Sociology, University of Kentucky, Agri-
Culture Experiment Station RS-44 (1975).
36. Jeanne L. Hafstrom, Marilyn M. Dunsing and Albert W. Gustafson.
"Early Background and Later Life Style." Illinois Research,
Vol. 16, No. 4 (1974): 18-19.
37. R. J. Hanson and R. G. F. Spitze. "Farm Size Characteristics
Affecting Off-Farm Earnings of Illinois Farmers." Illinois
Agriculture Economics, Vol. 14, No. 1 (1974).
38. John C. Hendee. "Rural-Urban Differences Reflected in Outdoor
Recreation Participation." Journal of Leisure Research,
Vol. 1, No. 4 (1969).
39. M. Knight. "A Connecticut Town Discovers Its Nuclear Power Plant
is a Mixed Blessing." New York Times. May 22, 1973.
40. J. B. Mitchell. "Rural Zoning." Ohio Report. Ohio Agricultural
Research and Development Center. Vol. 58, No. 6 -(1973): 124-125.
III-D-43
-------
41. Ted L. Napier. "Current Rural-Urban Attitudinal Differences."
Ohio Report. Ohio Agricultural Research and Development Center,
Vol. 57, No. 1 (1972): 6-7.
42- . "Rural-Urban Differences: Myth or Reality?" Ohio
Agricultural Research and Development Center, Research Bui. 1063,
(1973).
43. G. S. Phillips. "Attitudes and Opinions on Current Issues:
Ohio's Rural Non-Farm Residents." Ohio Report. Ohio Agricul-
tural Research and Development Center, Vol. 57, No. 4 (1972):
54-56.
44. G. H. Phillips and J. Rico-Velasco. "Changing Population in
Rural Ohio." Ohio Report. Ohio Agricultural Research and
Development Center, Vol. 57, No. 3 (1972): 45-47.
45. Carolyn P. Raetzke and Jeanne L. Hafstrom. "Some Differences
Between Nuclear Oriented and Extended-Oriented Families."
Illinois Research. Vol. 18, No. 2 (1976): 12-13.
46. Ann Satterthwaite. "Some Functions Recreation will Play for
the Individual in the Future." B. L. Driver, ed. Elements of
Outdoor Recreation Planning. Ann Arbor: University of Michi-
gan Press, 1970.
47. John T. Scott Jr. and C. T. Chen. "Expected Changes in Farm
Organization when Industry moves into a Rural Area." Illinois
Agriculture Economics. Vol. 13, No. 1 (1973).
48. R. G. F. Spitze and R. J. Hanson. "Off-Farm Jobs Boost Farm
Family Income." Illinois Research, Vol. 16, No. 4 (1974): 5.
49. D. W. Thomas. "Small Town Growth and Decline in Ohio." Ohio
Report. Ohio Agricultural Research and Development Center,
Jan. - Feb., 1972: 12-13.
50. J. C. Van Es. "Incorporated Places in Illinois." Illinois
Research. Vol. 16, No. 4 (1974): 8-9.
51. J. C. Van Es and Michael Bowling. "Migration and the Aging of
County Populations." Illinois Research. Vol. 18, No. 3 (1976):
6-7.
52. League of Women Voters of Kentucky, Inc. What is an ADD?
Regionalism and Land Use Planning in Kentucky. 1977.
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53. Walter G. Dupree Jr. and John S. Consenuno. United States
Energy Through the Year 2000 (Revised). U. S. Department of
the Interior, Bureau of Mines, Dec., 1975.
54. The Ford Foundation. The Technical Fix Scenario: A time to
Choose America's Energy Future, A Final Report.Energy Policy
Project, Cambridge: Ballinger. 1974.
55. Dupree and Consenuno. Energy Through the Year 2000.
56. Ford Foundation. Technical Fix Scenario.
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4. GENERAL CHARACTERISTICS OF THE ORBES REGION:
CURRENT SOCIAL, ECONOMIC AND LAND-USE STATUS
4.1. POPULATION CHARACTERISTICS
4.1.1. DENSITY
The 18.4 million people residing in the ORBES region are, of course,
not randomly distributed throughout the region, but cluster in a pre-
dictable fashion within topographic, prevailing land use, and social and
economic constraints to form a rather hetereogeneous pattern. (See
Map 14). The ORBES area as a whole is not a densely populated one, with
the vast majority of the counties containing less than 100 persons per
square mile. Pockets of heavy population density represent the few
metropolitan areas centered on one or more large cities (1000 or more
per square mile) and encompassing satellite and dormitory communities
and occasional medium sized cities (400-999 square mile). In north-
eastern Ohio just south of Cleveland (outside the ORBES region in Cuyahoga
County) is Akron, flanked on the south and east by the medium sized cities
of Canton and Youngstown. In central Ohio, Columbus is dominant and in
the southwestern Ohio is a metropolitan area with Dayton at the northern
edge and Cincinnati on the Ohio River. Between the two cities are the
small cities of Hamilton and Middletown. South of Cincinnati in Kentucky
are the small cities of Covington and Newport. Louisville, southwest of
Cincinnati and also on the Ohio River is the nucleus of a fourth metro-
politan area and Indianapolis in central Indiana is the nucleus of a
fifth.
The several medium sized cities are Fort Wayne and Evansville in
Indiana and Lexington, Kentucky. Population concentration in St. Clair
and Madison Counties, Illinois, are parts of the St. Louis metropolitan
area. East St. Louis is in St. Clair County. Those counties with
moderate density (100-199 per square mile) indicate the location of a
number of small cities.
The ORBES region can be roughly divided into two regions. The
first includes all of Ohio except the Appalachian area and the eastern
two-thirds of Indiana. In general the density of the population is
higher and the metropolitan areas more extensive than in the second
region comprising all of Illinois, Kentucky, the western third of
Indiana, and Appalachian Ohio.
4.1.2. RURAL/URBAN CONFIGURATION
The majority of counties in the ORBES region may be characterized
as mixed rural and urban, counties devoted to both pastoral, rural non-
farm, and small community pursuits. (See Map 13). The major metropolitan
centers are found clustered along the Ohio river, in the heartlands of
Indiana and Illinois, and cutting a wide swath from southwest to north-
east across Ohio.
III-D-47
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Urbanization has recently (1970-1974) spread out from major Ohio
River cities as well as from surrounding urbanized areas in Central
Ohio (Columbus), the Ft. Wayne, Indiana/Lima, Ohio area, Central
Kentucky (Lexington), and the Illinois area near St. Louis.
Completely rural counties are a minority in the region and are
found primarily in Kentucky, and clustered in the Appalachian section.
(See Map 13). The mountainous topography of the area militates against
the formation of communities larger than 1000 population (as do im-
portant economic factors) and the population residing there is not only
scattered primarily along roadways and comparatively isolated from one
another but also from the rest of the region. Rural areas with larger
communities (up to 2500 population) are scattered throughout the state
of Kentucky, clustering again in the Appalachian area and along the
banks of the Ohio River as well. Particularly notable are the number
of contigous counties with no community over 2500. Highly rural
Illinois communities share the river and are also found along the
Western borders of the state, though rarely. Appalachian Ohio pre-
sents a similar but much less strong pattern of location of its four
very rural counties. Other highly rural areas in the region are
scattered about Indiana and Illinois and are surrounded by mixed rural
and urban areas and some are on the fringe of SMSAs.
4.1.3. STABILITY OF RESIDENCE
One rather striking characteristic of residents of the ORBES region
is their relative lack of geographic mobility, or put another way, their
preference for maintaining their home (birth) state as their residence
state. (See Map 23 ). The overwhelming majority of the counties are
populated by native-born residents. Again it can be seen that the
Illinois, Western Indiana and Kentucky portions of the ORBES region
house the more stable while the Ohio-Eastern Indiana portions contain
the more mobile populations. As is to be expected the more mobile
residents are concentrated in urbanized areas and in border counties.
The most stable segments of the population are concentrated in the
rural areas of Kentucky. The exceptions in Hardin and Meade County
in Kentucky probably reflect the existence of Fort Knox. Clark County,
Indiana and Fulton County, Kentucky are unexplained at this time al-
though the situation is possibly a consequence of the conjunction of
several states at that point.
While we cannot say, at this point, whether these people have gone
and returned after a sojourn in other states, recent figures for the
five-year period of 1965-70 do suggest that this stability is of at
least that long a duration. (See Map 28). Only a few scattered
counties show less than eighty percent of the population as five-year
residents. Of these counties, Champaign and Jackson in Illinois,
Monroe in Indiana, Hardin in Kentucky and Greene in Ohio have sizable
universities in moderate to small size communities. In addition both
Hardin and Christian Counties in Kentucky have large military in-
stallations. The other anomalous counties are unexplained at this time.
Areas that are characterized by over 90% of the population having lived
there five years or more are primarily rural and semi-rural areas-
III-D-48
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This picture of stability becomes even more clear and specific
when one looks at the percentage of the population residing in the
same county over this same five-year period (See Map 28). Again
some of the same factors may apply. Portage and Athens in Ohio,
Tippecanoe and Johnson in Indiana, Fayette in Kentucky, McDonough
County in Illinois all have universities. Kentucky particularly
shows the majority of counties have eighty or more percent having
chosen to remain in the same county for at least five years, as do
those residing in eastern Ohio, southern Indiana, central and western
Illinois.
4.1.4. MIGRATION
Migration trends within the region can be characterized as to
type and direction by examination of Maps 16 and 17, showing figures
on net migration within the ORBES region. The recent reversal of the
trend of rural to urban migration to urban to rural shows up here,
particularly in eastern Kentucky, an area which has traditionally lost
population for decades. The counties losing population recently form
an east-west band in central Kentucky, through scattered counties where
Kentucky, Indiana and Illinois meet, up the Wabash River toward Chicago,
across north central Indiana to west central Ohio. Other pockets of
out-migration are along the Mississippi River in Illinois and extreme
northeast Ohio.
Eastern Kentucky and southeastern Ohio are gaining population in
part due to the coal boom. However, the reversal of a hundred-year-
old migration trend also says much about the preferences of people
shifting away from urban areas to more rural ones. Still, many of
the areas gaining population in the ORBES region are those near SMSA's
suggesting that dependency on urbanized areas continues to exist, but
perhaps more so on the fringes of SMSA's rather than in their urban
cores. Generally speaking, the ORBES region states are gaining
population through migration, though Illinois counties are faring less
well in this respect than Indiana and Kentucky.
4.1.5. AGE
Maps of the age composition of the ORBES region population (Maps
29-35) have been prepared as well as graphs illustrating the population
composition of impact counties. Map 35, showing the proportion of
the population 65 years of age and older, possibly lends further
clarity to our description of the remarkable stability of the popu-
lation, by suggesting, albeit indirectly, that many of the native
residents are life-long ones. Older residents are noticeably concen-
trated in western Illinois and the counties along the Ohio and Wabash
Rivers in southern Illinois and extreme western Kentucky. This latter
area is characterized by numerous recreational facilities, e.g. the
Shawnee National Forest, a low level of urbanization (Map 95). This
Illinois migration trend of the 1960's has been described as one,
primarily of the elderly, moving from the northern cities to the southern
rura 19 counties with an accompanying out-migration of the young from these
southern counties (l.p.7.). Examination of Map 16 inclines one to
suspect an out-migration from the state as well.
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Kentucky and Illinois have the highest proportion of counties where
the elderly account for 12% or more of the population and only parts
of western Indiana and southeastern Ohio may be so characterized. The
counties with low percentages of older population appear to correlate
with urbanized areas, universities, and military installations. The
low percentage of elderly in the extreme eastern Kentucky, especially
in Pike, Leslie, Rowan and Greenup Counties are extremely provocative.
4.1.6. SEX COMPOSITION
As with most of the rest of the United States, females make up the
majority of the population, (51%). Map 36 shows where females comprise
at least fifty-three percent of the population and over, suggesting,
in part, that many of these women are, due to greater female longevity,
somewhat elderly (See Map 35 as well). Military bases and university
communities account in part for counties where men considerably outnumber
women.
4.1.7. MARITAL STATUS
The proportion of married males in the population is shown in Map
43 and females in Map 44. Together, the most "married" population cuts
a wide swath through the very center of the ORBES region from its south-
western tip to its northern center, an area where at least 70% of the
males and 65% of the females form marital units. The noticeably low
proportions of married males in Illinois, together with the generally
higher percentage of females in the population (Map 36) tend to support
the suggestion of out-migration of youth, especially males.
A slightly different picture of the married emerges in Map 45 which
shows the proportion of "intact" families compared with all families.
This map shows Indianapolis as sort of the "hub" from which a high pro-
portion of intact families radiate north-south in Indiana and east and
west into Ohio and Illinois respectively. Kentucky is somewhat of an
anomaly with regard to intact families, particularly in eastern Kentucky.
Maps 39 through 42 shed a little more light on this interesting configu-
ration of marital status graphically displayed by showing the propor-
tion respectively, of females and males in the population that are
either widowed or divorced. Females at any given time do show a greater
proportion of their population as not-married than do males, in demo-
graphic terms, so the relative proportion is what is of interest here.
Map 40 shows a heavy concentration of formerly-married women in southern
Illinois, as is the case for men as well in Map 39. The relatively
large proportion of the population that is over 65 suggests that many
of these residents are older widows and widowers who are retired here.
Eastern Kentucky, however, presents no clear picture at this point as
is a fairly high percentage of not currently-married women and no
correspondingly high proportion for men. This may point to a higher
out-migration level for men than for women.
III-D-50
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Knowing the number and age of children among families helps to
tell us about what stage characterizes the population in the family
life cycle and their adaptability to developmental change. Not too
surprisingly, Map 46 shows a high proportion of families with children
in a pattern similar to our "intact families" map, but with information
about eastern Kentucky, which shows large numbers of families with
children under 18 (being discrepant from the norm). Since the popu-
lation here is probably fairly young, a fairly high degree of marital
instability may characterize this area, though we are far from certain
about this speculation. .It is also possible that religion and contra-
ceptive practices may be different here. Map 47, however, does show a
very high proportion of families there headed by females. Illinois
patterning points to the probability that most families are in later
stages of the family cycle.
4.1.8. ETHNIC COMPOSITION
Not surprisingly, the only significant concentrations of foreign-
borns or those of foreign or mixed parentage are on the outskirts of
Chicago and westward in northern Illinois and in the far northeast
corner of the ORBES region near the urban-industrial northern cities.
4.2. SOCIO-ECONOMIC CHARACTERISTICS
4.2.1. INCOME
The ORBES region, compared with the U.S. as a whole in terms of
per capita income, is not a wealthy area. However, there are a series
of counties in Central Illinois, Indiana, and southwestern and north-
eastern Ohio that manage to be at or above the U.S. mean per capita
income. On the other hand, there is a considerable pocket of very low
per capita income centered in Appalachian Kentucky and spreading west-
ward and northward. Another small pocket of low per capita income is
to be found in very southern Illinois and western Kentucky. (See
Maps 69 and 70).
Median family income (Map 68) shows much the same picture, but
more sharply (at least for families). Only Kentucky has counties where
family median income falls below $4,000 a year. The- ORBES region, meta-
phorically, is built somewhat like a layer-cake in terms of median in-
come, with the bottom slice being the poorest (eastern Kentucky) moving
northwesterly to slightly higher median incomes, a layer of medium to
moderate incomes ($5,000 tO $8,999) and then an icing of a fairly high
income layer. The metaphor wears off above the fairly well-to-do belt
in central Illinois, Indiana and the southwest and northeast corners of
Ohio. Incomes begin to decline again above that, though not to low
levels. Areas around SMSA's (except for the Ashland'area and Christian
County in southern Kentucky) tend to have median family incomes of at
least $7.,000 and the majority have incomes above $9,000. •
Map 67 showing percentage of families with incomes above $15,000,
presents a somewhat different picture, especially with regard to high and
low percentages of that income. Counties with highest percentage of rela-
tively well-to-do families are in the same affluent belt previous maps have
III-D-51
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shown, but there are fewer of them. The counties with less than five
percent of the families earning $15,000 or more now form a belt north-
west of the Appalachian counties running from Western Kentucky, Southern
Illinois across Kentucky to a few isolated counties in Southern Ohio.
The majority of counties have a moderate proportion of the well-to-do
(7.5-14.r*
Map 74 is somewhat the converse of the preceding maps, for it shows
the percentage of families below the low income level in 1969. Here the
layer-cake effect is even more pronounced. One must think of the cultural
and lifestyle differences, as measured by income, that are present in
the region; the southern third of the ORBES region is by and large very
poor and the northern third comparatively very well-to-do, and about on
par with U.S. averages or better. Moreover, as Map 76 shows, the poverty
strikes disproportionately at the young in the southeastern quarter of
the region compared to the rest. Or, as Map 75 shows, it strikes dis-
proportionately at the old in the northwest quadrant. So, even among
the poor, life-cycle differences in association with poverty vary
greatly in the region.
Even among the old and poor, the nature of the poverty as measured
by percentages paid for old age assistance (Map 77) varies too. The
highest percentages are to be found in Western, South-central and Northern
Kentucky, and the next highest among the remaining Kentucky counties with
a few exceptions. Old age benefits account for less than 30% of Public
Assistance payments in all of Illinois, and in the vast majority of
Indiana counties. The same is somewhat less true of Ohio.
Clearly percentages paid for old age assistance do not correlate with
percentages of the elderly in the low income population. Illinois, with
the highest percentage of elderly in its low income population pays out
a very small portion of public assistance to those 65 or older. The
parts of Kentucky with very high portion of public assistance going to
the elderly have, in general, moderate proportions of the elderly in
the low income population.
A patterning similar to Map 77 on old age assistance can be seen in
Map 67, "percentage of families with incomes of $15,000 or more." Illinois
and Indiana have generally low levels of poverty (Map 74) and of these a
high proportion are elderly. Many of the elderly in the well-to-do parts
of Illinois and Indiana may not be experiencing substandard living con-
ditions in spite of low level of money income. The higher likelihood of
their having had a relatively affluent working life (Map 69) and having
accumulated sufficient assets to provide for comfort and security, would
result in fewer of their numbers receiving old age benefits. Public
assistance could then be diverted toward other categories of the poor.
Conversely, in parts of Kentucky with a few at higher income levels, it
is less likely that the elderly would have been able to provide their
own old age security during their working life and thus one would ex-
pect a large percentage of the elderly to be recipients of old age
benefits. Since the old comprise a more substantial percentage of the
III-D-52
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poor than in those eastern Kentucky counties with even higher levels of
poverty, as one would expect, the percentage of public assistance de-
voted to old age benefits is higher.
4.2.2. THE FARM POPULATION
While farming may be as lucrative as any other business enterprise,
it can also be little more than a source of cheaper vegetables or re-
current debt. Many of the characteristics of the agricultural industry
are detailed in the land-use section which follows this one. However,
living on a farm is one type of lifestyle commitment that is important
both to the persons engaged in that pursuit and to the economy of the
region. Map 68 presents crucial information on the personal income of
farmers, and the value of farm products and land types and sizes of
farms, and changes in numbers of farms and farm acreage. These are
illustrated in Maps 90, 91, 92, 93, 94, 88, and 89. Nonetheless, Maps
15 and 19 do give us some valuable information on the farm population.
Kentucky (Map 15) has, by far, the most counties where 40% or more
of the population reside on farms. Ohio and Illinois both have only
one such county so characterized. If we expand our definition of rural-
farm life to include counties where at least a quarter of the population
resides on farms, then approximately half of Kentucky but less than a
quarter of Indiana and Illinois and only a tiny portion of Ohio qualifies.
(Size of farm is of course a crucial variable here: see land-use
section).
Map 19 shows an interesting pattern of changes in the farm popula-
tion over the 1960-70 decade with a massive loss (40% or more) character-
izing the southeastern border of the ORBES region, south-central Indiana
and bits of southern Illinois and western Kentucky.
All counties in the ORBES region show losses of farm population
except one (Massac County in Illinois), part of the national trend of
the decline of small farms and concommitant consolidation of existing
farms into ever-larger enterprises with fewer owners.
Map 65 represents the economic need to seek employment elsewhere
among farm operators, suggesting indirectly something about the relative
profitability of farming in the region. North-central Illinois by this
measure has fewer farmers working 100 or more days off the farm, southern
and central Kentucky also has a fairly high proportion of full-time
farmers as does the remainder of Illinois and parts of eastern Indiana.
The same is true of a few isolated counties in east-central Indiana and
central and northeastern Illinois. Judging by this admittedly imperfect
measure, generally speaking, farming is regarded as a full-time activity
by half or more of the farmers in the region and must provide at least
an acceptable level of return for them-and their families, whether it
be a bountiful return or not.
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4.2.3. SELECTED OCCUPATIONAL CHARACTERISTICS
University and college communities and many SMSA counties show a
predictably high proportion (20% or more) of employed professionals
and managers (Map 57 ). So, surprisingly, do several counties in
Appalachian Kentucky. This phenomenon deserves further exploration
in the future. Map 64 does show that a fairly high proportion of the
professionals in Eastern Kentucky may be in the education field. (This
map also includes non-professional school support personnel). Counties
with colleges and universities without a great deal of other economic
diversification also show up clearly on this map.
Eastern Kentucky shows a high proportion of the labor force
working for the government as do some of the poorer counties in
Southern Illinois (Map 62 ). Presumably much of this is associated
with the administration of public assistance programs. State hospitals
and other large governmental personnel.
Employees dependent upon the manufacturing industry to earn a
livelihood form a heavy proportion of the work force in over half of
Indiana and Ohio (Map 52 ). The heaviest concentration of manufacturing
is found in the Eastern half of Indiana and the Northeastern quadrant of
Ohio. Conspicuously lacking in employees engaged in manufacturing is all
of Eastern Kentucky, much of Southern Illinois, and scattered Central
Illinois counties.
The high percentage of the labor force employed in retail trades
(20%+) (Map 59 ) reflects primarily trade center communities scattered
throughout the region. Only a few counties in Kentucky have less than
ten percent of the labor force employed in retail trades.
The construction trade (Map58 ) has fair prominence in Eastern
Kentucky, reflecting work associated with mining in large part. Another
pocket of fairly heavy concentration of construction workers is in
Western Kentucky and the tip of Southern Illinois, reflecting most
probably work on the Interstate occurring near 1970. The same is
probably true of Crawford County in Southern Indiana.
It should be remembered that these maps do not necessarily indicate
the location of high levels of construction activity. Proportionately,
a larger part of the labor force is dependent upon construction activity
which by its nature is less stable than some other forms of employment.
4.2.4. UNEMPLOYMENT
Unemployment (Map56 ) is definitely associated with the degree of
poverty in Eastern Kentucky and Southern Illinois. Of interest is the
band of high employment stretching east to west across Northern Ohio,
and Central Indiana and Central Illinois as well as in the Bluegrass
area and surrounding counties in Central Kentucky.
III-D-54
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4.2.5. WOMEN IN THE LABOR FORCE
Again, Appalachian Kentucky and Ohio show another deviant pattern in
a minimal proportion of women in the work force, as does the tip of
Southern Illinois (Map 54 ). Lack of employment opportunities characterize
these areas. Particularly hard hit must be the Appalachian women who are
heads of households(See Map 47).
Central Illinois, NortheYn Indiana, and the Bluegrass area of Kentucky
show high percentages of women in the labor force^and their participation
in the labor force is generally associated with areas of relatively high
median income of families,as well as higher per capita income (See Maps
68 and 69 as well).
Map 55, the percentage of families with both husband and wife
working, shows much the same pattern described above, detailing even
more clearly the women's contribution to overall household affluence
(as well as their lack of contribution elsewhere).
4.2.6. COMMUTING WORKERS
Naturally, SMSA areas draw workers from surrounding counties,
particularly the central-city counties, as Map 51 shows. The patterns
on the map show precisely which counties are "commuter" counties and
which are "recipient" counties. This facet of county life should prove
interesting in future sections of this report where we discuss the
likely impacts of power plant construction.
4.2.7. EDUCATIONAL LEVELS
The affluent belt seen in previous maps crossing Norttyjft*«tffa,l
Illinois, Indiana, and Ohio also represents a comparatively well
educated population, the median being 12 years or more (Map 48). The
layer-cake effect is once more present with Southern and Eastern
Kentucky showing very low levels (9 years or less) of educational
attainment in the population. Except for a cluster of counties in
Southwestern Indiana, Northern Kentucky, and Southern Illinois, Indiana
and Ohio represent intermediate levels 'of educational attainment.
Educational levels are usually lower in rural areas as opposed to urban
areas. However, while this holds true here,too, of more striking sig-
nificance are the vast discrepencies that characterize the region.
Since educational attainment is associated also with income and
occupational status, these educational differences point to vastly
different lifestyles and even perceptions of lifestyles.
c n Sep , Kentucky> most counties in the ORBES region have a
5 - 9.9% college educated population. The predominant percentage in
Kentucky is 5% or less. Exceptions are the university communities
with small populations and undiversified economies.
III-D-55
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Those who failed to complete high school are shown in Map 49.
Nearly all counties in Kentucky show that 60% or more of the popu-
lation falls in this category, rising to 80% or above in some
Eastern Kentucky counties.
Most of the ORBES region can be characterized as not highly
educated with 49% or more of the population not completing high
school. Only Northcentral Illinois, Indiana and Ohio escape this
trend.
4.2.8. HOUSING
Housing lacking some or all plumbing is a surrogate index for
poverty, and Map 83 looks somewhat like Map 74. Rather primitive
housing characterizes the Eastern Kentucky counties where 30% or
more houses lack some or all plumbing. Conversely, in the affluent
belt of Northcentral Illinois, Indiana and Ohio, less than 5% of
housing may be so characterized. Map 84 shows household density and
once again, Eastern Kentucky shows a high proportion of crowded
houses. Much of Kentucky and parts of Southern Indiana and Ohio
indictate a fairly high prevalence of crowded housing conditions.
The affluent belt, of course, shows the opposite. The map may be
explained in terms of size and worth of homes, presence or absence
of extended family under one roof and the number of children present
in the household.
Map 80 shows the percentage change in year-round housing units
during the 60s decade. Counties gaining ten percent or more housing
units form a wide swath from the South-central Kentucky border due
north through Central and Northern Indiana and eastward diagonally from
the southwest to northeast corner of Ohio. Counties in far Southeastern
Kentucky and Ohio and in Southern Illinois which show a loss in housing
units are also counties which are experiencing out-migration (See
Maple ). Clearly Illinois is the most stable of the four states. Most
counties in the ORBES region, however, are gaining housing and most have
a growth rate of 10% or more.
Home ownership patterns are shown in Map 86 and are in part an in-
dicator of the relative transience or stability of the population. In
this sense, the more stable areas are to be found in Southeastern Illinois
and Southern Indiana. SMSAs and college and university and military
communities generally show a high percentage of rental housing. Kentucky
once again shows a higher proportion on non-owner occupied homes re-
flecting in part the greater poverty of the state as well.
As can be seen in Map 85 . the prevalence of one-unit structures is
fairly homogeneous throughout the ORBES region, with only a few exceptions,
notably some central-city counties of SMSAs. Tippecanoe and Monroe
counties in Indiana and Meade and Hardin counties in Kentucky are all
university or college communities and the Kentucky counties are near
Fort Knox as well.
III-D-56
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4.3 LAND USE
4.3.1. COAL
Coal supplies are of course, of crucial importance to the coal-
utilizing power industry. Map 2 shows both where coal reserves lie
and which counties are the coal-producing ones. Kentucky leads the
region by far in terms of coal production with operating coal mines
in Eastern and Western Kentucky. Most of the fertile Illinois farm-
land is also underlaid with coal though only the Southern Illinois
region is a major producer. Eastern Ohio and Western Indiana also
have quite a few coal-producing communities.
4.3.2. FORESTS
Forestry was once a major industry in parts of the ORBES region,
notably in Eastern Kentucky, and it continues today on a much-reduced
scale there. Map 4 shows the percentage distribution of forested
land (figures vary,from 1965 to 1975 sources). Forest acreage
gradually decreases as one moves northwestward across Kentucky except
for the Bluegrass area with little forest acreage. Forested areas
surround Brown County in South Central Indiana and generally charac-
terize counties along the Ohio River. Other forested patches are to
be found in Eastern Ohio and Southern Illinois.
4.3.3. FARMLAND
The great agricultural expanses of most of Illinois, Northern
Indiana and Northwestern Ohio show up as a clear belt in Map 3 . The
forested Appalachian area clearly shows up as non-farm area as well.
Generally speaking, except for the large cities in the region, the
vast majority of the ORBES region can be characterized as primarily
agricultural in nature, though as we will see, the size and profita-
bility of agricultural pursuits varies quite widely.
Map 89 shows the dynamics of changes in farm acreage for the 1964-
69 period. Part of what is shown here is farm land loss associated
with urbanization and part of it is connected with the relative un-
profitability of the enterprise, especially in Eastern Kentucky and
Appalachian Ohio. Decline in farm acreage occurs not only here but
along much of the Ohio River with a few exceptions.
Map 88 further clarifies the trends shown in Map 89 for it dis-
plays changes in the number of farms showing sharp declines in Eastern
Ohio and Kentucky as well as in Southern Indiana and Illinois. Again
increase in the number of farms sometimes means smaller farms, par-
ticularly near urbanized areas where "baby farms" are a popular form
of suburban living. Maps 88 and 89 show that an increase in number
of farms as well as farm acreage was primarily a Northeastern Ohio and
Central Kentucky phenomenon. Illinois, the Southern border of Kentucky,
and to some extent Northern Indiana exhibit the general trend of in-
creased farm acreage consolidated into fewer holdings.
III-D-57
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As stated previously and shown in Map 92 , the size of the farm
varies widely in the ORBES region, with the largest farms to be found
in Illinois, Northeastern Indiana and Central Ohio. Very small farms
(100 acres or less) characterize the Southern Appalachian area in
Kentucky and moderately small farms (100-200 acres) characterize al-
most all of Kentucky, Ohio and three-quarters of Indiana.
Relative profitability is shown indirectly in Map 93 and more
directly on Map 94 . These two together support the contention that
profitability of farms is in part a function of size as well as what
is grown. Counties with larger farms show a much higher percentage
of sales of $2500 or more than do counties with small farms.
The average market value of agricultural products per acre (Map 91)
shows considerable discrepancy across the region with the Northern
part of the Region doing much better than the Southern. Further
evidence of the relative profitability of farming is found in Map 90
the average value of farm land and buildings per acre. Illinois
clearly has the largest area of the most valuable farm land with
Indiana running a close second. About half (the Southern half, with
the exception of the Bluegrass area in Kentucky and the area where
the Wabash and Ohio Rivers meet) the ORBES area contains farms worth
$299 an acre or less. These areas in particular are candidates for
land use other than farm, notably mining and forestry.
III-D-58
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REFERENCES
J. C. Van Es and Michael Bowling. "Migration and the Aging of
County Populations." Illinois Research, Illinois Agriculture
Experiment Station, Vol. 18, No. 3 (1976): 6-7.
III-D-59
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5. DEMOGRAPHIC PROFILES AND IMPACT ANALYSIS: KENTUCKY
5.1 RUSSELL COUNTY (10,542).
Russell County in South Central Kentucky is the proposed site
of a nuclear power plant in both of the high energy scenarios.
Currently the only power generating facility is a 270 megawatt hydro-
electric plant at Jamestown. The two-unit plant in the first scenario
and the three-unit plant in the second scenario will bring the county's
generating capacity up to 2,270 or 3,270 megawats respectively by
2000.
5.1.1. LAND USE
Lake Cumberland and the land between its numerous fingers covers
the southeastern half of Russell County, providing over 50,000 water
recreational acres. Of the land area, almost 77% is devoted to
farming and over 50% of the land is forested. Urban use of the land
is minimal since there are only two towns with over 1,000 residents
and both are small.
Both Jamestown (pop. 1,027) and Russell Springs (pop. 1,641) are
located on U. S. 127 which runs north-south across the county.
Running east-west with a junction at Russell Springs are a toll road
and State Highway 80. Twenty-four miles east on these roads is
Somerset (10,436) and 52 miles to the west is Glasgow (11,301).
There is no mining of coal in Russell County. There is, however,
some quarrying of sand and gravel and production of petroleum totaling
$22,000 in 1973.
5.1.2. RECREATIONAL AND CULTURAL FACILITIES
As mentioned above, Russell County is at the center of a large
recreational area around Lake Cumberland, with 3,629 land and 50,263
water acres devoted to recreation, part of this a state park. In
addition, Green River Lake is only 23 miles north-northwest from
Russell Springs on State Highway 76.
There are no museums or other urban recreational facilities in
the area.
Baptists are the dominant religious denomination.
5.1.3. RESIDENCE
This rural, sparsely (44 persons per square mile) populated county
is well removed from any of the urbanized areas in Kentucky. A very
high percentage of the popi/lation lives on farms (44%), the rest in
III-D-61
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small towns or in the countryside. The population is composed primarily
of native Kentuckians (91.3%), with a few people from the North Central
U.S. (3.9%), and is very stable. Almost 92% of the residents lived
in Kentucky in 1965 and 87% resided then in Russell County.
Like much of Kentucky, Russell County has experienced a reverse
in the trend towards loss in population and out-migration since 1970.
In the 1960's net migration was -14.7 and the population declined by
4.8%. Since 1970 the population grew by 9.9% and migration rate is
7.6. Much of this loss in the 1960's must have been from the farm
population which decreased by 20.9% since the towns of Jamestown and
Russell Springs both showed moderate increases (29.7 and 45.9 percents
respectively) during the same time period. We cannot say whether the
reversals reflect an increasing tendency to stay on a farm.
5.1.4. AGE STRUCTURE
Russell County has a relatively high median age of 33.6, reflecting
the relatively high percentage of the population over 65 (13.3%)
The graph of age structure shows a sharp decrease in the young
adult population, both male and female, presumably the result of out-
migration. This and the substantial proportion of adults 45 and older
present a picture of a population with families mostly in the later
stages of the family cycle. Maps on marital structure support this
interpretation. Although percentages of married men and women are
high or relatively high, percentages of single men and women are
relatively low or low. There are average numbers of widowed men and
women but relatively low percentages of divorced men and women as well
as families with female heads. However, the proportions of intact
families and families with children under 18 are also moderately low.
This indicates that most of the population marries, marriages are
reasonably stable, but many families no longer have children at home
and often one of the spouses is dead.
Without seeing a graph of age structure since 1970 it is impos-
sible to speculate on the composition of the recent in-migrants. A
guess is that increasing development of recreational facilities may
be keeping some of the original population and drawing others, possibly
at retirement.
5.1.5. EDUCATION
Educational levels are characteristic of rural Kentucky, low,
with very few having completed college or even high school. There is
no resident college population in this or any of the neighboring
counties.
III-D-62
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5.1.6. HOUSING
There was only a small gain in-the number of households between
1960 and 1970. Nevertheless, there was a sizeable percentage of
housing units built in that time (21.2%) as well as a 23.2% increase
in the number of housing units. Considering the population losses
and out-migration during the same period, this must mean the residents
are building new residences and splitting households into smaller
units.
Housing units are overwhelmingly owner-occupied (80%) one-unit
structures (92%). Many (31%) lack some plumbing. House values are
relatively low ($7,658) as are rents ($51). As expected in an area
with a predominance of the elderly, only average proportions of the
units are over-crowded with more than one person per room.
5.1.7. ECONOMIC ACTIVITY
Characteristic of this-part of Southern Kentucky, Russell County
exhibited small gains in farm acreage (1.4%) coup-led with small losses
in numbers of farms (-3.0%) between 1964 and 1969, indicating a trend
toward farm consolidation. Farming is not profitable in Russell
County. Class I-V farms are small (average 128 acres) and average
return is low ($7,545). Various farming activities are pursued with
livestock raising and tobacco dominant, but the few class I-III farms
(114 out of 608 Class I-V farms) suggest that very few farmers have
economically viable operations.
Table III-D-3
!
Ky-1 FARMS BY TYPE
Type No. of Farms
Livestock (exc. poultry and dairy) 235
Tobacco • 130
General 118
Dairy 92
Poultry 16
Out of 1,540 farms, 932 are either part-time retirement or class VI
farms. The average return on these farms is $1,040 and the average
size is 42.3 acres. The fact that only 40% of farmers worked 100 or
more days off the farm in 1969 suggests both lack of supplementary
employment opportunities and generally low income expectations.
Although Russell County does not have large absolute numbers of
workers covered by County Business Patterns it apparently provides
job opportunities for residents of nearby counties as well as its
own residents.
III-D-63
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Table III-D-4
Ky-1 COUNTY BUSINESS PATTERNS, 1973
Total Population 10,542
In CBP 1,558
Construction 61
Manufacturing 897
Transportation 37
Trade 408
Finance and Services 141
The primary non-farm economic activity is manufacturing, but
significant numbers are involved in trade as well. The major type of
manufacturing appears to be textiles and apparel. There is nothing
else with even 100 employees by 1975.
In examining the residents of Civilian Labor Force for 1970, and
comparing the figures with those in County Business Patterns, it should
be noted that the 11% of the Civilian Labor Force employed in construc-
tion does not appear to be part of the employment picture in 1972.
Perhaps in 1970 there was a large construction project in or close to
the county.
It is difficult to interpret other aspects of the occupational
structure. As often happens in small counties with little diversity
in economic activity, those in education and government service
represent a higher than average percentages of the Civilian Labor
Force. It appears also that relatively few wives work, not surprising
considering the large rural farm sector. The percentage of women in
the work force, however, is just about average, probably reflecting of
the percentage of women who must work and possibly also the fact that,
of ten work force in the textile and apparel industries, most are
women.
5.1.8. INCOME
Per capita and median family incomes in this rural county are low
($1,635 and $4,497). For farm families median income is only slightly
lower ($4,033). By 1973 the relative position of Russell County had
not changed. Per capita income was still low ($2,527). The statistics
in Sales Management support this picture of low "effective buying
power" with few in the higher categories and many with an EBI of less
than $3,000.
Low income population is high (35.7%) and even.higher in the farm
population (37.9%).
III-D-64
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5.1.9. IMPACT ASSESSMENT
Russell County, being poor, very isolated and rural in nature,
has the primordial belonoingness sub-orientation. It is also a seeming
candidate for the classi c boomtown syndrome associated with power plant
development in these kinds of communities. However, its lack of economic
diversification and an infrastructure to deal with boomtown demands
means that the boom *is likely to take place in nearby Somerset, in
another county, which does have more amenities and facilities to offer
the labor force during the construction phase. Residents then will
have to deal only with day-to-day impacts. We predict some conflict
between the instrumental orientation of the utility companies and
those residents whose land is seen as a possible site, for their
attachment to place is likely to be very strong as it is with many
Eastern Kentucky residents.
III-D-65
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5.2. TRIGG, (8,620), LIVINGSTON, (7,596), MARSHALL, (20,381),
BALLARD, (8,276), ANU CARLISLE, (5,345) COUNTIES
Five counties in the extreme western section of Kentucky are
slated for power plants under the two high energy scenarios. Each
will be the site of a two-unit (2,000 megawatt) coal-fired plant
under scenario one. All but Ballard County will have a two-unit
coal-fired plant under scenario two. Scenario three, the low energy
coal based scenario, would place one plant (1,500 megawatts) in
Livingston County.
At present, Livingston is the only county with an operating
power plant facility. This is a small 130 megawatt hydroelectric unit
at Grand Rivers. There is, however, in neighboring McCracken County,
a 1,750 megawatt coal-fired power plant.
These five counties do not form a contiguous cluster. Trigg
County on the Tennessee border is directly to the east of Lake Barkley
and the "Land Between the Lakes" recreation area. Livingston County,
north of the "Land Between the Lakes" area, is on the Ohio River.
Marshall County, just south of Livingston, lies on the western side
of the "Land Between the Lakes" area and Kentucky Lake. Ballard and
Carlisle Counties are on the Ohio River about where the Ohio and
Mississippi Rivers converge.
"Except for Marshall County, these counties appear to be just
off the major highway routes. The Kentucky Parkway, a toll road,
runs diagonally across the state from Ashland through Lexington,
across the northern edge of the "Land Between the Lakes" area, across
Marshall County to Mayfield in Graves County and to the state border.
At intervals, major roads lead north and south to population centers.
In this area only three are of significance. Paducah, 27 miles north
of Mayfield in McCraoken County, is the largest of the cities (31,627).
Situated on the Ohio River between Ballard and Marshall Counties, it
probably is not more than forty miles from any place in Carlisle,
Ballard, Marshall or Livingston Counties. Mayfield itself (10,724)
and Murray (13,537) south of Marshall in Calloway County are secondary
urban centers. For the residents of Trigg County, Hopkinsville (21,250)
in neighboring Christian County is the nearest city and is readily
accessible over U.S. Highway 68 and several state highways.
-\
Except for Marshall County, the populations of these counties
are small and sparsely populated. Towns are very small and few in
number, the two largest being in Marshall County. In these five
counties, only the following six towns have over 1,000 residents,:
III-D-66
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5.2.1.
Trigg:
Marshall:
Ballard:
Carlisle:
LAND USE
Cadiz (1,987)
Benton (3,652)
Calvert City (2,104)
LaCenter (1,044)
Wickliffe (1,211)
Bardwell (1,049)
Approximately a third of Trigg County is covered by Lake Barkley
and the "Land Between the Lakes" Recreational Area. This is reflected
in the higher than usual (for this area of Kentucky) percentage of
land in forest, and the very high recreational land acreage for this
County. Marshall County as well has large acreages devoted to
recreational use, although in this case most of the acreage is water.
Table III-D-5
Ky-2 LAND USE
Trigg
Livingston
Marshall
Ballard
Carlisle
Farms
56.4
69.8
47.1
75.3
72.5
Forest [Total
49.0
39.6
35.4
26.8
25.5
117,077
408
57,082
28,052
2,259
RECREATION
Land
116,362
353
7,323
24,848
1,784
Water]
715
74
49,762
3,205
477
While discussing recreational acreages, however, the substantial acreage
in Ballard County should be noted as well. Possibly the lower percentages
of land devoted to farming in Trigg and Marshall Counties are a conse-
quence of this recreational development. In Trigg County it appears
that a large proportion of the land simply is not available for farming.
In Marshall County, it is likely that there has been a secondary
recreational development for private or commercial use. This is in
accord with population variation among the counties.
This area is outside the coal and oil producing regions of
Kentucky. There is one mine in Carlisle which produced 26,139 tons of
clay in 1973, as well as some quarrying of sand and gravel. Trigg
County produced $390,000 worth of stone, Ballard and Marshall, a very
small amount of sand and gravel. Livingston County, however, produced
$14,170,000 in stone, sand and gravel, and zinc. •
5.2.2. RECREATIONAL FACILITIES
The outdoor recreational facilities are very good |n this area,
even for Kentucky. The large lake enclosed "Land Between the Lakes"
area covers part of Trigg County and extends to Marshall County.
Three state parks are connected with this large recreational area.
Ballard County has the large Ballard Wild Life Management Area along
III-D-67
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the Ohio River. Nearby facilities include Pennyrile State Forest and
the Shawnee National Forest across the river in Illinois. One charac-
teristic of recreational possibilities in this area is the large
percentage of the water acreage available.
5.2.3. RESIDENCE
Except for Marshall County, these five counties are entirely
rural and sparsely populated. Since the population of Calvert City,
(the only community classified as urban by the U.S. Census) has less
than 4,000 people, the rural population of Marshall County must be
distributed less sparsely than in the other four counties.
Table III-D-6
Ky-2 DISTRIBUTION OF POPULATION
County Density % Urban % Rural non-Farm % Rural Farm
Trigg
Livingston
Marshall
Ballard
Carlisle
21
24
67
32
27
0
0
17
0
0
68
81
70
74
72
32
19
13
26
28
Marshall County exhibited substantial growth and in-migration
during the sixties, although Livingston grew as well, but at a slower rate.
Table III-D-7
Ky-2 POPULATION SHIFTS
1960-70 1970-4 1960-70 1970-4
Trigg
Livingston
Marshall
Ballard
Carlisle
-2.8
8.1
21.8
,-0.2
-4.5
5.4
10.7
7.3
.3
1.1
-11.4
4.2
13.4
.8
-4.3
4.6
10.3
5.7
.8
2.2
After 1970, growth continued at a lower level in Marshall County and
appears to have accelerated in Livingston County. After losing popu-
lation during the sixties, Trigg, Ballard and Carlisle have experienced
small growth, and, for Trigg and Carlisle, a reversal of migration
direction. Ballard appears to have the stable population in terms of
growth.
III-D-68
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In spite of the relative stability of Ballard County, it has a
higher percentage (72.3% native Kentuckians as opposed to 86.6, 84.3,
80.4 and 82.5 for Trigg, Livingston, Marshall and Carlisle respectively)
of the native population who were born in other states. These migrants
are predominantly from the North Central U.S., (14.3) probably
neighboring Illinois and Indiana, but there are also substantial
proportions from the south (9.5).
Judging from the stable population size, the fact that this county
had only a slightly lower percentage of the population (83.4) living
in Kentucky in 1965, and its extreme western location, Ballard is
part of a pattern of local residential movement which includes the
adjacent states. The difference between Ballard and Carlisle may be due
to the location of bridges across the river. The other three counties
are more likely part of a pattern of local mobility oriented slightlymore
toward other Kentucky counties. Of the five counties, Livingston
experienced the greatest level of inter-county mobility.
In general the residential mobility of the counties in this area
are about average for the ORBES region. Livingston and Ballard
Counties have somewhat higher percentages who lived in another state
in 1965 but this is reasonable considering their locations along the
river bordering the state.
5.2.4. AGE STRUCTURE
The age structures of the population in all five counties are
similar. Median ages are high:
Trigg 32.5
Livingston 32.1
Marshall 33.1
Ballard 36.5
Carlisle 37.5
Still there is a difference of over 3% between the median ages in the
three eastern and the two western counties. There is a sharp decline
in relative numbers of young adults in all counties. However, in
Marshall County the relative numbers in each age cohort are roughly
equivalent until the attrition in numbers due to old age sets in.
In the other counties there are relatively larger numbers in the middle
aged cohorts than in the young adult cohorts.
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5.2.5. MARITAL STRUCTURE
Consistent with the picture presented by the age structure,
percentages of widowed men and women in the two western counties,
Ballard and Carlisle are relatively high, and since the death rate is
higher among men, this leaves a relatively high percentage of families
with a female head. There are few divorced or single people in any of
the counties.
Generally the percentages of both men and women who are married
is high or relatively high. Marshall and Livingston Counties also
show high percentages of intact families pointing to relatively stable
marriages. Marriage may not be less stable in the other three counties
but owing to the larger percentages of the widowed in the western
counties and the relatively larger numbers of single men and few
married men and women, husband-wife families are less prevalent.
5.2.6. EDUCATION
These counties are characteristic of Kentucky with low levels of
educational attainment. Ballard and Marshall Counties show the highest
median school years completed at that is less than 11.0. No county has
even 40% of the population who have finished high school. Percentages
having completed college are lower than 5%.
5.2.7. HOUSING
Marshall and Livingston Counties have the largest percentages of
new housing units and households since 1960.
Table III-D-8
Ky-2 HOUSING, 1970
Trigg Livingston Marshall Ballard Carlisle
Change 1960-70:
Households
Housing units
Average:
House value
Rent
%Built since 1960
%0wner occupied
%Lack some plumbing
4.6
7.3
$8,582
63
33.0
69.7
28.8
19.5
22.2
$8,238
60
29.6
80.5
27.6
31.6
26.3
$11,673
69
33.9
84.2
13.2
8.5
2.5
$7,217
71
24.2
80.0
14.7
2.5
2.2
$7,171
65
23.1
79.2
18.9
This is consistent with the rate that new units are being built and
the population increase discussed earlier. The other counties are
building new units at a moderate to high rate but this does not appear
to reflect the changing needs for more housing. Between 13% (Marshall)
and 29% (Trigg) of the housing units in these counties lack some.plumbing
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and only in Trigg County are over 10% of the units crowded. Over
85% of the housing is in one unit structures, is predominantly owner-
occupied, and is relatively low in value. It should be noted, however,
that Marshall County with the highest percentage of home owners, has
the highest median house value.
5.2.8. ECONOMIC ACTIVITIES
Marshall County, which has the smallest percentage of its popu-
lation living on farms (13%) and the smallest percentage of land
devoted to farming (47%), has the least productive farming among the
five counties. This may be a function of size. This low profitability
Table III-D-8
Ky-2 FARMING, 1969
Trigg Livingston Marshall
Ballard
Carlisle
Change 1964-69:
Farms 9.8
Acreage 2.0
Average:
Land value $212
Return per acre 44
Class I-V Farms:
Number 418
Avg. acres 276
Avg. return $14,497
Other Farms:
Number 300
Avg. acres 106
Avg. return $1,170
-3.2
-6.0
$147
29
299
342
$12,226
297
124
$1,019
-15.0
- 9.8
$236
29
$7
285
155
,133
632
74
$920
-5.8
- .7
$257
57
484
214
$13,866
364
59
$1,163
-4.9
-4.6
$215
50
344
212
$12,306
281
62
$1,157
may be reflected in the very low ratio of potentially full-time farming
operations (Class I-V farms) to other types of farms, as well as the
higher percentage losses in farm numbers and acreage between 1964 and 1969.
Although the farming in Trigg County does not, from these data, appear
qualitatively different nor does the return appear substantially higher,
Trigg and several nearby counties have experienced gains in the numbers
of farms and gains or very small losses in the farm acreage between
1964 and 1969. Also fewer than average numbers of farmers work off the
farm.
Livestock raising as a primary operation is the most important
type of farming. Tobacco (Trigg and Ballard) and dairy farming (Carlisle)
are second in importance.
III-D-71
-------
Both Marshall and Trigg Counties have substantial percentages of
manufacturing jobs covered in County Business Patterns although only
Marshall County is a focus for in-commuting workers. The difference
appears to be in numbers. Marshall has almost four times the number
of jobs, and less than three times the population of Trigg County.
Ky-2
Table III-D-9
COUNTY BUSINESS PATTERNS, 1973
Trigg Livingston Marshall Ballard Carlisle
Population
Jobs in CBP
Mining
Construction
Manufacturing
Transportation
Trade
Finance
Services
8,620
1,419
142
654
36
279
48
245
7,596
796
160
51
62
247
103
153
20,381
5,221
591
3,062
199
753
178
361
8,276
1,358
219
253
42
54
5,354
1,333
13
6
142
26
53
The most important industry in these counties is the chemical
industry in Marshall County employing over 2,000 persons. The next
most important are the primary metal industry, also in Marshall County,
and the paper industry in Ballard County, each employing between 500
and 999 persons. All the other manufacturing industries employ less
than 500 persons. Marshall also produces furniture or fixtures. Trigg
County has fabricated metal, apparel and machinery industries. Carlisle
produces electrical equipment.
The numbers employed in finance or in services in Livingston
County is surprsing considering the fact that this county has no
communities of 1,000 or more. The numbers employed in Ballard County
in construction are also noticeable. Livingston, as is consistent with
the value of mineral production, is the only county with significant
numbers of jobs listed in mining. However, Carlisle's clay mine may
employ significant numbers also because there are over 1,000 jobs
unaccounted for in this county and most of them must be in mining or
manufacturing. Similar gaps in the data for Ballard County are more
likely to reflect the presence of one large employer, the paper
industry mentioned above.
Examination of the composition of the labor force in 1970 adfts
little to the picture. High percentages of foremen and craftsmen in
the labor force in Marshall and Ballard Counties are probably related
to the relatively high numbers of jobs in manufacturing (Marshall) and
construction (Ballard) in these counties. Considering the highly rural
nature of Livingston County, it is not surprising that few women (29.8)
are counted in the labor force.
III-D-72
-------
5.2.9. INCOME
For the ORBES region, per capita and median family incomes are
close to average, and the median family incomes for total and farm
population do not differ greatly. This middling position within the
ORBES region does not appear to have changed by 1974.
Table III-D-10
Ky-2 INCOME
1969
Median
family
1969
Median
farm family
1969
Per. Cap.
1973
Per. Cap.
1974
Median
Family EBI
Trigg
Livingston
Marshall
Ballard
Carlisle
5.2.10.
5,761 4,875
6,164 7,143
7,305 7,593
7,000 8,109
5,839 5,943
IMPACT ASSESSMENT
3,210
3,497
3,350
3,590
3,815
3,720
4,202
3,644
3,936
4,405
8,244
8,627
099
540
9,
9,
6,856
These five Kentucky counties, which are in close geographical
proximity, Trigg, Livingston, Marshall, Ballard and Carlisle, differ
somewhat in their basic environmental orientations in spite of relative
homogeneity of the population itself in terms of age structure,
educational attainment and income. Trigg and Marshall may be classified
as having an aesthetic (symbolic) sub-orientation primarily because of
the large recreational aspect. The possibility for conflict between
the economic benefit and the aesthetic sub-orientations exist in
Marshall because it is also the most urban, the most affluent, more
industrialized and has the most commuting workers. In short, it seems
ripe for further industrial development such as a power plant site
and associated industrial development. Furthermore, given the nature
of the population, it seems likely that Marshall County would be open
and receptive to a power plant.
Because the prevailing orientation in Trigg County is aesthetic, we
would expect considerable opposition to power plant siting there. It
is questionable though whether the county has the resources to be
effective in opposition efforts.
Livingston County also with its recent population growth and high
inter-county mobility might also be receptive to power plant develop-
ment, however, given its rural nature, it would also be -innundated by
the construction phase boom and experience negative impacts becaus.e of
the lack of an effective economic infrastructure to deal with demands
of migrant workers for services, housing and amenities.
III-D-7.X
-------
Ballard County with its aesthetic sub-orientation seems an unlikely
candidate for power-plant development because it also is an area of
generally older people and contains the most valuable farmland and the
highest incomes. In short, it seems to be prospering at its own pace
and the people there probably do have a fairly high sentimental
attachment to place as well. In other words, we would predict
opposition to a plant in this county. The only mitigating factors are
the mixed origins of the population, with quite a few being from other
states, however, we think many of these in-migrants to be retirees,
and probably unsympathetic to development. However, should a plant
be sited there, many workers could commute from nearby cities and
mitigate any boomtown impacts.
Carlisle, being isolated, rural farm in nature and with an older
population of limited education and income, while possibly being
receptive to development, would probably experience an intense boom-
bust phase should a plant be located there with its attendant disa-
mem'ties.
III-D-74
-------
5.3. HENDERSON (36,031), UNION (15,882), WEBSTER (13,282), MCLEAN (9,062)
AND BUTLER (9,723) COUNTIES
In Eastern Kentucky, just south of the place where the Wabash
runs into the Ohio River and the states of Kentucky, Indiana and Illi-
nois meet, are five counties subject to the impact of potential power
plant development. Two counties, Henderson and Union, are on the Ohio
River. Webster County, adjacent to both of the above counties, is
bordered on the west by the Tradewater River and on the east by the
Pond River. Adjacent McLean County also has the Pond River as its western
border. The Green River cuts across this county and merges with the
Pond River. To the southeast the Green River also crosses Butler County,
the fifth county likely to be directly affected by power plant develop-
ment.
At the present time there are power generating facilities in both
Henderson and Webster Counties. Henderson has both a small hydro-elec-
tric (170 megawatts) and a small coal-fired (52.5 megawatts) plant.
Webster has two plants also, both located at Sebree. There is a 350
megawatt coal-fired municipally owned plant. In addition, the Big Rivers
Rural Electric Cooperative has a coal-fired unit (80 megawatts) in
operation, a 60 megawatt unit under construction, and three units (65,
200, and 200 megawatts respectively) planned for operation in 1976, 1979
and 1984. An additional facility planned for Henderson County is a
coal conversion plant at Baskett, just east of Henderson on U. S. High-
way 60.
No plants would be located in this area in the low energy
scenarios.
For each of the high energy scenarios, a two-unit (2,000 megawatt)
coal-fired plant would be placed in both Union and Webster Counties. In
Scenario I, a single unit (1,000 megawatt) coal-fired plant would be
built in both McLean and Butler Counties as well. This area would have
no nuclear plants.
Three, or possibly four urban areas would likely be of importance
to the residents of these counties. Henderson (22,976), though not the
largest city, is on the Ohio River just ten miles south of Evansville,
Indiana (138,764) where major highways converge from all directions.
Most residents, at least in the eastern halves of Union and Webster
Counties and in the western part of McLean County, should find the
city less than thirty miles away. Some of those in McLean County
might find Owensboro. (50,329;), in Daviess County, a bit closer. Like-
wise those living in southern or western Webster County might prefer
to go to Madisonville (15,332), in Hopkins County, for some shopping,
services and urban amenities. Bowling Green (36,253), in Warren County,
would be the closest urban center for those in Butler County. This area
is generally well serviced by highways connecting these centers and
crossing the area to more distant parts of the state.
III-D-75
-------
Outside of the city of Henderson, there are only eight communities
with populations over 1000 in these five counties and four of them have
less than 2000 residents.
Table III-D-11
KY-3 POPULATION CENTERS
Density Population
Henderson County 83 per sq. mile 36,031
Henderson 22,976
Union County 47 per sq. mile 15,882
Morganfield 3,563
Sturgis 2,210
Uniontown 1,255
Webster County 39 per sq. mile 13,282
Providence 4,270
Clay 1,426
Sebree 1,092
McLean County 35 per sq. mile 9,062
Livermore 1,594
Butler County 22 per sq. mile 9,723
Morgantown 1,394
Looking at portions of the population concentrated in the urban
areas and the relative sizes of the counties and populations, it can
reasonably be suggested that the populations of these five counties
are similar in the sparseness of their distribution outside the urban
areas.
5.3.1. LAND USE
These five counties all lie in the,western coal-producing region of
Kentucky. Union County had the most substantial coal production in 1973
and 1974, as well as the largest production of oil. There is a small
amount of quarrying of stone in Butler and sand and gravel in Henderson
and Union Counties.
III-D-76
-------
TABLE III-D-12
KY-3 MINERAL PRODUCTION, 1973
Coal Oil
No. of Mines Tonnage Barrels
Henderson 2 524,175 1,043,932
Union 6 7,086,571 1,291,987
Webster 3 1,842,961 605,633
McLean 5 1,309,335 480,670
Butler 7 • 74,394 47,840
We do not have reliable figures on the amount of land which is
affected by mining operations.
Only in Butler County is there a substantial proportion of the
land in forest. Conversely, Butler has the lowest (although not low
for the region) percentage of its land devoted to farming.
TABLE III-D-13
KY-3 LAND USE
Henderson
Union
Webster
McLean
Butler
FOREST %
1975
19.6
15.6
27.2
25.2
52.1
FARM LAND %
1969
86.3
90.2
72.5
80.2
61.6
RECREATIONAL
ACREAGE
1975
4,546
6,363
547
307
855
Union and Henderson both have sizeable acreages devoted to outdoor
recreational facilities. The other three counties have less than 1,000
acres each devoted to outdoor recreation.
5. 3.2. RECREATIONAL AND CULTURAL AMENITIES
One major park, the John J. Audubon Park, is located in Henderson
County, but as in most of Kentucky, outdoor recreational facilities
are readily accessible to most residents. The Land Between the Lakes,
Pennyrile Forest State Park, Mammoth Cave National Park, Rough River
Dam, and the Shawnee National Forest in Illinois provide some of the
major possibilities for residents of these counties.
The possibilities for urban amusements and activities are in
varying degrees available in the urban centers, especially Evansville,
Indiana which has the only museums listed by the American Association
of Museums near this area.
III-D-77
-------
Baptists churches have the largest membership in all these counties
In all except Union County, they comprise over 50% of all church member-
ship.
5.3.3. RESIDENCE
The farm population is relatively small in the three northwestern
counties of Union, Webster, and Henderson Counties and comprises
slightly over one-fourth of the population in McLean (28%) and Butler
(29%) Counties.
This portion of the population, as in the ORBES region in general,
decreased disproportionately, as can be seen in the following percentage
changes in farm population for 1960 through 1970:
Henderson -49.0
Union -17.2
Webster -41.2
McLean -20.4
Butler -39.2
If you ignore Henderson (the city), the largest sector in each county is
the rural non-farm population.
Table III-D-14
KY-3 DISTRIBUTION OF POPULATION
Percent Percent Percent
Urban Rural Non-farm Farm
Henderson 64 29 1
Union 22 62 15
Webster 33 53 14
McLean 0 72 28
Butler 0 71 29
McLean and Webster experienced both population decline and out-
migration in the sixties while Henderson continued to grow even though
experiencing a low level of out-migration.
Since 1970 all five counties have had a slow growth in population
and negligible or small in-migration. Webster and McLean, which had
the highest rate of out-migration in the sixties now have the highest
level of in-migration.
III-D-7'8
-------
Table III-D-15
KY-.3 POPULATION SHIFTS
Population Change Net Migration
1960-70 1970-74 1960-70 1970-74
Henderson
Union
Webster
McLean
Butler
7.5
9.3
-6.7
-3.1
1.4
2.1
2.2
5.5
6.6
5.2
-2.9
2.1
-8.6
-9.7
.8
-0.8
0.5
5.7
5.7
4.0
The two border counties with their higher populations have larger
percentages of people born in other states, mostly the North Central
States, probably neighboring Indiana and Illinois. When looking at
residence in 1965,
Table III-D-16
KY-3 RESIDENTIAL STABILITY
Residing in:
n
Birth State County 1965 Ky. 1965
Henderson
Union
Webster
McLean
Butler
80.0
77.9
87.5
87.3
89.4
84.0
71.8
81.4
80.9
86.1
88.8
79.3
89.8
89.3
90.9
it is clear that Union has a much more mobile population than any of the
other counties. Butler County on the other hand is the most stable of
the five.
5.3.4. AGE STRUCTURE
The very low median age of the Union County population (23.8) re-
flects the very high population of males, age 15-19 (2,290). This one
group of males forms almost 15% of the population. This must be an
institutional population since almost 2000 live in group quarters but
the nature of the institution has not been determined. Otherwise the
profile of the age structure is not greatly different from those of
the other four (-counties.
Median age in the other four counties range from 29.1 (Henderson)
to 35.9 (Webster). There are relatively few children, a decline in the
relative numbers of young adults (especially sharp in Webster County),
III-D-79
-------
and relatively larger numbers of the middle aged and older. The curve
for Webster County is interesting in that there are roughly equal numbers
in each cohort between 20 and 55 with a sharp drop between children and
adult cohorts and a small increase in numbers after age 55.
5.3.5. MARITAL STRUCTURE
If you attempt to eliminate the effect of the unusually large number
of teenage males in the Union County population, there is little dis-
tinction about the marital structure of this area. High percentages of
men and average or above average percentages of women are married. With
the high median age, one expects a relatively high percentage of widows
in Webster. Higher numbers of divorced women and families with a fe-
male head as well as fewer intact families would also be expected in
Henderson, the most urbanized county. In addition, the greater numbers
of young adults agrees well with the higher than average percentages of
families with children under 18 in Henderson County.
5.3.6. EDUCATION
In accordance with their younger median ages, both Union and
Henderson Counties have relatively high median levels of educational
attainment. This reflects the higher than average percentages of the
population who have completed high school. Percentages of the
population who have completed college are low, less than 6% in these
two counties, and less than 5% in Webster, McLean, and Butler Counties.
5.3.7. HOUSING
The changes in numbers of households and housing units between
1960 and 1970 are in accord with generally average percentages of new
units being built.
Table III-D-17
KY-3 HOUSING CHANGES, 1960-70
Households Housing Built since 1960
Units New Units
Henderson 13.8 10.6 21.0
Union 5.1 8.6 17.1
Webster -1.1 -0.3 13.8
McLean 6.7 8.8 23.8
Butler 13.4 ' 13.8 24.6
It should be noted that those counties with declining population and
increasing households, must contain smaller households, or greater
numbers of single person households.
III-D-80
-------
Except for Henderson County, housing is overwhelmingly in one unit
structures, it often lacks plumbing, house values and rents are low.
Henderson County with its large urbanized area has fewer home-owners,
higher rents and house values, and fewer units lacking some plumbing.
Table III-D-18
KY-3 HOUSING CHARACTERISTICS, 1970
Lack some
Plumbing
Owners
Median
House Value
Median
Rent
Henderson
Union
Webster
McLean
Butler
11
18.
24.
21.0
47.1
,1
.9
.4
66
71
76
78
76
11,631
6,995:
5,663
8,350
5,456
79
84
55
66
54
5.3.8 ECONOMIC ACTIVITIES
Farming appears to be a profitable economic activity in Union
County where farms are large and return per acre, though not high for
the ORBES region, is high for Kentucky.
TABLE III-D-19
fKY-3 FARMING,1969
Henderson
Return per acre $ 60
Value per acre 320
Chg. acres 1964-69 -1.0
Chg. farms 1964-69 -5.5
Farms, I-V No. 735
Ave. size 301
Ave. ret. $18,835
Farms, Other No. 338
Ave. acres 54
Ave. ret. $1,190
Union
$ 83
300
13.9
8.5
480
389
$33,737
136
71
$1,267
Webster
$ 43
202
6.0
6.6
471
268
$13,647
390
79
$930
McLean
$ 46
229
3.1
-1.0
512
223
$10,966
351
51
$1,140
Butler
$ 21
128
15.7
10.3
380
271
$7,975
627
114
$919
Class I-V Farm Types
Livestock 408
Cash-grain 261
'Tobacco 10
Dairy
355
111
2
4
252
156
7
6
157
199
44
13
242
40
14
32
III-D-81
-------
Henderson County farmers, although not as well off as those in Union County,
can produce a return which makes farming a viable economic activity.
It is clear from the figures for these counties that changes in
numbers of farms and farm acreage do not provide indicators of relative
profitability. (See Henderson, Union, and Butler county figures).
"\
Clearly livestock and cash-grain crops are the primary agricultural
products^with a little tobacco raising and milk production in McLean and
Butler Counties.
None of these counties have any significant amount of manufacturing
activity as measured by the 1972 value added by manufacturing. However,
Butler County job opportunities are predominantly in manufacturing (68%)
and a relatively high percentage of the labor force in Henderson County
work in manufacturing.
Because of restrictions on publication of data, the number of miners
employed in mining in Union County is not listed. However, recalling
the large coal production, the Department of Mines and Minerals figures
for 1973 were checked for number of employees. In 1973 mining provided
employment for 1618 men. This figure is consistent with the figures
listed in County Business Patterns. If we assume that the numbers were
similar in 1972, mining is the most important economic activity in
Union County (over 40%).
Except for Butler and Union Counties, a fairly low level of mixed
job opportunities are available. Union County is the only one of the
five counties in which substantial proportions of the population does
not commute out for work.
Table III-D-20
KY-3 COUNTY BUSINESS PATTERNS, 1973
Henderson Union Webster McLean Butler
Total Population
in CBP
Agriculture
Mining
Construction
Manufacturing
Transportation
Trade
Finance
Services
36,031
9,301
27
276
895
3,184
406
2,543
270
1,664
15,823
3,920
-
-
-
531
52
607
102
978
13,282
1,307
-
-
73
71
124
353
62
134
9,062
882
-
—
15
306
236
52
97
9,723
1,333
-
24
28
910
28
189
48
106
By 1975 the only industry employing over 500 persons was a primary
metals industry in Henderson County. A rubber and plastics industry,
also in Henderson County, had employed 665 persons in 1972 but that
number had declined to less than 500 by 1974.
III-D-82
-------
Other smaller industries (employing less than 500) are listed in
the county figures for at least some of the time between 1972 and 1975.
Henderson County had industries producing: 1) furniture, 2) lumber
products, 3) textile products, 4) apparel, 5) transportation equip-
ment, and 6) chemical products. Butler County had industries producing
1) lumber products, and 2) apparel and textile products. Webster
County produced: 1) primary metals and 2) apparel. Union County
produced: 1) apparel, 2) textiles and 3) fabricated metal. McLean
County had industries producing: 1) furniture and 2) primary metals.
Examination of the occupational distribution of the work force in
1970 calls for two additional observations. The four counties closest
to the river are part of an area with high concentration of craftsmen
and foremen in the work force. This area extends from the convergence
of the Ohio and Mississippi Rivers north along the Ohio and Wabash
Rivers and is centered in southwestern Indiana. The concentration then
thins out but still comprises a substantial portion of the work force
across eastern Indiana and all of Ohio.
A second observation is that the percentage of the civilian labor
force working in construction in 1970 in Butler County was relatively
high but there were few jobs in construction in the 1973 County Business
Patterns. It appears that a construction project might have been taking
place in Edmonson County but the direction of commuting does not bear
this out. Perhaps the gross measures obscure the real situation. If
not, this anomaly cannot be explained.
5.3.9. INCOME
Per capita and median family incomes range from moderate to low
with the highest incomes in Union and Henderson, and the lowest in
Butler. Income for farm families is generally on a par with the median
family income except for Union County where the productive agriculture
provides farming families with the highest median income in the state.
The relative positions of the counties remain in 1973. The 1974 figures
on effective buying power indicate that Butler County has unusually large
percentages of the poor, even for Kentucky.
TABLE III-D-21
Ky-3 INCOME
1969
per.
capita
1969
medium
family
1969
farm
families
1973
per
capita
1974
medium
family EBI
Henderson 2,431 . 7,833' 7,402 4,517 10,416
Union 2,117 8,120 10,089 4,622 9,672
Webster 2,069 6,003 5,992 3,829 7,106
McLean 2,116 6,218 6,371 3,423 8,841
Butler 1,572 4,772 4,795 2,390 4,597
III-D-83
-------
5.3.10. IMPACT ASSESSMENT
These five Kentucky counties slated for possible power plant siting,
Webster, Henderson, Union, McLean and Butler, are physically close to
one another but differ greatly in what their basic environmental orien-
tations would seem to be. Henderson and Union, the most affluent and
urbanized counties, seem to have a primarily instrumental orientation,
which would generally make them receptive to power plant development
and likely, also, to have an economic infrastructure to deal with
population growth. Henderson county would not be subject to a boom-
bust syndrome because of the availability of a skilled labor force
in nearby Evansville and in Henderson itself. Union county, on the
other hand, is likely to experience a boom-bust cycle from the con-
struction phase in one or two of its small cities, depending on where
the plant is located.
Webster and McLean Counties, and particularly the former, are likely
to be highly sentimental in their environmental orientation and some-
what resistant to power plant development because of relative stability,
elderliness and rurality of the population. It is doubtful whether
effective opposition to a plant could be brought about should the
residents be opposed to power plant development given the low educational
and occupational levels that characterize these counties.
Butler County seems to -have a primordial belongingness environmental
sub-orientation. It also seems to have an aesthetic sub-orientation
considering the proportion of the land which is forested. The high
proportion of the poor and lack of economic diversification suggest poor
adaptation to a boomtown syndrome that would be likely in this isolated
county. We also would expect the population to be opposed to development.
III-D-84
-------
5.4. MEADE, (18,796) AND BRECKENRIDGE, (14,789) COUNTIES
Meade and Breckenridge Counties on the Ohio River southwest of
Louisville are the proposed sites of coal-fired plants for both of
the high energy scenarios. A two-unit, 2,000 megawatt plant would be
placed in each county in both scenario one and two. Neither county
has any current power generating facilities.
U.S. Highway 60 between Louisville and Owensboro (a distance of
109 miles) crosses both Meade and Breckenridge Counties making either
of the above cities readily accessible to many of the residents of
these counties. Those who live close to the river, where a plant is
likely to be sited, would have to travel over side roads to reach the
major highway. Elizabethtown in nearby Hardin County is readily
accessible to some of the residents by state roads or U.S. Bypass 31W
as well.
Table III-D-22
Ky-4 COMMUNITIES OVER 1,000
Meade Breckenridge
Vine Grove (2,987) Hardinsburg (1,547)
Muldraugh (1,773) Cloverport (1,388)
Brandenburg (1,637) Irvington (1,300)
Both counties have three town each, only one of which has over
2,000 inhabitants. Only Cloverport and Bradenburg are located on the
river.
5.4.1. LAND USE
Both counties have just under half the land in forest (Meade 43%,
Breckenridge 49%) but Breckenridge has a substantially larger propor-
tion of land devoted to farming (Meade 68%, Breckenridge 88%). Approxi-
mately 2% of the land is in urban use. Part of Meade County on the
Hardin County line is a large army base, Fort Knox. Both have sub-
stantial amounts of recreational land.
Table III-D-23
Ky-4 RECREATIONAL LAND USE
Meade Breckenridge
Total acres 6,346 8,143
Land 5,940 2,982
Water 408 5,139
There is no coal production in these counties but in 1972 and
1973 Breckenridge produced 17,848 and 13,285 barrels of oil respectively.
III-D-85
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5.4.2. RECREATIONAL FACILITIES
As can be seen in the land use figures above, outdoor recreational
facilities are available for most residents. Otter Creek Park is in
Meade County and in addition, there are several state recreational
facilities in nearby counties: Bernheim Forest, Knobs State Park,
Mammoth Cave National Park, Nolin River Lake, and Rough River Lake
and Dam. Directly across the Ohio River is the Hoosier National
Forest in Indiana.
5.4.3. RESIDENCE
On the border between Meade and Hardin Counties is a large army
base, Fort Knox. Since a third of the workforce is non-civilian in
Meade County, the assumption has been made that the extremely anomalous
profile of this county presented by demographic measures used in this
report are due to the presence of this base. Until we discuss eco-
nomic activity, it is impossible to separate the population attached
to military base from the remainder of the population. For this
reason, this section will profile Breckenridge County and assume that
the civilian population of neighboring Meade County does not differ
greatly.
This is a sparsely populated (27 per square mile) rural county
with 37% of the population living on farms. There has been very slow
population growth (.4%) increasing slightly since 1970 (4.3%). Like
much of Kentucky, the out-migration of the sixties (-7.1) has stopped
and there is net in-migration since 1970 of 3.2%. Whether this reversal
has meant a slowdown in the decrease of the farm population (-30.8)
is undetermined. Of the native population, 92% were born in Kentucky
and most of the few out-of-state residents probably came from
neighboring Indiana.
The population is very stable in residence, 93% having lived in
Kentucky in 1965, 88% in Breckenridge County.
5.4.4. AGE STRUCTURE
Median age in Breckenridge County is 30.5. The age profile
illustrates the predominance of older middle-aged and the elderly in
the adult population. The largest single adult cohort is that for
ages 55 through 59.
5.4.5. MARITAL STRUCTURE
This relatively young population is for the most part married with
few, especially women, who remain single. There is a somewhat higher
than average percentage of widowed men but little significance is seen
III-D-86
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in this. Since most women appear to marry, and divorce does not seem
to be particularly frequent, the percentage of families with a female
head is somewhat lower than usual.
5.4.6. EDUCATION
Educational levels are low with less than 30% of the population
having finished high school and only 2% having finished college.
5.4.7. HOUSING
In spite of the out-migration and low population growth of the
sixties, there have been substantial gains in numbers of households
(9.3) and housing units (10.7). The housing is predominantly in one-
unit structures (85%) and over 27% have been built since 1960. Housing
values ($5,126) and rents ($42) are relatively low and relatively high
percentages lack some plumbing (33%). Slightly over three-fourths are
owner occupied, a relatively high percentage for Kentucky.
5.4.8. ECONOMIC ACTIVITIES
As in so much of Kentucky, raising livestock and tobacco are the
major farming operations. Although farming appears to be only marginally
profitable, average return per acre is only $35. Breckenridge County
is one of a cluster of counties exhibiting gains in both numbers of
farms (8.5) and farm acreage (.3) during the late 1960's. Meade also
exhibited an increase'in the number of farms (8.5) although farm acreage
was reduced (-4.3). Since the population remained almost the same
during this period, farms must be breaking up to some extent. Price
of farm land is low in these counties. Perhaps that is related to
these trends.
Table III-D-24
Ky-4 FARMING, 1969
Meade Breckenridge
Average:
Land value $198 $151
Return per acre 42 35
Class I-V Farms:
Number 462 1,045
Average return $10,730 $9,385
Average acres 199 236
Other Farms:
Number 509 783
Average return $1,152 $1,194
Average acres 79 81
III-D-87
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The size of the civilian work force covered in County Business
Patterns is about equal in both counties and distribution among the
various job categories is similar. The category with the largest
numbers is "trade". Although numbers are withheld, indications are
that Meade County has a significant proportion of jobs in manufacturing.
Over 600 jobs are unaccounted for and since few are likely to be in
agriculture, construction or transportation, they are probably in one
or a few large manufacturing firms. The 1972 Census of Manufacturing
supports this suggestion by listing one chemical industry which
employs between 500 and 999 people.
Table III-D-25
Ky-4 COUNTY BUSINESS PATTERNS, 1973
Meade Breckenridge
Total employed 1,285 1,194
Construction 32 41
Manufacturing - 226
Transportation - 68
Trade 331 424
Finance 130 96
Services 143 303
Breckenridge County has small industries employing between 100 and 499
people in: 1) apparel and textiles, and 2) stone, clay, glass and
concrete. One striking difference is the numbers employed in services,
more than twice as many in Breckenridge County which also has the
smaller population. Of course it is possible that the military services
provide many services for the base attached residents of Meade County.
Substantial numbers in both counties commute out for work.
5.4.9. INCOME
Per capita and median family incomes are below average for Brecken-
ridge ($1,972 and $6,316) and average for Meade County ($2,273 and
$7,803). The surprising feature of income distribution is the rela-
tively high median family income for farm families in Meade County
($9,095 as opposed to $5,968 for Breckenridge). Since there is only a
small difference in average return per farm, it must be suggested that
many farm families have a member working elsewhere. A relatively high
percentage (56.1) of farmers work off the farm at least 100 days a
year and 322 of the 509 "other farms" are classified as part-time.
III-D-88
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Fort Knox with a population of over 37,000 (almost half the population
of the county) is across the county line in Hardin County which also
contains Elizabethtown (11,748). These two communities contain 63%
of the population of Hardin County, one of the larger Kentucky counties.
Since Hardin County draws commuters for work, the location of Fort
Knox would argue for the disproportionate drawing of workers from
Meade County. If so, why this would affect farm families more than
non-farm families would be interesting to know.
Relatively, per capita incomes appear to have reversed by 1973
(Meade $2,900, Breckenridge $3,445) but there is not enough information
to say more.
5.4.10. IMPACT ASSESSMENT
The predominant orientation of Meade and Breckenridge Counties is
clearly sentimental and symbolic given the farming and recreational use
of the land and its stable, older and poor residents. Meade County's
previous experience with Fort Knox and mobile populations suggests a
somewhat easier possible adjustment to power plant siting, however,
neither of these counties has the infrastructure to deal with a
construction boom. The nearness to rather large cities suggests the
likelihood of a commuting labor force by and large, and in that sense,
minimum impact of that phase. On the other hand, the nature of the
indigenous population, especially in Breckenridge County, suggests there
may be quite a bit of resistence to a power plant project.
III-D-89 '
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5.5. SCOTT COUNTY (17,948)
Scott County is the site of a planned low BTU coal conversion
plant. At present there are no power generating facilities in that
county.
Located in Central Kentucky just north of Fayette County, the
center of the Lexington SMSA, by 1974 Scott County was included in the
SMSA. The major town in Scott County is Georgetown (8,629). All other
residents live in places of less than 1,000. However, several cities
are nearby. Lexington (108,137) is 17 miles south by 1-75 or U.S.
Highway 25. Frankfort (21,356), the state capitol, is 18 miles west
on U. S. Highway 460 and 64. In addition, Cincinnati is just an hour's
drive away by 175 which passes Georgetown.
5.5.1. LAND USE
Only a relatively small percentage of the land in Scott County
is forested (17%). It is for the most part rolling farm land (95%).
There is no mining or quarrying in Scott County and only a negligible
portion of the land (872 acres) is in recreational use, so the balance
must be devoted to urban or rural residential use. According to The
River Basin Water Quality Management Plan, about 3% of the land is
devoted to urban use.
5.5.2. RECREATIONAL AND CULTURAL AMENITIES
The recreational, cultural and educational facilities of nearby
metropolitan areas are readily accessible to residents of Scott County.
In addition, Scott County has a small college, Georgetown College.
Central location and closeness to Lexington with the many highways
which converge at this point means that many outdoor recreational
facilities are available as well. Kentucky has an extensive system of
state parks and within two hours one may reach a number of them as
well as the Daniel Boone State Forest in Eastern Kentucky.
Residents of Scott County, as is the pattern in Kentucky, are
predominantly Protestant and Baptist.
5.5.3. RESIDENCE
At least in 1970, population density in Scott County was rela-
tively low (63 per square mile) and was predominantly rural with 20%
of the population living on farms. During the 1960's the population
of the county had been growing (16.8) both through natural increase
and in-migration (6.0) although this was mainly due to the growth
of Georgetown (23.5) and the rural non-farm population since farm
population had been decreasing (-23.1). The total rural population
had experienced a growth of 11.1% so the increases in the non-farm
sector must have been large to offset such losses in farm population.
III-D-90
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After 1970 these population shifts seem to have leveled off.
Population increased but at a much lower level (2.5) and migration
has been estimated at (-)0.5.
The residents of this county are somewhat more mobile than
the average for the region. Only 73% lived in Scott County in 1965
although 87% lived in Kentucky. Most of the residents are native
Kentuckians (85%) with most of the balance of native Americans born
either in the South or in the North Central states.
5.5.4. AGE STRUCTURE
The age structure is characterized by a slightly higher than
average percentage of young adults and slightly lower than average
percentage of middle-aged adults which is reflected in the somewhat
lower than average median age (26.3).
5.5.5. MARITAL STRUCTURE
As would be expected in the fairly young and mobile population,
there are fewer than average widows and more than average numbers of
divorced women in the population. The general tendency for larger
proportions of men to marry and to remarry are reflected in the higher
percentages of married, and the lower percentages of divorced and
widowed men in contrast to women in the same categories.
5.5.6. EDUCATION
Educational levels are higher than usual for Kentucky but are not
high relative to the region. Median school years completed is less
than 11.0 and 8.6% of the population have completed college although
only slightly more than half have finished high school. Considering
the location of Georgetown College with over 1,000 students and the
faculty to service the college, all of whom have at least a high
school diploma, in a county with less than 18,000 residents, the
educational levels of the general population must be lower than above
percentages suggest.
5.5.7. HOUSING
Central Kentucky, in general, is characterized by low levels
of home ownership. In Scott County only 62% of the housing is owned
by the occupant, although 77% is in one-unit structures. The increase
in number of households (20.7) and housing units (23.0) has been sub-
stantial and is in accord with the percentage of housing units built
since 1960 (25%).
Values of housing are characteristic of fringes of urban areas
in the region, lower than those at the urban center but somewhat higher
than surrounding rural areas. Median value of owner-occupied housing
III-D-91
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units is $14,464 and rent is $83. For Kentucky, the proportion of
housing units lacking some plumbing facilities is lower than average
(20%).
5.5.8. ECONOMIC ACTIVITY
In spite of the relatively high value of farm land ($488) and the
moderate average return from farming per acre ($66) and per Class I-V
farm ($13,858), the number of farms and farm acreage grew slightly
between 1964 and 1969 (3.8% and 4.4% respectively). However, during
the 1960's farm population declined sharply as mentioned earlier. It
is difficult to explain this unless the nature of farming is changing.
From census figures, farming appears similar to that in neighboring
Fayette County except that it is less profitable in Scott County.
Table III-D-26
KY-5 FARMING, 1969
Scott Fayette
Class I-V farms:
Number 798 698
Average acres , 198 212
Average return $13,858 $29,526
Other farms:
Number 356 431
Average acres 43 33
Average return 1,220 1,666
Farm types:
Tobacco 567 . 396
Livestock 168 153
General 36 38
County Agricultural returns:
Total $11,493,093 $21,327,271
Fayette County is the center of a horse farming area with sizeable
cattle production as well. The labor intensive nature of this type
of farming operation entails the on-farm residence of some of the
farm workers as well as the farm operator. If a similar pattern has
prevailed in Scott County, it is conceivable that the lower returns
on farming or some other factors have led to a reduction in the resi-
dent farm labor force, hence reducing the farm population without
forcing either farm consolidation or breakup. This, of course is
speculation, but it points out the necessity of further examination of
the experiences of the farm population (in this case a sizeable 20%)
if we wish to be able to gauge their possible reactions to industrial
development in their county.
According to County Business Patterns, the primary non-agricul-
tural activity in Scott County is manufacturing. Major industrial
III-D-92'
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Table III-D-27
KY-5 COUNTY BUSINESS PATTERNS, 1973
Scott
Total Population 17,948
In CBP 3,817
Manufacturing 1,979
Trade 702
Services 681
Construction 180
Finance 127
Transportation 80
employers are: 1) fabricated metal products (employing 617) and
2) non-electric machinery (employing 451). There are also plants
employing between 100 and 499 persons for the manufacture of:
3) electrical equipment, 4) instruments and related products, 5) furni-
ture and fixtures, 6) rubber and plastic products, and 7) office and
art supplies.
Scott County has a substantial proportion of residents who
commute out of the county, mostly to nearby Fayette County.
One notable characteristic of Scott County is the relatively
high percentage of women in the work force and the similarly high
numbers of these who must be working wives. This pattern is character-
istic of Central Kentucky and often of urban, more affluent areas.
5.5.9. INCOME
Per capita and median family incomes are lower than those in the
prosperous Central Kentucky counties to the south, although still higher
than in much of Kentucky. In 1969, per capita income was $2,401 and
median family income was $7,566. Surprisingly, median family income
for the farm population was slightly higher ($7,598). Relatively
speaking, income seems to have remained about the same with moderate
percentages of the population in the high and low income categories
through 1974.
5.5.10. IMPACT ASSESSMENT
Scott County, slated for a coal conversion plant, presents rather
mixed environmental orientations to us. On the one hand, there is a
large rural farm population with a predominantly sentimental orientation.
On the other hand, urban influences, which are primarily instrumental
in character and due both to a fairly good sized town in the county
and nearby Lexington suggest the potential for real conflict concerning
the location of a coal conversion plant. Being nearby residents our-
selves, we know the plant is a very controversial issue. We predictt
III-D-93
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however, that the instrumental orientation will eventually predomi-
nate and the plant be constructed there. Opposition will probably
come primarily from environmentalists in nearby Fayette County and
from farmers. If it is well-organized, it might be able to delay
the plant or possibly stop its' construction.
III-D-94
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5.6. BOONE (32,812), CARROLL (8,523), TRIMBLE (5,349), OWEN (7,470)
AND GALLATIN (4,134) COUNTIES
Five counties in Northern Kentucky may be subject to the impact
of power plant development. Sites in Boone, Carroll and Trimble Coun-
ties have already been chosen for new coal-fired units. Rabbit Hash
in Boone County will be the site of a three-unit coal-fired plant
totaling 2,138 megawatts with units scheduled to go into operation in
1980, 1982 and 1984. Carroll County presently has a plant at Ghent
to which will be added three coal-fired units (500, 550 and 550 mega-
watts) scheduled for operation in 1977, 1980 and 1983. At that point,
power generating capacity in Carroll County will total 2,625 megawatts.
Trimble County will have a new two-unit coal-fired plant at Wises
Landing totaling 990 megawatts and scheduled to go into operation in
1981 and 1984.
The scenarios posit additional units for Trimble County and new
plants in Gal latin and Owen Counties. In Scenario I, Trimble and
Gal latin Counties will both have large 3,000 megawatt coal-fired plants
and Owen will have a 1,000 megawatt plant. Scenario II would place a
3,000 megawatt nuclear plant in Trimble County and a small 1,000 coal-
fired plant in Owen. Scenario III would add only one plant, a two and
one-half unit (1,500 megawatts) plant, in trimble County to the pre-
sently planned concentration in this area. From the information above,
it appears that Trimble County offers good locations for either coal or
nuclear p'ower plants.
Boone, Gallatin, Carroll and Trimble Counties border the Ohio
River between Cincinnati and Louisville. The Kentucky River goes from
the Central Kentucky region across Carroll County and empties into the
Ohio River. Owen County is adjacent to Carroll and Gallatin Counties
and has the river for its northern border.
A major highway, 1-71, crosses all four river counties from
Cincinnati to Louisville. Two U.S. Highways, 127 and 421, cross 1-71
in Trimble and Gallatin Counties running south to Frankfort, the capiV,
tol of the state which lies 20 miles west of Lexington, a third metro-
politan center. Probably no place in these counties is more than fifty
miles from one or another of these three cities.
Boone is the only populous county of the group. Although
included in the Cincinnati/Covington SMSA, it has only two towns with
over 1,000 residents, Florence (11,457) and Walton (1,801). Both are
located just off 1-71 and 1-75 at the eastern edge of the county and
close to the urbanized areas. Florence1 is just to the east of
Covington in Kenton County. Probably any power plant, however, would
be located along the river in the western, less densely settled part of
the county.
III-D-95
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Only three other towns in these counties have over 1,000 people:
Carrollton (3,884) in Carroll County, Owenton (1,280) in Owen County,
and Warsaw (1,232) in Gallatin County. Both Carrollton and Warsaw
are located on the Ohio River but Owenton is on U. S. Highway 127 in
the center of Owen County. Although Trimble does not have sizeable
communities, Madison, Indiana (13,081) is just across the river in
Jefferson County.
5.6.1. LAND USE
Over three-fourths of the land in all five counties is in farm-
land. Almost a half of the land in all but Boone County is forested.
Urban use of land has been estimated and is negligible in all but
Boone County.
Table III-D-28
KY-6 LAND USE
Boone
Gallatin
Carroll
Trimble
Owen
Percent
Farmland
1969
79.4
77.0
77.9
82.0
79.9
Percent
Forest
1975
31.0
43.3
45.1
45.1
41.6
Percent
Urban
1975
18.0
4.6
2.0
2.9
0.7
There is no oil or coal production and other mining or quarrying
activities are negligible.
5.6.2. RECREATIONAL AND CULTURAL AMENITIES
Outdoor recreational facilities, as is usual in Kentucky, are
readily accessible. Three of the counties, Boone, Carroll and Owen,
have sizeable amounts of recreational land, considering the small
populations and size of these counties. In addition to two state
parks within these counties, there are several more within this
Northern Kentucky region as well as any recreational facilities
connected with the rivers.
Those who wish to enjoy museums, theatres or other similar
recreational amenities must travel to one of the nearby urban centers.
III-D-9P
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Table III-D-29
KY-6 RECREATIONAL LAND (Acres)
Total Land
Hater
Boone
Gal latin
Carroll
Trimble
Owen
2,735
138
1,078
416
2,923
2,591
100
1,033
404
2,414
144
38
45
12
509
5.6.3. RESIDENCE
Population density is low for all but Boone County. In the
three completely rural counties, Gallatin, Trimble and Owen, the farm
population is substantial. As expected, Boone County is largely rural
non-farm with a substantial urban sector. The unexpectedly urban-like
profile presented by the percentages for Carroll County Ms the
consequence of a small county having the main local population center.
The rural population is probably just as sparse in the rest of the
county as it is in the other highly rural, low density counties.
Table III-D-30
KY-6 DISTRIBUTION OF THE POPULATION
Boone
Gallatin
Carroll
Trimble
Owen
Density
per.sq. mile
per
132
41
66
37
21
Percent
rural
non-farm
50
64
39
61
55
Percent
rural
farm
12
36
16
39
45
Percent
urban
38
0
46
0
0
Except for Boone County the populations are highly stable and
composed predominantly of native Kentuckians. Owen County appears to
be the most stable. Higher rates of mobility, expected in an urbani-
zing area, characterize Boone County. It appears that most of the
native out-of-state population comes from the North Central States,
probably Indiana across the river.
III-D-97
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Table III-D-31
KY-6 RESIDENTIAL STABILITY
Resident in:
Boone
Gal latin
Carroll
Trimble
Owen
Birth
State
77.6
87.6
85.5
87.4
91.6
Same County
1965
67.1
82.7
82.4
78.6
87.0
Same State
1965
81.4
93.1
91.8
90.4
94.7
The only striking population shifts since 1960 have been in Boone
and Owen Counties. In Boone County the direction of change has re-
mained the same but the magnitude is reduced. Owen County has experi-
enced a reversal in numbers and direction of migration. Whether it is
the conditions at home or the conditions elsewhere which are inducing
residents to stay in the county cannot be determined with current infor-
mation. Generally, what these figures seem to convey is that people
are increasingly inclined to stay put. Perhaps in some of the counties
which have experienced out-migration, old residents are returning.
Table III-D-32
KY-6 POPULATION SHIFTS
Population Change Net Migration
1960-70 1970-75 1960-70 1970-74
Boone
Gallatin
Carroll
Trimble
Owen
49.6
7.0
6.9
4.9
-9.3
10.3
5.3
1.4
3.0
6.1
32.1
.1
2.0
- 4.7
-13.2
5.0
3.6
-0.2
—
6.1
Statistics for the shifts in farm population are only available
for the decade of the sixties when Carroll, Trimble and Owen exper-
ienced sharp reductions (45.5, 23.1 and 32.2 respectively) while
Boone and Gallatin Counties had only a small reduction in farm popu-
lation (3.8 and 5.4). We cannot estimate to what extent the farm
population has participated in these changing patterns in population
shifts since 1970.
5.6.4. AGE STRUCTURE
The age structures of these five counties can be viewed as
lying on a continuum with Boone County at one end and Owen County
at the other end. Boone County is characterized by a large young
population and rapidly decreasing numbers in the older age cohorts.
III-D-98
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In Owen County there are relatively few children, a sudden drop in num-
bers after the teens, and relatively large numbers of the older middle-
aged and elderly in the population. Trimble, Gallatin and Carroll Coun-
ties vary between these two extremes as can be seen in the age profiles
and in the median ages;
Boone
Trimble
Gallatin
Carroll
Owen
25.3
28.1
29.7
30.2
35.0
5.6.5. MARITAL STRUCTURE
In general this is an area that has relatively'high percentages
of married people in the population. Boone County, in addition, has
a young population with relatively few divorced or widowed persons and
high percentages of intact families and families with children under 18. .
There are correspondingly low percentages of families with a female
head. Carroll County presents an interesting anomaly with relatively
high percentages of divorced people and somewhat higher than average
percentages of families with children under 18. It is Gallatin County
which has the low numbers of intact families and larger numbers of fami-
lies with female heads, accompanied by relatively high percentages of
divorced women and the widowed. This poses a question, since one would
expect the one-parent families to be drawn to the local center of popula-
tion in Carroll County. The distribution cannot be explained unless the
small numbers of people involved and the problems incurred when looking
at percentages rather than numbers have obscuredii the situation. Owen
County, as expected with its older population, has fewer families with
children still at home.
5.6.6. EDUCATION
Except for Boone County, educational levels are low, ranging
from a median of 11.0 to a median of 11.9 years. Even the levels for
Boone County are just above the ORBES region average for percentages
who have completed high school and college. There is no resident
student population to affect these percentages.
5.6.7. HOUSING
Consistent with shifts in population, Boone County gained
significantly in percentages of households (54.8) as well as new
housing units (56.9). Over 40% of its housing units have been built
since 1960 but this rate is not high enough to accommodate the increased
demand. Almost 80% are one-unit structures and relatively few lack
plumbing (9.6).
III-D-99
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The situation in Owen County is almost the reverse. The loss
in percentage of households (-0.2) is consistent with, if smaller than,
population losses. There was a small gain in the number of housing
units (2.9), however, and surprisingly, almost a fifth (19.7) of the
housing units have been built since 1960. Many still lack some plumb-
ing (42%), nevertheless.
The other three counties range between these extremes with mode-
rate gains in households and numbers of units. Gallatin seems to have
been building houses at a somewhat slower rate (13.7) and consequently
has a slightly higher percentage of houses lacking some plumbing (33.1).
House values and rents are in line with the above pattern, high-
est in Boone($16,995; $128) and lowest in Owen ($8,774; $57) County
with the others ranging in between. It should be noted that home
ownership levels are not particularly high in this area.
5.6.8. ECONOMIC ACTIVITIES
Although substantial proportions of the population live on farms,
farming for the Class I-V farmer is just barely a viable economic acti-
vity. Tobacco is the most important crop in the five counties. In
Boone County, however, livestock farming is a more important type of
farming operation.
Table III-D-33
KY-6 FARMING, 1969
Boone Gallatin CarrollTrimble
Owen
Changes 1964-69:
Farms - 1.4 -16.2
Acreage 11.0 -14.3
Average:
Land value $468 $236
Return per acre 49 46
Class I-V farms:
Number 499 205
Average acres 177 181
Average return $10,944 $10,004
Other farms:
Number 746 168
Average acres 52 71
Average return $ 426 $1,246
Percent farmers:
Work off farm 58.4 36.5
- 2.2
-14.4
$253
50
335
171
$9,116
150
52
$1,274
38.8
- 4.8
- 9.2
$253
52
403
158
$9,176
213
62
$1,239
43.0
- 3.1
- 1.1
$193
39
707
205
$9,166
383
90
$1,223
36.0
III-D-10Q
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Boone, the only county with above average land values, is the
only county with an increase in farm acreage during the late sixties.
All counties experienced decreases in numbers of farms, Gallatin hav-
ing the sharpest decrease (16%). These figures, together with the
percentages of farmers working off the farm at least 100 days per year
also provide an indicator of the extent to which farming provides a
viable economic alternative to other employment for the farm popula-
tion. Of course, it should be remembered that farm residence may
reflect preferred life style and not necessarily economic orientation.
Boone and Carroll Counties, the only counties with substantial
numbers of employees covered in County Business Patterns, were the only
two with listed manufacturing activity, although it is considerably
more important both in numbers and in percentages in Boone County.
Table III-D-34
KY-6 COUNTY BUSINESS PATTERNS, 1973
Population
In CBP
Mining
Construction
Manufacturing
Transportation
Trade
Finance
Services
Boone
32,812
7,931
—
428
3,435
245
2,358
134
947
Gallatin
4,134
268
—
—
___ .
29
180
19
15
Carroll
8,523
2,358
57
129
812
73
527
93
651
Trimble
5,349
213
—
58
—
—
59
44
16
Owen
7,470
504
—
36
—
113
169
61
50
In 1973, County Business Patterns listed an apparel and textile
industry employing 494 persons for Carroll County. By 1974 there were
also chemical and primary metals industries employing between 100 and
500 persons each. The textile industry was no longer operating. By
1975 there was a similarly sized transportation equipment industry and
the primary metals industry was apparently not operating. With these
changes, it is impossible to suggest what is there now. In general,
Carroll County seems to provide a fairly balanced range of job oppor-
tunities to both its own residents and to those of adjacent counties.
It is a focus of in-commuting, probably because of containing the main
local population center.
Boone County offers a wider range of jobs in manufacturing with
sizeable industries (employing between 500 and 999) in: 1) non-electric
machinery, 2) fabricated metal products, 3) electrical equipment, 4) fur-
niture and fixtures, and somewhat smaller industries in 5) rubber and
plastic products, 6) paper, 7) instruments and various miscellaneous
manufacturing. Substantial numbers are employed in the services and
III-D-10.1
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trade as well. Nevertheless, many residents commute to other counties
(probably the Covington or Cincinnati areas) for work, or alternately,
elect to live in more rural Boone County.
It should be noted that in spite of the relative importance of
manufacturing in these two counties, neither had over 50 million
dollars in value added from manufacturing in 1972.
The other three counties all have very few job opportunities
listed in County Business Patterns.
In examining the distribution of the work force among the various
occupations, the relatively high percentages in construction in
Gal latin County and as craftsmen or foremen in Gal latin, Boone and
Carroll Counties should be noted. Recalling the anomalies in the mari-
tal structure previously mentioned for Gal latin and Carroll Counties,
it is interesting to speculate about whether there has been some
construction or developmental activity in that area which is affecting
the social structure and composition of these two counties.
5.6.9. INCOME
As expe.cted, the per capita and median incomes are high or
relatively high in Boone County and below average in the other
counties. This pattern holds through 1974. It is also interesting to
note that, except for Boone County again, there is little difference
between the figures for the total and for the farm population.
Table III-D-35
KY-6 INCOME
Boone Gal latin Carroll Trimble Owen
1969:
Median family $10,011
Median farm family 8,179
Per capita 2,857
1973:
Per capita 4,523
1974:
Median family EBI 14,938
$5,864
4,537
1,844
3,286
8,269
$6,885
6,594
2,311
4,019
9,857
$6,596
5,679
2,073
3,339
10,280
$5,892
6,366
2,094
3,833
6,830
5.6.10.^ IMPACT ASSESSMENT
The environmental orientations of these five Kentucky counties,
Boone, Carroll, Gal latin, Owen and Trimble, are very homogeneous with
the exception of Boone County. The latter county, being part of a
SMSA, has a primarily instrumental orientation and, as such, should
house a population generally amenable to power plant development.
III-D-102
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Moreover, there would be no boomtown syndrome due to the nearby
availability of a skilled labor force.
Gal latin, Owen and Trimble Counties would seem to be charac-
terized by the primordial belonging sub-orientations, given the rural
and recreational nature of land use and the stability and relative
elderliness of the population who are probably highly attached to
their homes, land and lifestyle. .Gallatin and Trimble would not
experience booms because of nearness to urban centers. Owen County
would be innundated by the construction phase and unable to deal with
the strains.
Carroll County presents a less clear picture with its rural
population and one small city that serves as a trade center. If a
power plant were to be sited in the county, Carroll ton would become
a likely boomtown candidate. The city might generally welcome such
development and, given its relatively diversified but small, economic
infrastructure, not have too much difficulty coping with boomtown
demands and successfully attracting secondary industry after the power
plant is built. One might surmise that the prestige sub-orientation
would characterize CarrolIton residents and the primordial belonging-
ness sub-orientation characterize its rural population who might be
opposed to power plant development.
III-D-103
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5.7. BRACKEN (7,227), MASON (17,273), LEWIS (12,355) AND GREENUP (33,192)
COUNTIES
In northeastern Kentucky along the Ohio River a string of four counties,
Bracken, Mason, Lewis and Greenup, have been selected as potential
sites for power development. The only power generating facility in the
area is a new plant near Maysville in Mason County with one 300 mega-
watt coal-fired unit under construction and two coal-fired units (300
and 500 megawatts respectively) scheduled to go into operation in 1977
and 1980.
Under both high energy scenarios, this area will be subject to a
high level of impact. Under Scenario I there will be two-unit coal-
fired plants in both Bracken and Greenup Counties and a single unit
nuclear plant in Lewis County. Scenario II proposes a three-unit nuclear
plant each for Bracken, Mason and Lewis Counties and a two-unit nuclear
plant in Greenup County. Under low energy Scenario IV a three-unit
(3,000 megawatt) nuclear plant would be built in Lewis County.
The C & 0 Railroad and state highways both run along the river
across all four counties from the Cincinnati-Covington SMSA to the
northwest to the Portsmouth, Ohio, Ashland metropolitan areas to the
east. All along the river, most likely sites for plants, are within
60 miles of one or the other of the above mentioned metropolitan
areas. In addition, three U.S. highways, 62 from Georgetown in Scott
County, U.S. 68 from Lexington in Fayette County, and State 11 coming
north through Fleminsburg from 1-64 (47 miles), all converge at
Maysvilie, major town of the area on the river in Mason County.
5.7.1. LAND USE
The region is primarily agricultural with relatively high per-
centages of forest land in both Lewis and Greenup Counties.
Table III-D-36
Ky-7 LAND USE
Recreational
acreage (1975) %Land in Farms (1969) %Land in Forest (1975)
Bracken
Mason
Lewis
Greenup
320
482
1,100
2,000
84.9
91.1
59.4
51.8
35.4
17.5
74.4
70.4
III-D-104
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Mining is of negligible importance. Greenup, although on the edge
of the eastern Kentucky coal producing region, has no production listed
for 1973. Greenup County did produce 26,151 tons of clay mined by 11
men at six mines in 1973. Lewis County also produced some clay, 15,155
tons at two mines employing 5 men.
5.7.2. RECREATIONAL AND CULTURAL AMENITIES
The area is predominantly Protestant with Baptists predominating
in Lewis and Greenup Counties. Methodists predominate in Mason County.
Residents have little access to museum or cultural facilities. There
are however, extensive outdoor recreational facilities available.
Greenbo Lake State Park is in Greenup County, and Blue Licks Battlefield,
Grayson Lake, and Carter Caves State Parks are located in nearby counties.
Stretches of the Shawnee State Forest and Wayne State National Forest
in Scioto and Lawrence Counties, Ohio, are across the river. Less than
50 miles south is the northern edge of Daniel Boone National Forest. In
addition, as can be seen from the forest map, sizeable portions of these
counties are in forest although the land may not be developed for
recreation.
5.7.3. RESIDENCE
Residence is predominantly rural non-farm although Greenup County
has been included since 1970 in the Ashland SMSA, indicating the increas-
ingly urban nature of that area. Only Greenup County has more than one
community with a population of 1,000 or more. Maysville, in Mason
County, and Flatwoods, in Greenup County, and each have between 7,000
and 8,000 people. Augusta in Bracken County, Vanceburg in Lewis County,
and Russell, Raceland, Worthington and Greenup, in Greenup County, all
have less than 2,000 residents. The small variation in the generally
low population densities (less than 50 per square mile in Bracken and
Lewis: 50 to 100 per square mile in Mason and Greenup) no doubt
reflects the distribution of the towns.
The population is overwhelmingly stable in residence. Over 80%
are native Kentuckians in the three easternmost counties while between
70% and 80% are native Kentuckians in Greenup County. It should be
noted that of those coming from other states, greater numbers have
migrated from the north-central states than from the south.
Table III-D-37
Ky-7 RESIDENTIAL STABILITY
Live in Lived in Lived in
County Birth State Same State, 1965 Same County, 1965
Bracken 89.7% 91.7% 82.8%
Mason 87.1% 90.3% 84.8%
Lewis 83.3% 91.6% 87.0%
Greenup 76.0% 89.1% 81.4%
III-D-105
-------
Except for Greenup County, the area is characterized by higher than
average residential stability. The greater mobility of Greenup County
residents is to be expected but differences among counties are not
great.
Migration trends between 1960 and 1970 show a very small gain in
Greenup County and losses in Bracken, Mason and Lewis Counties.
Table III-D-38
Ky-7 POPULATION SHIFTS
Bracken Mason Lewis
Greenup
1960-70
Population -2.6 -6.4 5.8 13.5
Farm Sector -16.5 -18.8 -22.5 -38.1
Migration -7.9 -14.6 -19.2 .2
1970-74
Population 4.9 -2.4 3.7 0.9
Migration 3.7 -3.4 0.2 -2.5
In Bracken and Mason Counties natural increase was not high enough
to offset loss from out-migration and both counties sustained population
losses. In Lewis County, with the highest rate of out-migration, there
was still a small increase in the population. This supports the picture
of a county with many young families. Population increase in Greenup
County was almost exclusively a consequence of natural increase.
By the early seventies only Mason County was continuing to lose
population. Bracken and Lewis Counties were growing at a modest rate
and had experienced a reversal of the previous trend towards out-migra-
tion. Greenup County's population appears to have stabilized in spite of
a low level of out-migration.
Shifts from the rural sectors occurred in all four counties in the
sixties and from the urban sector in Mason County (Maysville) as well.
In Greenup County changes in population distribution (including net
migration and natural increases) involved a loss of 15.5% from the rural
sector and a gain of 87.3% to the urban sector. These changes were
accounted for by the rapid growth of Flatwoods (97.3), Raceland (66.5)
and Russell (35.9) during this period.
5.7.4. AGE STRUCTURE
There are distinct differences in age structure among these four
counties. Bracken and Mason have moderately high median ages while
Lewis and Greenup have rather low ones:
III-D-106
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Bracken 33.0
Mason 32.3
Lewis 26.2
Greenup 26.9
The somewhat higher than average death rate and the low birth rate in
Bracken County are in accord with this picture. Especially noticeable
is the low proportion of adults in the middle years (20 to 50) for
both Bracken and Mason Counties. This may reflect a past period of
out-migration on a higher level than in the other two counties.
5.7.5. MARITAL STRUCTURE
In all four counties percentages of married men is high (Greenup)
or relatively so and in Lewis and Greenup Counties the percentages of
married women are also relatively high. These factors, coupled with
the relatively low percentages of divorced men and women, the relatively
high percentages of families with children and a low median age, present
a picture of an area with especially large numbers of young families in
the early stages of the family cycle.
Differences between Lewis and Greenup Counties appear to be related
to relative stability versus mobility. As has been shown, Lewis County
is relatively stable resident!'ally with a low in-migration rate and
probably an increasing tendency for the young to remain nearby. The
young are workers rather than students. They marry and have families.
Marital instability is not counteracted by the possibilities for re-
marriage offered by the more mobile and more urbanized environment
characteristic of Greenup County. Indeed, the higher than usual per-
centage of single men in Lewis County may be due to this same factor,
fewer opportunities to marry in the first place.
Data for Mason and Bracken Counties suggest another group of
factors. High median age and low to moderate percentages of families
with children under 18 indicate an area where families are, for the
most part, in later stages of the life cycle. In Bracken County a
relatively high percentage of the women are widowed and there are
relatively few single women. Mason County is characterized by a high
percentage of divorced women and families with a female head and a
correspondingly low percentage of intact families. Surprisingly,
considering the industry in the county, there is also a low percentage
of adult males in the population (46.8%). These data point to this area
as a focus of in-migration for single and divorced women, most likely to
work in Maysville. Continued net out-migration is a puzzle, however. The
age structure for Mason County coupled with this information suggests out-
migration of young adult males which may more than balance any in-migra-
tion of women, many of whom may be middle-aged. If males have a greater
tendency to migrate out for jobs, education, or to leave a difficult
family situation, marriage, and remarriage for the remaining women are
less likely. <> ;
III-D-1Q7
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5.7.6. EDUCATION
Generally the population is poorly educated with very few having
college degrees or even high school diplomas. The median level of
schooling is slightly higher in Greenup County.
5.7.7. HOUSING
Gains in numbers of households and housing units between 1960 and
1970 were less than 10% in all but Greenup County. Building rates are
keeping up with the increase in number of households and providing for
some replacement of existing houses.
Houses are overwhelmingly in one-unit structures. Many in the
three western Counties lack some or all plumbing facilities. This is not
surprising considering that housing is older in these counties.
The higher numbers of persons per room in Lewis and Greenup Counties
is probably related to the younger population than to anything else.
Table III-D-39
Ky-7 HOUSING, 1970
Bracken Mason
Lewis Greenup
Change 1960-70:
Households 0.9 0.5 4.6 24.5
Housing Units 5.6 2.2 9.4 24.1
Median:
House Value $8,808 $12,873 $6,956 $11,412
Rent 63 72 55 77
% of Units
One-unit structures 87.4 81.3 92.2 91.2
Built since 1960 8.0 14.4 16.0 27.9
Owner-occupied 66.5 56.1 67.6 77.7
Lack some plumbing 34.1 23.3 48.1 14.7
Values of housing units and rents, characteristic of the area, are
low. The differences between the house values in Bracken and Mason
Counties as opposed to those in Mason and Greenup Counties is striking
and corresponds to the location of the larger population centers.
5.7.8. ECONOMIC ACTIVITY
An examination of the County Business Patterns for 1973 gives some
indication of non-farm economic activity in these counties.
III-D-108
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Table III-D-40
Ky-7 COUNTY BUSINESS PATTERNS, 1973
i
Bracken Mason Lewis Greenup
Total Pop. 7,227 17,273 12,355 33,192
In CBP 535 4,489 1,001 1,648
Agriculture — 8 — —
Mining — — — —
Construction 14 144 28 287
Manufacturing —- 1,975 648 383
Transportation 56 110 23 78
Trade *125 1,356 235 595
Finance 40 202 37 76
Services 44 672 24 178
* Retail trade only; no wholesale figures supplied for
Bracken County.
Highly rural Bracken has very few jobs in any of the categories and
no activity is predominant. By 1974 there were between 100 and 500
persons engaged in the manufacture of rubber and plastics but nothing
else of significance. Between 15% and 25% of the resident workers
commute out of the county to work. Few women are in the labor force
and consequently few families have both husband and wife in the labor
force. Those women who must work, widows with children, divorcees and
single women, may migrate rather than commute out, possibly to Mason
County.
We see almost the reverse situation in Mason County. There are
over 15% more workers than there are working residents. This county
is a focus of in-commuting, probably from adjacent counties. There
are over two and one-half times the number existent job opportunities
in Mason than in Greenup County with almost twice the population. The
major part of these jobs are in manufacturing although there are also
substantial numbers in trade and the services. Surprisingly, given
the pattern of job opportunities in the area, Mason has not been the
focus of net in-migration. Age and marital structure plus an examina-
tion of the type of industries located in Mason County offer clues to
the interpretation of this anomaly. The electric machinery industry and
the textile industry, two of the three largest industries in this county,
employ relatively high percentages of women (41% and 68% respectively)
compared to the percentages of women employed in Kentucky manufacturing
(34%) in general. These jobs plus the usual opportunities in trade and
the services suggest a reason for the concentration of women who must
work in this county. On the other hand, since women usually receive
lower wages,'these jobs may not be attracting men to the county.
-------
In addition to the above industries, there are over 250 employed in
the production of machinery and between 100 and 249 employed each in the
tobacco and transportation equipment industries.
In Lewis County manufacturing is also a significant economic
activity but apparently is not sufficient to provide jobs for all
residents since over 25% of the workers commute out. This is not
surprising when you look at the numbers. Lewis has approximately 70%
of the population of Mason County but less than a fourth the number of
jobs. Small firms make shoes and wood products and small numbers of
workers are engaged in trade and services. This county is much more
similar to Bracken than to Mason County in its economic composition.
The situation in Greenup County is somewhat different. Greenup
appears to contain residential satellites of the Ashland SMSA. Most
jobs are in trade which is probably only sufficient to serve the
immediate area. Note that Mason County with only one town, Maysville,
has many more jobs available in the trades and services than does
Greenup County with similarly sized Flatwoods. This suggests the
probability that Maysville serves a wider area. Possibly residents of
Greenup County go outside for many services.
By 1974 Greenup County appeared to have developed some significant
industrial activity, probably an outgrowth from Boyd County where these
same activities were also present at about the same level. In addi-
tion to small industries in 1) stone, clay, glass, and concrete, and
in 2) chemical products (both employing between 100-500), there is now
a growing (employing over 1,000) industry in 3) primary metals.
In general the percentages of the population employed in the
different sectors support the above profiles and add nothing to the
picture. It should be noted, however, that there is a very high per-
centage of the work force who are employed as craftsmen or foremen in
Greenup County. Since there is not a large amount of manufacturing,
this information provides a clue to the segments of the population
choosing to reside in that county.
As an economic activity, farming is noticeably more profitable in
Mason County than in the other three counties, in spite of the relatively
small size of farms. This may partially explain the slightly smaller
percentage of farmers who worked off the farm for more than 100 days in
Mason County (27.9% as opposed to 33.3, 38.5 and 58.0 percent in Bracken,
Lewis and Greenup Counties respectively). Percentages working off the
farm in Bracken and Lewis Counties are still relatively low, especially
when compared to Greenup County. These figures accord well with the
greater number part-time farms in the latter county.
III-D-UO
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Table III-D-41
Ky-7 FARMING, 1969
Bracken Mason Lewis Greenup
Change 1964-9:
Farms -2.6 -1.6 -8.5 1.6
Acreage -5.9 -3.8 -5.7 9.4
Average:
Land value 216 299 147 174
Return per acre 51 70 29 23
Class I-V Farms:
Number 581 717 527 242
Avg. acres 151 170 236 218
Avg. return 9,096 12,010 8,674 8,145
Other Farms:
Number 309 300 638 703
Avg. acres 74 57 95 90
Avg. return 1,155 1,107 1,141 1,033
Average sizes of farms are relatively small, less than 200 acres
in Lewis and less than 150 acres in the other counties. Average values
of land and buildings are also low. Except for Mason County where
farming may be a more viable activity, the majority of farms in the area
have cash incomes of less than $2,500 a year. Return per acre is low
also, especially in the two easternmost counties.
There have been changes in numbers of farms and in farm acreage
since 1964. Bracken, Mason and Lewis Counties all show losses in both
numbers of farms and in farm acreage between 1964 and 1969. Greenup
County, however, showed a gain in number of farms and in farm acreage
for the same period. In terms of land utilization, the change is small
but considering the low return on farming, the trend is of interest as
a possible indicator of life styles of Greenup County residents.
Several types of farming activity are important in this area.
Tobacco was the primary farm type listed for all four counties. Dairy
farming was second in importance for all but Greenup County. Livestock
raising was a close third in importance for Mason County. It should
be noted that although tobacco is the most important activity on a
large proportion of farms, the small differences between the total cash
returns from crops and livestock (and products) indicate that the return
per farm may not be sufficient to provide the basis for full-time
farming operations. Considering the value of tobacco as a cash crop,
it is likely that anyone owning a farm with-a tobacco allotment will
take advantage of it as a supplementary source of income to farming or
any other economic activity either by working it himself or leasing it
to a nearby farmer. That is, the return from tobacco may be widely and
III-D-111
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thinly spread over the population. Dairy farming and other livestock
farming, both labor intensive activities, are most likely to provide the
basis of full-time farm operations.
• Table III-D-42
Ky-7 TOTAM/ALUE OF FARM PRODUCTS, 1969
County Crops Forest Products Livestock & Products
Bracken 3,452,152 2,555 2,097,276
Mason 5,057,133 2,903 4,600,767
Lewis 2,786,890 46,334 2,466,230
Greenup 1,414,640 22,725 1,259,617
It is suggested that the generally low return on farming and the
low value of farm land, has (as indicated by the increase in numbers
and acreage of farms and the high percentages of part-time farms)
allowed workers in the increasingly urbanized Greenup County to elect
a semi-rural life style. Farming as an avocation, to supplement the
family income or simply to pay the property taxes, can be pursued as a
secondary economic activity.
In the other three counties another interpretation is offered.
Similar percentages of part-time farms, farmers who work off the farm,
losses in farm numbers and acreage, and high levels of residential
stability indicate that a fairly consistent proportion of farmers must
either give up farming or find other sources of income to support an
acceptable standard of living. Mason County, where farming is a slightly
more viable economic activity, has fewer making these choices, even
though opportunities for other employment are probably better here than
in either of the two adjacent counties. Indeed residents of other
counties commute to Mason County for work.
5.7.9. INCOME
Maps on median family income, per capita income, and percentages of
families in the high and low income categories for 1969 all present a
similar picture. Mason and Greenup Counties are average or slightly
below average for the ORBES region. Bracken and Lewis are relatively
poor. The farm population is poor in all four counties, especially so
in Greenup County.
Figures for 1973 show a somewhat changed picture. Per capita income
in Bracken and Lewis Counties is still low, but Greenup County also is
categorized as a low income county. Perhaps this is related to the
slowdown in migration in the early 1970's.
III-D-112
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Table III-D-43
Ky-7 INCOME
Bracken Mason Lewis Greenup
1969:
Median Family $5,850 $7,140 $5,726 $7,592
Median Farm Family 5,417 5,517 5,372 4,818
Per capita 1,877 2,407 1,713 2,236
1973:
Per capita 3,241 4,075 2,439 3,241
1974:
Median Family EBI 6,216 8,881 6,187 11,916
Sales Management statistics for 1974 support the 1969 picture,
showing Bracken and Lewis Counties as moderately low, Mason as about
average for the region, and Greenup as somewhat above average in median
"effective buying power" (EBI) and in percentage of households with
above average EBI. High percentages of households with low EBI are
shown for Bracken and Lewis Counties. Obviously a more sophisticated and
detailed examination of income in these counties is necessary before a
clear picture can be drawn. The pattern of income differences among
the counties is apparent, however.
One aspect of income distribution should be noted. In all four
counties the poor form a substantial proportion of the population and the
low income population has many young people in all but Bracken County
and fewer than average of the elderly in Lewis and Greenup Counties.
This might have been predicted from age and marital structure. Public
assistance payments, however, are primarily to the elderly. Except for
Bracken County, this poses a question about the quality of life and the
resources available to the poor in the middle and early phases of the
family cycle who apparently are numerous in the other three counties.
5.7.10. IMPACT ASSESSMENT
Bracken, Lewis, Mason and Greenup Counties in northeastern Kentucky,
while in geographical proximity, present some variation in environmental
orientations. Bracken County is a poor rural county with a high pro-
portion of people who are in the later stages of the family cycle, with
children gone and frequently one spouse dead. There are few job oppor-
tunities for those in their working years who are unable to maintain a
viable farming operation. Most of the public assistance goes to aid the
elderly who are often widowed. As a consequence, some migrate out and
some commute to nearby counties for work. Lewis County is very similar
in demographic characteristics except for age structure. Young families
are more prevalent in this county which also exhibits an unusually stable
residential pattern, even for this generally stable area. The pre-
III-D-113
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dominant orientation in these two counties is that of primordial
belonging with some evidence of an aesthetic sub-orientation in Lewis
County, which may account in part for younger people's presence there.
Attitudes toward power plant development probably vary because of the
difference in age structure of the population with Lewis County being
more favorable. A commuting work force during the construction phase
from nearby cities would generally mitigate construction boom impacts.
Mason County is the site of a regional trade and manufacturing
center. Though sharing the general rural characteristics of the area
and the age structure of neighboring Bracken County, Mason County
provides economic options and supplements to farming for both its own
residents and those of adjacent counties. Mason County presents a mixed
environmental orientation picture. It seems to be a thriving county with
a fairly diversified economy. This would suggest receptivity to power
plant development and the capacity to deal with a moderate boomtown
situation, given adequate planning.
Greenup County is a transition area between the more rural counties
to the west and urban areas to the north and east. The popula-tion,
young, working class, and somewhat more mobile, are most likely oriented
to the urban areas for economic activities, living standards, social
services and amenities, but they are very likely to have their roots
in the more rural society to the west. Greenup County seems to be in
the transition from a sentimental to an economic benefit sub-orientation
as it continues to urbanize. The youthful ness of its population and
its bedroom community status would seem favorable indicators for power
plant development, provided the plant were located in a rural area for
the prestige sub-orientation tends to be dominant in suburban areas where
some opposition may exist but is likely to be ineffective. A commuting
labor force from nearby Ashland or Portsmouth would mean minimal boom-
town effects.
III-D-114
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5.8. JEFFERSON (695,005) COUNTY
Jefferson County will be the site of two new coal-fired units (425
and 495 megawatts respectively), planned as additions to the Mill Creek
Plant in Louisville and scheduled to go into operation in 1977 and
1979. These additions will bring the already high power generating
capacity in Jefferson County to 3,254 megawatts by 1985. No additions
are projected in the scenarios.
Jefferson County is the center of the Louisville SMSA which by
1974 included Bullitt County in Kentucky and Floyd and Clark Counties
in Indiana. Louisville, located on the Ohio River, is the major city
in the SMSA with a population of 361,472. Jeffersonville and New
Albany, across the river in Indiana, are nevertheless sizeable with
20,008 and 38,402 respectively. The entire SMSA has a population of
826,553, but 695,005 are in Jefferson County.
5.8.1. LAND USE
About 15% of the land is in forest and almost 37% in farms in
this highly urbanized county. Somewhat higher percentages of these
uses of land prevail in the less populous counties of the SMSA.
This area is outside the coal producing areas and there is no
oil production in these counties. The value of cement, stone, sand,
gravel and clays quarried in this county totaled $21,009,000 in 1973,
however.
5.8.2. RESIDENCE
The population is predominantly urban in Jefferson, Clark and Floyd
Counties and presumably must be developing urban characteristics in
Bullitt County since that county has been included in the SMSA by 1974.
The number of people living on farms is low, only 2,043 (.3%), less
than half what is was in 1960. Five percent of the population are
classified as rural non-farm, the rest are urban dwellers.
As in most large cities, the percentage of foreign born or those
with foreign or mixed parentage is larger than in the surrounding
areas (4.5%) but, nevertheless, is almost negligible. Of the native
born population, 77.9% are native Kentuckians, almost 15% come from
the north-central and southern states and 2% from the northeast.
Considering.the size of the city, Jefferson County is relatively
stable residentially. In 1965, over 82% of the population lived in
Jefferson County and another 4% in another Kentucky County. Census
figures suggest that in the sixties people were-moving out of the city
into satellite communities since Louisville lost population by 7.5%
but the county as a whole gained in population by 13.8%. Net in-migration
111-0-1:15
-------
for this period is only 1.8% and thus would account for only a small
part of the residential shift. By 1975 there had been a reversal of
county migration to a -3.0% and practically no estimated increase in
population. Neighboring Bullitt and Oldham Counties showed sharp
increases in population (28.5 and 25.1) and net in-migration (19.8
and 20.9) between 1970 and 1975. All these figures suggest that there
are two simultaneous trends occurring: 1) migration out of the SMSA
and 2) migration to the urban fringes. In appears merely to have
accelerated during the early 1970's.
Table III-D-44
Ky-8 POPULATION SHIFTS
1960-70 1970-74
[Number Percent] [Number Percent]
Population Change 84,108 13.3 5,700 0.8
Net Migration — 1.8 -20,800 -3.0
5.8.3. AGE STRUCTURE
Median age is relatively low (27.6) in Jefferson County as might
be expectetl in an urban area. There are no pecularities in the age
distribution.
5.8.4. MARITAL STRUCTURE
Surprisingly, Jefferson County has a low (46.1) percentage of
adult males in the population.
The characteristics of marital status are those expected in an
urban environment. There are low or moderately low percentages of
the widowed, both men and women, high percentages of divorced women and
families with a female head, and correspondingly low percentages of
intact families.
5.8.5. EDUCATION
Educational levels are only moderately high for the region with
over half the population having completed high school and 9.7% having
completed college. The latter percentage is, in part, a consequence
of Louisviflle's having a college population of 16,508, mostly attending
the University of Louisville.
III-D-116
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5.8.6. HOUSING
There has been a gain of 21.3% in the number of households between
1960 and 1970, and a similar gain of 20.7% in the number of housing
units for the same period. This rapid increase is reflected in the
high percentage of total housing units built in this period (26.8%).
As expected only 72.1% of the housing units are in one-unit
structures, only 46.9% are owner-occupied and there is a low percentage
of housing units lacking some plumbing facilities. Housing is less
expensive than usual for major urban areas averaging $15,380 for owner-
occupied single family dwellings. Rents are about average ($78) for
the area.
5.8.7. ECONOMIC ACTIVITIES
Jefferson County has a diversified and relatively balanced range
of economic activities. It is the only Kentucky county with over
100,000 wage earners covered by County Business Patterns. In addition
there were 8,615 on federal civilian payrolls in 1974. A high per-
centage of the labor force worked in manufacturing and Jefferson County
had a respectable amount of manufacturing as measured by 1972 value
added by manufacturing. The largest industrial employers in Jefferson
County produce: 1) electrical equipment, (16,966); 2) machinery,
(14,471); and 3) tobacco, (10,370). Since this is the largest city in
the state, it is not surprising that many workers are engaged in the
professions, in management, or in trade or that workers commute from
surrounding counties to work. As expected also, a high percentage of
the labor force are females.
Table III-D-45
Ky-8 COUNTY BUSINESS PATTERNS, 1973
Total Population . 695,005
In CBP 268,183
Agriculture 610
Mining 363
Construction 16,727
Manufacturing 101,519
Transportation 16,183
Trade 68,704
Finance 16,340
Services 47,025
Farming as an economic activity is relatively insignificant in
terms of the people involved. However, those who farm as a primary
economic activity apparently do reasonably well. The average income
for Class I-V farms is $17,701, and the average size, 150 acres.
III-D-117
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Farm land is expensive, averaging $961 per acre. Farms are primarily
devoted to the raising of livestock (other than dairy or poultry) and
secondarily to dairy farming. There are, however, twenty-five vege-
table farms in Jefferson County, over one-fourth of the total in
Kentucky. Evidently some crops must also be raised on most farms since
the 1969 total for return on crops was almost as high as that for
livestock and products:
Crops $3,568,854
Forest products 12,445
Livestock and products 3,749,563
Percentage of farm operators working off farms is high (57.2). Average
income from part-time farms together with Class VI and retirement farms
is only $1,155 and the average size is only 52 acres. Since there was
a decrease in farm acreage (-6.9) but an increase in number of farms
(14.5) between 1964 and 1969, it is suggested that many full time farms
are being broken up into small farms which provide a semi-rural life-
style option for residents whose primary economic activity is not
farming.
5.8.8. INCOME
Considering the educational and occupational structures as well
as regional variation, it is not surprising that median family income
in this urban area was only moderately high ($9,813). Per capita income
was $2,605 in 1969 and $3,717 by 1973. Moderately high percentages of
the population are in high income categories and correspondingly few
in the low categories.
Of those who are poor, higher than average numbers are young and
relatively few are old. Public assistance payments are more or less
in line with this.
5.8.9. IMPACT ASSESSMENT
The prevailing sub-orientation in Jefferson County, given its
urban diversified nature, is economic benefit. Since the plants planned
are additions to an existing plant, and there is a skilled labor force
nearby, it is predicted that impact will be minimal unless opposition
groups holding contrary environmental orientations emerge.
III-D-H8
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6. DEMOGRAPHIC PROFILES AND IMPACT ANALYSIS: ILLINOIS
6.1. MERCER (17,294), HENDERSON (8,451) and HANCOCK (22,645) COUNTIES
Three counties in northern Illinois along the Mississippi are
slated for nuclear energy development under the high energy scenarios.
Scenario I posits a two-unit (2,000 megawatt) plant for Mercer County.
Under Scenario II, two-unit plants are planned for Henderson, Hancock,
and Mercer Counties. At the present time there are no power plants in
any of these counties.
There are only eight towns with over 1,000 residents in these
counties, five in Hancock County and one on the border between Hancock
and Henderson Counties. The communities are, for the most part,
located at junctions of the main east-west highways which cross the
counties and north-south state roads. These counties are, however,
ringed by urban areas, both in Illinois and across the river in Iowa.
Directly north of Mercer County, about 30 miles from Aledo (3,325) is
the Davenport-Moline SMSA. U.S. Highway 34 crosses Henderson County,
connecting Galesburg in Knox County with Burlington, Iowa. Monmouth
(11,022) in neighboring Warren County is half way between the two
metropolitan areas, on the same highway. The only Henderson County
town, Oquawka (1,352), is six miles north of this highway on the river.
The presence of the Iowa cities of Fort Madison and Keokuk across
the Mississippi River from Hancock County may account for the concen-
tration of small communities in this county. All are in the northern
half of the county on the routes (U.S. 136 and State 9) to the above
cities. The nearest Illinois city for residents of this county is
Macomb (19,643) in neighboring McDonough County.
6.1.1. LAND USE
All three counties have high percentages of land devoted to
farming, less than 15% of the land in forest.
Table III-D-46
IL-1 LAND USE
% Farmland 1973 Mineral Production (dollars)
Mercer 93.3 w
Henderson 83.0 w
Hancock 90.5 $1,085,000
III-D-119
-------
Mercer County is underlain by coal bearing rock but, at least in
1974, there was no coal production. The other two counties are located
just outside the coal fields. There are no oil or gas fields under-
lying this area but all three counties have some stone quarrying.
Mercer County has no land devoted to state parks or conservation
areas. Hancock has a 150 acres state park and a further 49 acres of
state managed conservation property. Henderson County, while having
only 89 acres in state parks, has 6,281 acres of conservation property.
There are a few state parks in the surrounding counties as well.
Recreation facilities may also be connected with the river and together
with the above facilities provide what is probably sufficient for these
rural areas.
6.1.2. RESIDENCE
In all three of these sparsely settled counties, slightly over a
fourth of the population live on farms. The urban segments live in one
of three towns, each with less than 3,400 people (Aledo - 3,325, Carthage
3,350, Hamilton - 2,764), and the rural non-farm segments live in even
smaller places or in the open country.
Table III-D-47
IL-1 DISTRIBUTION OF POPULATION
Density
Farm Population
Urban Population
Rural Non-Farm Population
31
Mercer
per Sq.
27%
19%
54%
Henderson
Hancock
Mile
22 per Sq. Mile 30 Per Sq.
32% 26%
0% 26%
68% 74%
Mile
The population in these counties appears to be changing very little.
All the towns, with the exception of Oquawka and Hamilton (both show 24%
population increase between 1960 and 1970) exhibit either little change
or decline during the sixties. All counties have experienced low levels
of out-migration since 1960 and although the population was maintained at
about the same level during the sixties, it has been falling since then.
Table III-D-48
I1-1 POPULATION SHIFTS
Mercer Henderson
1960-70
pop. change .8 2.6
net migration -5.1 -5.1
1970-74
pop. change -0.9 .-2.4
net migration -2.1 -3.5
Hancock
-3.7
-5.9
-5.4
-5.6
III-D-120
-------
A large part of the population shifts may have affected farm
families, although it is possible that shifts from farm to non-farm
residence may occur within the county and thus not be reflected in
county population change and net migration figures. Losses from the
farm population during the sixties was substantial:
Mercer -28.0
Henderson -32.1
Hancock -26.3
As expected in border counties, slightly fewer residents are
natives of Illinois than in counties in the interior of the state.
Levels of recent residential stability, however, do not appear to
differ greatly from other counties in the state. Close to 90% of
the population lived in the same state in 1965, over 75% in the same
county.
Table III-D-49
IL-1 RESIDENTIAL STABILITY
Birth State Same County 1965 Same State 1965
Mercer
Henderson
Hancock
79.6
70.3
74.3
83.9
76.1
81.3
94.9
87.6
89.8
6.1.3. AGE STRUCTURE
Little about the age structure of these counties is distinctive.
Median ages are:
Mercer 30.9
Henderson 31.6
Hancock 32.4
These counties have relatively high percentages of older people and relatively
few young adults. The most noticeable difference among these counties
relates to the pattern of variation among the young adult cohorts.
All three counties exhibit sharp declines in relative numbers of indi-
viduals between the teenage and the adult age groups. The decrease is
sharpest for Hancock County and there is a slight decrease in numbers
after that for each cohort until the 40 plus groups. In Mercer and
Henderson the pattern is for an increase in the 25-29 age group. This
could indicate more of the young returning after working or going to
school elsewhere.
III-D-121
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6.1.4. MARITAL STRUCTURE
The high percentage of intact families characterizes all three
counties:
Mercer 92.4
Henderson 89.8
Hancock 89.9
These percentages, together with the relatively low percentages of
single and divorced people, the average percentages of widowed men and
women and the age structure are consistent with a picture of these
counties as peopled by families fairly evenly apportioned among the
different stages in the family cycle. Neither those families with
very young children nor those whose children have left home predominate.
The young frequently leave, those who remain or return are likely to
marry. Marriages are reasonably stable or the divorced, especially
female heads of families find it advantageous to leave the county.
6.1.5. EDUCATION
As is true across the northern ORBES region, most people finish
high school. Very few have gone to college, however. This does not
mean that the children born in these counties are not attending college
elsewhere. It does mean that the residents who remain in the area,
for the most part, are not the ones who have gone beyond high school.
There are no resident student populations large enough to materially
affect these percentages.
6.1.6. HOUSING
Changes in numbers of households and housing units during the
sixties was consistent with changes in population, and rates at which
new units were being built.
Table III-D-50
11-1 HOUSING, 1970
Mercer Henderson Hancock
Changes: 1960-70
Housing Units 3.8 15.8 -1.2
Households 3.6 8.8 -0.4
New units since '60 13.3 18.6 11.4
% of units:
Lacking plumbing 5.4 10.3 9.8
One-unit structures 91.6 88.3 87.2
Home owners 73.5 72.5 74.8
Median value $11,252 . $9,372 $9,017
Median Rent 89 81 88
III-D-122
-------
The fewer than average proportion of housing units which lack some
plumbing may be a factor leading to lower replacement rates for units.
Most are single unit dwellings.
Median values for owner occupied single unit dwellings and median
rents are moderate to low in these counties.
6.1.7. ECONOMIC ACTIVITIES
As expected with the ring of urban centers around these counties,
many commute out. The primary non-agriculture activity is in retail
trade. A small amount of manufacturing is done in Hancock County in a
food industry (employing 224 persons) and a chemical industry, both
listed in County Business Patterns.
Table III-D-51
IL-1 COUNTY BUSINESS PATTERNS, 1973
Mercer Henderson Hancock
Total Population
In CBP
agriculture
construction
manufacturing
transportation
trade
finance
services
17,254
1,341
41
74
87
166
718
66
164
8,451
530
—
«2
4
59
283
60
68
22,645
2,636
—
158
577
161
1,019
164
520
One interesting aspect of the work force in Hancock County is
the relatively high percentage of families with both husband and wife
in the work force.
After comparing the numbers of jobs covered in the 1973 County
Business Patterns and the numbers of farms reporting in the 1969 Census
of Agriculture, it is clear that farming is the most important economic
activity in all three counties. Return per acre is high, farms are
relatively large and large proportions of them appear to be full-time
operations. Livestock raising yields the most return (60% to 70%)
and crops are second in importance.
These counties exemplify the gradual trend towards farm consolidation.
The reduction in the amount of land devoted to farming in Henderson
County poses a question for which an answer cannot be suggested using
these data.
III-D-123
-------
Table III-D-52
IL-1 FARMING, 1969
Mercer Henderson Hancock
Average land value
Average return per acre
$380
106
$384
96
$365
92
Class I-V Farms:
Number 1,094 564 1,620
Average acres 295 350 273
Average return $32,082 $33,881 $23,231
Other Farms:
Number 146 52 289
Average acres 64 49 65
Average return $1,164 $ 806 $1,063
Changes: 1964-69:
Number of farms -9.3 -11.2 -5.6
Farm land - .2 - 6.3 - .1
6.1.8. INCOME
Median family incomes for both the total and the farm population
as well as per capita income are above average for the ORBES region.
The figures on 1973 per capita income indicate the persistence of
pattern. The 1974 figures in Sales Management place these counties as
just about average in "effective buying power", clearly lower than the
affluent north-central counties.
Table III-D-53
IL-1 INCOME
Mercer Henderson Hancock
1969
Per Capita
Median Family
Median Farm Family
$ 3,215
8,683
8,587
$3,423
8,307
9,048
$3,018
7,893
7,263
1973
Per Capita 5,403 5,711 5,804
1974
Median Family EBI 10,395 9,847 9,395
III-D-124
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6.1.9. IMPACT ASSESSMENT
Mercer, Henderson and Hancock Counties, bordering the Mississippi
River in northwestern Illinois, present a relatively homogeneous
picture with regard to their prevailing environmental orientations:
sentiment. However, among the sub-orientations, the ties are not
simply primordial belonging but have a very substantial prestige or
stratificational component as well. Given, too, the economic benefit
derived from this prosperous farming area, the instrumental sub-orienta-
tion is there as well.
Given these orientations, we think Mercer County the most receptive
to power plant development, largely because there would be minimal
boomtown effects due to a nearby large city. In the other counties, we
would expect some opposition from farmers should prime farmland be
selected for a power plant site. The relatively numerous small towns
in Hancock and Mercer County suggest some economic diversification
is present though farming dominates land use. In Hancock County, the
boomtown potential is there as is true for Henderson County. The
latter county, being completely rural and given its relative prosperity,
is likely to be opposed to power plant development. The same would
probably be generally true of Hancock County as well.
III-D-125
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6.2. IROQUOIS (33,532), LIVINGSTON (40,690), GRUNDY (26,535),
LA SALLE (111,409), MARSHALL (13,302) a/id DE WITT (16,975) COUNTIES
In an area of norther Illinois with an already high concentration of
present or planned nuclear power generation, increased development is
posited under Scenarios I, II and IV. Grundy, LaSalle and DeWitt Counties
presently contain sites of new or additional facilities planned to go into
operation before 1985. The town of Morris in Grundy County is the site
of a large nuclear power plant with a generating capacity of almost 5000
megawatts. The addition of five more 500 megawatt units before 1985 will
bring the generating capacity of this county to 7372.6 megawatts. At
Seneca, just over the county line in LaSalle County, 13 miles west and
also on the Illinois River, another nuclear power complex is developing.
In addition to units totalling 2293.4 megawatts under construction, two
new units of 1078 megawatts each are planned for completion by 1978 and
1979. These will bring the power generating capacity of this county up
to 4590.7 by 1985. DeWitt County, to the south in the north-central
part of the state, has a nuclear plant planned for Clinton with two 950
megawatt units slated to go into operation by 1981 and 1984. The power
generating capacity of this county will then reach 1907.5 megawatts.
Proposed developments under the scenarios would add further capacity
in Iroquois, Livingston and Marshall Counties which lie south of LaSalle
and Grundy and north of DeWitt Counties in this north-central region of
Illinois.
Marshall County apparently offers the most promising sites since it
would receive 4000 megawatts of power generating capacity under Scenario
1,2000 under Scenario II and 1000 under Scenario IV. Two units (2000
megawatts) in Scenario I would be coal-fired. Ail other units would use
nuclear fuels.
Both Livingston and Iroquois Counties would receive nuclear plants
under high energy Scenario II, 1000 megawatts for Iroquois County and
2000 megawatts for Livingston County.
These six counties are all close to a complex of urban centers in
northern and central Illinois. Dominant, of course, is the Chicago area,
just out of the ORBES region. Fanning out south and west from Chicago
are major highways crossing the impacted counties and leading to secondary
urban centers. Interstate Highway 80 goes west to the Davenport-Moline-
Rock Island SMSA and almost half way across the state crosses Grundy and
LaSalle Counties. LaSalle County has three small cities, Ottawa (18,716),
Peru (11,772), and LaSalle (10,736), close to this major transportation
route. Seneca (1,781) the plant site, is only a few miles south of the
highway and about 20 miles east of Ottawa.
The Illinois River curves south after crossing LaSalle County and
bisects Marshall County before it reaches Peoria. Any power plants are
likely to be sited along the river and State Highway 29 runs along the
river, connecting Peoria with Princeton and 1-80 about 50 miles to the
north.
III-D-126
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U.S. Highway 66 runs southwest through Livingston County to
Bloomington and Springfield. The major town in the county, Pontiac
(9,031), in the center of the county, lies on this highway at the
junction with State Highway 116. The probable location of the plant
in this county cannot be guessed. However, there are four other small
towns, two of them between 3000 and 4000, dispersed around the county
and the county is ringed by urban centers so that the lighter con-
centration of communities and highways may not mean isolation for
Livingston County residents.
Twenty-four miles directly south of Bloomington on U.S. Highway 51
is Clinton, site of the DeWitt County plant. Clinton is connected by
State Highway 10 with Lincoln (21 miles to the west) and with Champaign-
Urbana (40 miles to the east) as well as with Decatur (22 miles south).
U.S. Highway 57 runs south-southwest to Champaign-Urbana through
western Iroguois County. There are numerous small towns in Iroquois
County and although only one, Watseka (5,294), is larger than 2000, this
county's residents also have access to urban centers in other counties.
The closest is Kankakee, approximately 30 miles to the north from
central Iroquois County. A little further, about 50 miles to the south,
is Champaign-Urbana.
The generalization to be made about these counties is that they all
lie on major highway routes between the major urban centers of northern
Illinois. The counties have numerous small towns and although only
LaSalle has communities with populations over 10,000, most residents
have access to sizable towns or urban centers in nearby counties.
6.2.1. LAND USE
All six counties are underlain by coal-bearing rocks but none of
them show any coal production for 1974. In 1973, Marshall County pro-
duced $59,000 worth of sand and gravel. All of the other counties also
produced sand and gravel as well as cement, clay, some stone and pe-
troleum in DeWitt County. Production figures have been withheld,
however, so we cannot gauge the volume although we would guess it is
low. Land is primarily devoted to agriculture, with very little land in
forest. Some acreage in all but Livingston County is maintained by the
state for parks or conservation areas.
Table III-D-54
IL-2 LAND USE
% Land in Farms State Recreational
Iroquois
Livingston
Grundy
LaSalle
Marshall
DeWitt
1969
95.1
96.1
85.3
90.0
87.1
96.0
Acreage,
1,920
2,393
5,391
4,403
371
1973
III-D-127
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6.2.2. RESIDENCE
The density of the population in the three counties where development
is projected by the scenarios is somewhat lower than the density in the
counties where development is already taking place. All counties, however,
have densities of less than 100 per square mile.
Table III-D-55
IL-2 DISTRIBUTION OF POPULATION,
Density Rural Farm Non-Farm Urban
Iroquois
Livingston
Grundy
LaSalle
Marshall
DeWitt
30
39
61
97
34
43
31%
21
15
10
23
20
53%
39
43
25
57
35
16%
40
42
65
20
45
In general, urban percentages appear to reflect the locations of the
larger towns and, in conjunction with the other figures, permit one to
suggest that these counties may be grouped into two clusters with Grundy
and LaSalle, the counties closest to Chicago, being the most urbanized,
and the other four counties having a stronger rural flavor.
One interesting aspect of the population composition of the northern
counties (excluding DeWitt) is that, for the ORBES region, these counties
have high or relatively high percentages of the population who are either
foreign-born or of foreign or mixed parentage. Thus, one might expect
ethnic groups to be a visible element of the population in these counties.
Except for Grundy County, moderately high percentages of the native
population are natives of Illinois. It is not clear, however, that the
residents of any one county are more or less mobile than the residents
of any other county. In general these counties are moderately stable
residentially.
Table III-D-56
IL-2 RESIDENTIAL STABILITY
Iroquois
Livingston
Grundy
LaSalle
Marshall
DeWitt
% Residing in: Birth State
1970
80.0
84.5
75.4
83.8
86.4
81.8
Same State
1965
91.8
91.4
86.1
92.3
93.1
86.8
Same County
1965
84.5
78.8
76.8
85.7
81.9
76.7
III-D-128
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Grundy is the only county which has exhibited any substantial change
in population since 1960. It has grown in size and experienced moderate
in-migration. Interestingly, this increase has been primarily to the
rural non-farm sector of the population. Morris, (8,194) the largest
town had grown only 3.3% by 1970 while the farm population decreased
sharply during the same period.
Table III-D-57
IL-2 POPULATION SHIFTS
1960-70 1970-74
Tot. Pop. Farm Pop. Migration Tot. Pop. Migration
Iroguois
Livingston
Grundy
LaSalle
Marshall
DeWi tt
-.1
.9
18.7
.5
-.2
-1.6
-16.3
-25.6
-33.5
-18.0
-21.1
-27.3
-6.5
-5.6
8.8
-7.1
-5.2
-5.6
-.8
0.2
3.7
-2.2
-1.5
-1.3
-2.2
-1.2
0.3
-3.5
-2.3
-2.0
The other five counties maintained their population at a relatively stable!
level in spite of small losses from out-migration. They also show people
moving out of the farming sector.
6.2.3. AGE STRUCTURE
None of these counties is characterized by an unusually young or an
unusually old population. There are relatively few in the older age
cohorts in Grundy County. Grundy, Livingston, and DeWitt Counties do
not exhibit the sharp decline in relative numbers for young adult cohorts
which is evident in the other three counties. Since the presence of a
sizeable college population does not account for the differences in the
age profiles, this characteristic will be considered again when examining
economic activities. Median ages are:
Iroquois 31.7
Livingston 29.1
Grundy 28.6
LaSalle 35.4
Marshall 32.4
DeWitt 32.7
6.2.4 MARITAL STRUCTURE
Relatively high (exception: LaSalle) percentages of the families
in these counties are intact. Considering that relatively high numbers
(exception: Grundy) of men are married, that there are few single women
(exception: LaSalle) or divorced people, and the median ages are not
particularly high, this would be expected. Consequently, there are
relatively few families with female heads. The higher than average per-
centages of families in Grundy County with children under 18 is most
likely due to the slightly lower median age.
III-D-129
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6.2.5 EDUCATION
There is no substantial college populations in any of these counties.
Most people have finished high school and the median number of school years
completed is over 12. Somewhat less than 8% of the population has completed
college.
6.2.6. HOUSING
Trends on population growth are consistent'with the housing trends.
Grundy is the only county with substantial gains in numbers of households
and housing units. Consequently, the median house value and rent are
somewhat higher in this county and percentages of single unit dwellings
lower. It should be noted that, for the ORBES Region, this area has
relatively high valuations for single family dwellings and for median
rents. All the counties have low (less that 6%) percentages of their
housing units which lack some plumbing. Approximately a third of the
units are rented in this area.
Table III-D-58
IL-2 HOUSING - 1970
Changes 1960-70
Households Units
One-unit
Structures
% Built
Since 1960
Iroquois
Livingston
Grundy
LaSalle
Marshall
DeWitt
3.9
5.7
22.2
5.2
3.8
3.1
5.5
6.5
22.4
6.0
4.4
.7
89.7
86.3
79.8
82.2
89.8
84.6
13.0
15.7
26.1
13.5
15.4
14.0
Iroquois
Livingston
Grundy
LaSalle
Marshall
DeWitt
% Home
Owners
69.3
68.3
68.0
73.1
71.4
67.9
Med.
Value
$12,201
13,913
17,081
14,493
12,857
11,718
Med.
Rent
$ 97
107
124
100
96
87
% Lacking
Plumbing
2,9
2.1
2.7
3.1
4.4
5.4
III-D-130
-------
6.2.7. ECONOMIC ACTIVITIES
The farmland in these counties is among the most valuable in the
ORBES region. Return per acre is high or relatively so, a large
proportion of the farms fall into the Class I-V categories, few farmers
in these counties work off the farm and farm acreage has been growing
in four of the counties. The other two counties experienced only small
losses. Simultaneously the number of farms has been falling (except
for Grundy County) indicating a trend towards farm consolidation. Cash
grain farms are the most important type of farming operation, providing
approximately 70% of farm income. Livestock raising is second in im-
portance and there are a few dairy and poultry farms.
Changes 1964-9
FarmsAcreage
Table III-D-59
IL-2 FARMING, 1969
Ave. Value
Per Acre
Ave. Return
Per Acre
Iroquois
Livingston
Grundy
LaSalle
Marshall
DeWitt
-3.8
-1.7
1.2
-1.6
•12.6
-5.7
1.0
.9
2.7
.9
-3.3
- .4
$542
582
597
583
546
620
$91
92
70
98
96
82
Number
Iroquois
Livingston
Grundy
LaSalle
Marshall
DeWitt
Iroquois
Livingston
Grundy
LaSalle
Marshall
DeWi tt
2,
2,
248
120
754
466
745
753
163
192
73
254
54
124
Class I-V Farms
Ave. Acres
300
298
305
262
288
318
Other Farms
50
45
77
67
63
43
Ave. Return
$27,526
27,677
21,619
26,152
27,985
26,582
$1,135
1,603
1,123
1,032
885
1,092
-------
Except for LaSalle County, all of these counties have more working
residents than workers working in the county, that is, some residents
must commute out for work. This is reflected in numbers of jobs listed
in County Business Patterns relative to the population. Over 40% of
the jobs in LaSalle County are in manufacturing: 1) stone, clay and
glass products; 2) machinery; 3) chemicals; 4) paper products;
5) electrical equipment; 6) printing and publishing; 7) instruments;
8) fabricated metal products; 9) primary metal; 10) transportation
equipment; 11) apparel and textile products; and 12) food. There are
also substantial numbers employed in trade and services.
Table IH-0-60
IL-2 COUNTY BUSINESS PATTERNS, 1973
Iroquois
Livingston
Grundy
LaSalle
Marshall
DeWitt
Total Pop.
33,352
40,690
26,535
111,409
13,302
16,975
in CBP
5,820
9,472
6,877
33,130
2,369
3,051
Manufacturing
2,108
3,655
2,924
14,711
965
793
Construction
242
556
541
1,416
103
238
Iroquois
Livingston
Grundy
LaSalle
Marshall
DeWi tt
Agric.
7
30
58
12
Mining
134
539
Trans-
portation
191
534
516
1,855
185
252
Trade
2,147
2,594
1,772
8,309
749
1,129
Finance
254
317
230
1,012
93
138
Services
819
1,625
769
5,179
222
480
Although the magnitude is much less, manufacturing is also the primary
economic activity in both Grundy and Marshall Counties. Grundy County
industries produce: 1) paper products, 2) apparel, 3) chemicals, 4) rubber
products, primary metal, and 6)electric equipment. Marshall County
industries produce: 1) chemicals and 2) apparel or textile products. The
amount of construction in Grundy, it should be noted, is almost as large
as that in Livingston County which has a much larger population.
Jobs in DeWitt County are primarily in trade but there are small
manufacturing industries dealing in;l) printing and publishing, 2) pri-
mary metals, and 3) fabricated metals.
III-D-132
-------
Iroquois and Livingston Counties have manufacturing activity on a
level with that in Grundy County even though manufacturing does not
involve as large a proportion of the work force. Iroquois had in-
dustries producing: 1) electric equipment; 2) food; 3) lumber and
wood products, and 4) printing. Livingston has: 1) fabricated metals;
2) printing; and 3) electric equipment.
Livingston also has a few people involved in mining, as does
LaSalle County.
The only amplification of this picture offered by examination of
the labor force figures relate to women in the work force. Relatively
high numbers of women in Livingston County work and in both Livingston
and DeWitt Counties, relatively high percentages of families have both
husband and wife in the work force.
6.2.8. INCOME
All of these counties are part of the relatively affluent northern
ORBES region. The median family and per capita incomes for Grundy County
appear to be slightly higher than for the other counties. Although the
per capita income figures for 1973 do not show a continuation of this
pattern, 1974 Sales Management figures do show that Grundy County resi-
dents have somewhat higher "effective buying power" per family than do
the other counties.
It should also be noted that the median income for farm families is
somewhat higher in DeWitt County.
Table III-D-61
IL-2 INCOME
Med. Fam. 1969 Per Capita Income EBI
Total Farm 1969 1973 1974
Iroquois 8,723 7,864 3,452 5,906 10,240
Livingston 9,611 9,203 3,501 5,504 11,621
Grundy 10,982 9,833 4,098 5,587 14,468
LaSalle 9,953 9,451 3,813 5,299 12,355
Marshall 9,141 8,680 3,561 8,680 10,848
DeWitt 9,330 10,257 3,380 10,257 11,508
6.2.9 IMPACT ASSESSMENT
The prevailing environmental orientation in these Illinois Counties
(Iroquois, Livingston, DeWitt, Grundy, LaSalle and Marshall) while pri-
marily sentimental (prestige seems more important than primordial be-
longiness) have a strong instrumental orientation as well, as reflected
in the high economic returns afforded by the economic activity especially
in the more urban Grundy and LaSalle Counties.
III-D-133
-------
Farming in this area is a highly instrumental activity which yields
not only economic benefit but prestige as well. Acceptance of power
plant development would probably be highest in Grundy and LaSalle Counties.
With the exception of Iroquois County, no or minimal boomtown effects
would be expected, given the nearness of skilled worker population in
the urban areas and the economic diversification and affluence of the
smaller towns. It is expected that in all these counties, were prime
expensive farmland required for power plant development, there would be
some opposition from farmers. However, again except for Iroquois
County, these counties would seem likely to be receptive to further
development.
III-D-T34.
-------
6.3. FULTON (41,890), SCHUYLER (8,135), BROWN (5,586), CASS (14,219),
SCOTT (6,096), GREENE (17,014), AND JERSEY (18,492) COUNTIES
Along the Illinois River between Peoria and St. Louis, is a string
of counties slated for power development before A.D. 2000. Fulton,
the largest and most populous, has a new coal-fired, three-unit power
plant at Canton. The first unit (400 megawatts) was scheduled to go
into operation in 1976. The remaining two units (400 and 600 megawatts)
are scheduled to go into operation in 1979 and 1983 respectively.
At present Greene and Scott Counties each have very small power
plants (less than 3 megawatts each). These are the only generating
facilities in these counties.
Scenario I proposes placing one two-unit (2,000 megawatt) plant
in all counties except Fulton. The plant in Cass County would use
nuclear fuel, the remainder would be coal-fired.
Scenario II posits two two-unit nuclear plants, one to be built
in Cass and another in Greene County. Three two-unit coal-fired plants
would be built, one each in Brown, Greene and Jersey Counties.
Greene County will have the only plant under Scenario III, a
two-unit coal-fired plant, (600 megawatts per unit).
Although the residents of these seven counties could not be
described as isolated from urban centers, they are off of the main
transportation routes which cross Illinois. Also, although residents
have access to at least secondary urban centers, the distances they must
travel are, on the whole, further than for the residents of north-central
impact counties. *
Peoria lies up the Illinois River from Fulton County. The distance
between Canton (14,217) its largest town and that city is only 25
miles. Residents of the western part of the county are also very
close to Macomb (19,643) in neighboring McDonough County. Canton, site
of the plant, is in the eastern part of the county, however.
Residents of Schuyler, Brown and Cass Counties have relatively
easy access to Quincy (45,288), approximately 60 miles west of the
river and Springfield, approximately 50 miles east of the river. A
somewhat longer drive north, along-the river, will get the residents
to Peoria. Centrally located on the river for residents of all three
counties is Beardstown in Cass County. Beardstown (6,222) is the
largest community in these counties.
Scott, Greene and Jersey Counties are located between Jacksonville
(20,553) just over the county line in Morgan County and Alton (39,700)
at the northern edge of the St. Louis SMSA.
III-D-135
-------
6.3.1. LAND USE
Except for Fulton and Jersey Countie%, which are close to SMSA's,
over 90% of the land in these counties is devoted to farming.
For Illinois, these counties also have substantial proportions
of their acreages in forest, or at least they did in 1962. Of course,
it should be remembered that much of the forest land is counted as
part of the farm acreage.
A large amount of land in Jersey County is managed by the state
for recreational or conservation use. Fulton and Cass also have sizeable
acreages in state parks. In fact, numerous conservation and recrea-
tional areas are located along the Illinois River, especially along
the stretch between Peoria and Beardstown. In this region the river
has formed many small lakes in its wanderings and one would expect
many private recreational facilities as well.
All of these counties are underlain, at least in part, by coal
bearing rock. Fulton County, however, is the only one showing any
coal production in 1974, between 1.0 and 4.9 million short tons.
Table 111-62
IL-3 LAND USE
% of land in
farms, 1969
% of land in
forest, 1962
recreational
acreage, 1973
Fulton
Schuyler
Brown
Cass
Scott
Greene
Jersey
82.7
90.7
89.3
95.8
92.7
91.9
81.6
15.8
21.1
19.4
13.5
11.9
15.8
23.2
4,714
772
—
8,042
—
—
17,328
6.3.2. RESIDENCE
These are sparsely populated, residentially stable counties,
especially Brown and Schuyler. Among the counties, Jersey has exhibited
the most residential mobility and has been the only county to show
population growth since 1960. Fulton County has apparently reversed
the downward trend and has begun to gain very slightly in population.
The other counties experienced population decline and out-migration
during the sixties and these trends have continued although they appear
to be leveling off. As is characteristic of much of the ORBES region,
these losses appear to be disproportionately from the farm population
in all counties. e
III-D-136
-------
Table III-D-63
IL-3 RESIDENTIAL STABILITY
% residing in
birth state
1965 residence
same state
1965 residence
same county
Fulton
Schuyler
Brown
Cass
Scott
Greene
Jersey
85.7
89.4
91.8
84.8
88.7
88.1
82.2
92.6
95.2
95.2
92.4
92.5
94.3
91.3
83.9
83.4
84.5
82.4
78.6
85.8
78.5
Table III-D-64
IL-3 POPULATION SHIFTS
[total
1960-70
migration
farm population]
1970-74
[total migration]
Fulton
Schuyler
Brown
Cass
Scott
Greene
Jersey
-.1'
-7.0
-10.0
-2.2
-4.4
-2.6
8.6
-4.4
-8.7
-10.7
-6.0
-8.8
-5.8
.9
-26.7
-28.2
-32.8
-15.9
-21.5
-12.7
-26.7
1.3
-2.9
-1.9
-1.0
0.2
-2.3
2.9
0.3
-2.9
-1.0
-2.0
-0.1
2.3
1.0
The relative size of the farm population varies from about a third in
Brown and Schuyler Counties to less than a tenth of the population of
Cass County. It should be iterated that the density and urban percentage
reflect the location and distribution of the larger communities. The
density of the completely rural counties, when examined in conjunction
with the farm/non-farm distribution provides a rough picture of the
composition of the population outside local population concentrations.
Table III-D-65
IL-3. POPULATION DISTRIBUTION
Density
Farm
Non-farm
Urban
t
Fulton
Schuyler
Brown
Cass
Scott
Greene
Jersey
48
19
18
38
24
31
49
19
, 36
33
8
29 ,
24
16
33
23
67
48
71
42'
44
48
41
0
44
0
34
40
III-D-W
-------
The low percentage of the population living on farms in Cass County
poses some interesting questions. In spite of the percentage differences,
there are similar numbers of farms in this and in Brown and Schuyler
Counties which are about the same in size. Even if you discount the
presence of Beardstown, the farm population only comprises about 15%
of the population. The higher density along with the above factors
indicates that in this county more people can be supported in small
communities or in the open countryside than in the neighboring rural
counties.
6.3.3. AGE STRUCTURE
Median age in all but Jersey County is high or relatively high
with correspondingly few young adults and children in the population.
Schuyler, Brown, Scott and Greene Counties have noticeably high pro-
portions of those in the 40-*plus age cohorts. Jersey County, on the
other hand, has a population which is concentrated in young adult and
early middle age groups. Since there is only a small (746) resident
college population in Jersey County, most of these young adults must
be in the labor force. The sharp decline in size of age cohorts after
the teens is not so marked in Cass County as in the others. Median
ages are:
Fulton 33.1
Schuyler 37.2
Brown 38.2
Cass 33.4
Scott 34.6
Greene 33.8
Jersey 27.9
6.3.4. MARITAL STRUCTURE
In all but Jersey County there are low percentages of single
women and relatively low percentages of single men in the adult
population. Remembering the lower median age, the patterns of popu-
lation growth and migration, it is clear that Jersey County must be
considered separately. This county does have relatively high per-
centages of both married men and women as well as higher than average
percentage of families with children under 18. Relative numbers of
widowed men and women are about average. Neither divorced men nor
women seem to be attracted to this county and consequently there are
relatively few families with a female head and relatively large numbers
of intact families.
III-D-TOa
-------
The pattern clearly indicates,a predominance of families in the
early and middle stages of the family cycle, possibly because in-
migrants would tend to fall into this category and the young adults
are not leaving in the proportions thay they are in other counties.
Fulton, Schuyler and Brown also have relatively large numbers of
intact families and consequently few families with female heads. These
families are probably further along in the family cycle for the most
part since few of these families have children under 18. Of course,
considering the older median age, these counties have average or higher
percentages of the widowed in their populations.
Cass, Scott and Greene Counties exhibit a few unexplained anomalies.
They are part of a cluster of counties in Illinois having especially low
percentages of males in the adult populations. Since this is likely to
be a consequence of disproportional out-migration of young males, one
would expect effects on the marital structure but there does not appear
to be a clearly discernable pattern of marital structure in these
counties. Cass and Greene are somewhat similar in that both show high
or relatively high percentages of married and widowed males. Cass
County also has relatively large numbers of divorced males, indicating
that most of the males who remain in the county marry. The men in
Scott County do not seem as likely to marry as evidenced by the low
percentages of widowed and the only average percentages of the married
and divorced, and the few families with children under 18. Higher
than average percentages of women do marry, however, posing still
further questions.
6.3.5. EDUCATION
Educational levels in these seven counties are lower than in the
northern half of the state. In all counties the median school years
completed averages less than 12 years. Less than half of the popu-
lation has finished high school and less than 6% have completed
college.
6.3.6. HOUSING
Two of the counties, Schuyler and Brown have had decreases in
both numbers of households and housing units during the sixties, while
the other counties, with the exception of Jersey, have remained
relatively stable. These figures correspond well with population
shifts. The building rate for new housing units is consistent with
this apparently %table housing market.
III-D-139
-------
Table III-D-66
IL-3 HOUSING,
Changes 1960-70:
Households, 1960-70
Housing units change 1960-70
Average :
Median value
Median rent
%Units:
% One-unit structures
% Units built since 1960
% Owners occupied
% Lack some plumbing
Fulton
3.7
4.7
10,321
89
85.1
13.2
75.1
8.0
Schuyler
-3.0
-2.8
10,348
81
89.1
10.9
71.5
15.4
1970
Brown
-6.8
-6.1
9,360
73
94.5
7.8
73.3
14.7
Cass
1.6
.8
9,312
88
83.4
12.3
72.4
6.8
Scott
-0.8
7.0
9,150
71
92.0
12.3
69.0
12.6
Greene
2.0
4.6
8,423
72
90.2
11.5
71.1
12.8
Jersey
12.6
25.5
11,954
87
90.0
19.9
76.6
10.9
I
o
-------
The higher rents and home values are to be expected in Fulton and
Jersey Counties but are a surprise for Schuyler County. It should be
noted that for Illinois, even these higher figures are only average
and housing values for the other counties are low. The units lacking
some plumbing facilities is relatively high for Illinois in all but
Fulton and Cass Counties.
6.3.7. ECONOMIC ACTIVITIES
The farmland in this area, although relatively high in value for
the ORBES region, is only about average for Illinois. Farming appears
to be a full time activity for most farmers (except for those in
Jersey County). Farming is a reasonably profitable activity and in
two counties, Cass and Scott, the average return per farm is high.
Farming operations are fairly evenly balanced between livestock raising
and cash grain crops, the former predominating.
Table III-D-67
IL-3 FARMING, 1969
* Fulton Schuyler Brown Cass Scott Greene Jersey
Change 1964-69:
Farms -6.8
Acreage - .9
Average:
Land value 325
Return per acre 72
Class I-V Farms:
Number 1,419
Avg. acres 311
Avg. return 23,350
Other Farms:
Number 353
Avg. acres 63
Avg. return 1,117
-12.2 -5.9 -3.2
.4 - .3 2.3
266
66
252 385
91 84
-2.6
-2.5
337
74
-7.5
343
106
3.3
1.7
395
76
685 510 616 433 951 620
348 308 360 330 325 296
23,992 19,469 30,788 25,364 35,436 23,549
125 128 87 86
107 94 60 72
1,208 1,068 1,141 1,090
179 222
56 58
'1,218 1,017
Clearly this area also exhibits the trend towards farm consolidation,
most markedly in Schuyler where, it can be noted, the average value
of the farm land and buildings is lower than in most of the other
counties.
#
•> Non-agricultural jobs are primarily in retail trade in Schuyler,
Brown, Scott, Greene and Jersey Counties. Workers in the various
categories are more evenly distributed in Fulton and Cass Counties.
III-D-141
-------
I
o
Table III-D-68
IL-3 COUNTY BUSINESS PATTERNS, 1973
Fulton
Schuyler
Brown
Cass
Scott
Greene
Jersey
Population
In CBP
Agriculture
Mining
Construction
Manufacturing
Transportation
Trade
Finance
Services
41 ,890
8,042
9
669
221
2,840
303
2,189
318
1,458
8,135
980
98
151
40
433
35
159
5,586
654
11
25
68
297
40
180
14,219
3,048
97
1,195
361
903
112
363
6,096
920
162
77
123
469
41
29
17,014
1,765
12
35
393
43
752
126
385
18,492
1,825
46
166
201
699
121
584
-------
All of these counties have significant proportions of their popu-
lation who must commute out for work. It appears that fewer in Cass
County would have to do so than in Greene or Jersey. Cass has fewer
residents and more jobs listed in County Business Patterns. This
finding accords well with the less marked declines in the relative
sizes of the young adult age cohorts mentioned earlier for Cass County.
Clearly only two of the counties, Fulton and Cass, have substantial
manufacturing activity. Fulton County has industries producing: 1)
apparel and textile products, 2) machinery, and 3) transport equipment.
Cass County has 1) food and 2) machinery industries. Industrial activity
in Greene County revolves around 1) apparel and 2) paper industries.
Jersey County produces some transportation equipment. As mentioned
earlier when discussing land use, only Fulton County has a significant
amount of mining.
6.3.8. INCOME
Income levels in these counties are about average or slightly
above the ORBES region, with Brown County having somewhat lower income
levels than the other counties, and somewhat higher percentages of
those below poverty level. By 1973 there appears to have been some
shifts within this area. Scott County, and possibly Jersey County,
appear to have pulled ahead of the other counties in income levels.
Table III-D-69
IL-3 INCOME LEVELS
1969 Median
Family
1969 Median
Farm Family
1969
Per capita
1973
Per capita
1974 Median
Family EBI
Fulton
Schuyler
Brown
Cass
Scott
Greene
Jersey
£8,619
7,556
6,024
7,795
7,353
7,380
8,402
$7,840
7,753
5,929
7,406
6,662
7,352
7,088
$3,228
2,960
2,688
3,444
3,424
3,048
2,981
$5,386
6,111
5,406
5,944
6,276
5,547
4,324
$10
10
8
9,
11
8
124
040
407
368
068
020
11,015
6.3.9. IMPACT ASSESSMENT
In Fulton, Schuyler, Brown, Cass, Scott, Greene and Jersey Counties
along the Illinois River, a mix of environmental orientations is present
in these prime power plant sites. Fulton and Jersey Counties, bordering
SMSA's, have a primarily instrumental orientation while the remaining
counties may be generally classified as sentimental, with emphasis on
the prestige Hub-orientation. Fulton, a coal-producing area near to
Peoria, with an economically diversified infrastructure, should easily
absorb power plant development and its residents be favorably disposed
III-D-143
-------
toward development. This should be generally true of Jersey County as
well, however, their population might be even more positive, given its
youthful age structure. Its ability to benefit is also slightly greater.
The remaining rural counties, with the exception of Brown County
(discussed below), being economically fairly well off, quite rural and
isolated (except for Cass County) from urban centers and major trans-
portation lines, have a primarily sentimental orientation toward the
environment, and its older population suggests a strong primordial
belongingness sub-orientation. Farming, with its business emphasis,
is a strong instrumental activity here, as in the rest of Illinois,
creating a mix of orientations. However, all these counties (except
Cass possibly, because of its nearness to Springfield) would be candi-
dates for a fairly severe boomtown syndrome. Given the nature of the
population and their orientations, it seems likely that power plant
development would not be welcome here and considerable opposition
expected. Moreover, the economic infrastructure and the size of possible
recipient communities suggest difficulties in coping with boomtown
strains.
Brown County, the poorest of this group and with a high proportion
of older people and a strong attachment to place, would also be subject
to what we just discussed above, however, its ability to cope would be
even less and fewer benefits from plant construction would accrue to
its residents for they are not of the proper age to benefit.
III-D-144
-------
6.4. ST CLAIR (285,176), WASHINGTON (13,780), AND PERRY (1.9,757) COUNTIES
Three counties east-southeast of St. Louis are slated for new power
generating facilities under the high energy scenarios.
St. Clair, the populous county containing East St. Louis,would re-
ceive a low BTU coal conversion plant. Perry County would receive a high
BTU coal conversion plant as well as a single unit coal-fired (1,000
megawatt) power plant under Scenario II. Washington County, located be-
tween these two counties, would have a two-unit coal-fired power plant
under both Scenarios I and II.
At present St. Clair has power generating facilities totaling less
than 145 megawatts, while Perry and Washington Counties have no power
plants.
St. Clair County, bordering the Mississippi River, is part of the
St. Louis SMSA. Directly east is rural Washington County, having only
one sizable community, Nashville (3,027). Most residents of this
county, at least ifi the western half, would have direct routes to the
SMSA by Highways 64 or 460 and less than 50 miles to drive. The
Kaskaskia River runs along the northern border of Washington County and
if a plant were sited along this river in the Western half of the county,
access to the SMSA would be even better than described above. In the
eastern half of the county, any development would be likely to have
direct impact upon Centralia (15,217), just across the county line be-
tween Marion and Clinton Counties.
Perry County, just south of Washington County, has two sizable
communities, Du Quoin (6,691) and Pinckneyville (3,377), both located
in the center of the county 6 miles apart on State Highway 127. Resi-
dents of these communities are about 60 miles from the St. Louis urban
areas but less than 25 miles south are Murphysboro (10,013) and Carbon-
dale (22,816) in Jackson County.
The residents of all three counties are well located for easy
access to outdoor recreation facilities. In addition to the Shawnee
National Forest with its northern edge in Jackson County, there are
two large lakes nearby (Carlyle and Rend) with several state parks
attached, and there are numerous other state parks and conservation
areas in these and nearby counties.
6.4.1. LAND USE
Washington County has over 90% of its land in farms, but the
proportions in Perry and St. Clair Counties are close to three-fourths.
Perry County has slightly more land in forest (22% as opposed to 14%
III-D-145
-------
for the other two counties). Each of the countieslias some recreational
acreage as well:
St. Clair 1,129 acres
Washington 1,383 "
Perry 2,525
All three counties are underlain by coal bearing rock but only in
St. Clair and Perry Counties was coal produced during 1974. All three
counties produced some petroleum as well and in St. Clair County over
3,259,000 short tons of sand and gravel were quarried.
Urban related uses of land in St. Clair County must be relatively
large.
6.4.2. RESIDENCE
All three counties experienced moderate to small gains in popu-
lation during the sixties although in St. Clair County the growth
occurred in spite of a low level of out-migration. Since 1970, the out-
migration rate has accelerated so the population is now falling. Growth
in Washington County, on the other hand, has accelerated since 1970.
As in most counties in the ORBES region, the farm sector is declining.
The trend is especially rapid in Perry County (-35.3) as opposed to St.
Clair (-12.7) and Washington (-14.6) counties.
Table III-D-70
IL-4 POPULATION SHIFTS
St. Clair Washington Perry
1960-70
Pop. Change 8.6 1.6 3.0
Net Migration -3.3 1.1 .2
1970-74
Pop. Change -1.7 5.1 1.6
Net Migration -5.2 6.1 0.4
St. Clair, as might be expected in an urban county, has fewer
residents who are natives of Illinois and higher levels of residential
mobility than the other two counties.
III-D-146
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Table III-D-71
IL-4 RESIDENTIAL STABILITY
St. Clair Washington Perry
% Residing in:
Birth state 61.7 89.6 88.3
Same state, 1965 83.1 95.5 93.3
Same county, 1965 79.6 83.6 84.8
The distribution of the population among the residential sectors
varies among these three counties. St. Clair is overwhelmingly urban
with a very small percentage of the population living on farms. Approxi-
mately a third of Washington County residents live on farms, about a
fifth in the one town and the rest in small villages or in the open
countryside. Just over a half of Perry County's residents live in
small towns. The rest are distributed about two to one between rural
non-farm and rural farm residences. Taking into consideration the
numbers of farms and the density, after correcting for the location
of the towns, it appears that the rural populations are similar in
Washington (19 per sq. mile) and Perry (22 per sq. mile) Counties.
Both of these counties contrast sharply with densely urban St. Clair
County.
Table III-D-72
IL-4 POPULATION DISTRIBUTION
St. Clair Washington Perry
Density per sq. mi. 424 24 45
% urban 83 22 51
% rural non-farm 14 43 34
% rural farm 3 35 15
6.4.3 AGE STRUCTURE
Washington and Perry Counties contrast with St. Clair County in
median age:
St. Clair 26.9
Washington 37.9
Perry 35.2
The pattern of relatively large numbers of the elderly and few children,
though true for both Perry and Washington, are especially marked for
Washington County. St. Clair County, on the contrary, has relatively
more children and young adults and numbers in the older age cohorts
decrease"rapidly. The largest adult cohort for both Washington and
Perry Counties is that for people between 55 and 59. The largest
cohort for St. Clair County is for those aged 40 and 45.
III-D-147
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6.4.4. MARITAL STRUCTURE
As a consequence of the young population of St. Clair County, there
are few widows and relatively large numbers of families with children
under 18. A low percentage of families are intact, however, and re-
latively large percentage of families have female heads. This is
apparently due to the high percentage of divorced women in this county.
The low percentage of adult males in this county indicates that re-
marriage is less likely for these women.
Washington County, on the other hand, has relatively few divorced
women and relatively low percentages of families with a female head.
There are few divorced men in this population as well. Most men and
average numbers of women marry, but because of the older population,
high percentages (especially of men) are widowed and low percentages of
families have children under 18.
The marital structure of Perry County is similar to that in Wash-
ington except that distributions are somewhat closer to average. There
is, however, a relatively low percentage of adult men, especially single
ones, in the population. In general, these two rural counties are
characterized by families in later stages of the family cycle with the
attendant larger numbers of the widowed and families without children
living at home.
6.4.5 EDUCATION
Educational levels for these counties range from moderate (St.
Clair) to relatively low. The median number of school years completed,
even for St. Clair County is less than 12. In spite of a young popu-
lation, a resident college population of 7,283, and the urban character
of this county, 57% of the population has not completed high school, and
less than 7% have completed college. The other counties, as expected,
have even lower levels. Over 60% of the population in these counties
are without high school diplomas and only 4% have completed college.
6.4.6 HOUSING
Small gains in numbers of households and housing units and moderate
levels of building activity are in line with population changes in
Washington and Perry counties during the sixties. The relatively high
percentages of one-unit structures, home-owners, and units lacking
plumbing (for Illinois) are expected in these rural southern counties.
The house values and rents, although lower than in St. Clair County,
are not out of line with those in the north western parts of Illinois.
III-D-148
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Table III-D-73
IL-4 HOUSING - 1970
St. Clair Washington Perry
% Change 1960-70
Households 11.4 4.8 6.8
House units 12.1 9.6 7.4
% of Units:
One-unit structure 75.3 91.3 87.2
Built since '60 21.2 15.2 14.3
Home owners 67.2 77.1 79.8
Lacking plumbing 5.3 16.4 13.1
Average:
Median value $12,970 $10,118 $9,877
Median rent 107 70 77
St. Clair, in spite of a population decline, has shown an increase
in numbers of households and housing units, indicating a breaking up of
household units. There has also been relatively more building activity.
In character with the more urban environment, fewer units are occupied
by the owner, fewer are in^one-unit structures,and fewer lack some
plumbing.
6.4.7 ECONOMIC ACTIVITIES '
St. Clair County, of course, has the highest level of economic
activity in all categories and it is diversified. The three major
types of manufacturing activity in this county are related to:
1) primary metals, 2) chemicals, and 3) foods. There is also manu-
facturing relating to: 4) apparel and textile products, 5) paper
products, 6) printing and publishing, 7) leather products, 8) stone,
clay and glass products, 9) fabricated metal products,and 10) electri-
cal equipment.
Perry County's economic activity is centered around manufacturing,
the major industry producing 1) food products, with smaller industries
dealing in: 1) apparel, 2) primary metals, 3) fabricated metals, and
4) electric equipment. '
Washington County, for its size, has very few non-agricultural
jobs, and they are varied. Small industries produce 1) food and
2) machinery.
All three counties have out-commuting, ranging from 21% (Perry)
to 33% (St. Clair).
-------
Table III-D-74
IL-COUNTY BUSINESS PATTERNS - 1973
St. Clair Washington Perry
Tot. Pop. 285,176 13,780 19,757
In CBP 51,849 1,810 5,031
Agriculture 124
Mining 602 116
Construction 3,419 86 275
Manufacturing 14,116 314 2,607
Transportation 4,052 109 154
Trade 13,784 617 947
Finance 2,854 112 120
Services 12,702 435 674
It is consistent with what we know of the age and marital struc-
tures of these counties that females form a relatively high percentage
of the work force in St. ClairCounty and that there are fewer than
average numbers of working wives in Washington and Perry Counties.
All three counties had some farm consolidation during the late
sixties. For those who have potentially full-time farming operations
(Class I-V) farming appears to be a viable economic activity. It should
be noted, however, that a much smaller proportion of farms are potenti-
ally full-time in Perry County. Consistent with this figure is the
larger percentage in that county who work at least 100 days off the farm
per year. Perhaps this is related to the different balance of farming
operations in this county, since there seems to be little difference in
average return per farm.
Slightly over half of the Class I-V farms in Perry County are de-
voted to either livestock or dairy farming, both labor intensive ope-
rations, which earn 68% of the return from farming. These figures
indicate that cash grain crops may be relatively unprofitable in this
county. Unwillingness or inability to commit the labor necessary for
a full time viable farming operation and possibly the presence of
options for economic activity may be factors contributing to the
larger numbers of farmers working off the farm (50.3) and the low
proportion of Class I-V Farms.
Farms in St. Clair County are smaller, but the return per acre is
higher than in the^other two counties. A factor which may be keeping
down number of Class VI and part-time farms in this county is the
high cost of farm land. This may also encourage more intensive
practices, thus providing a higher return per acre.
III-D-150
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Table VII-75
IL-4 FARMING 1969
St. Clair Washington Perry
Changes 1964-69
Farms -2.7 -3.8 -4.6
Acreage .8 1.3 -1.2
Class I-V farms:
Number 1,267 1,065 564
Avg. acres 234 283 333
Avg. return $17,702 $16,927 $17,520
Other Farms
Number 395 321 367
Avg. acres 46 76 80
Avg. return $1,115 $1,173 $1,052
Average value land
& building per acre 501 297 251
Average return per acre 73 57 47
Farming operations:
Cash grain nos. 720 469 233
% cash grain ret. 54% 41% 31%
Dairy nos. 56 210 36
% Dairy ret. 6% 21% 7%
Livestock nos. 347 276 258
% Livestock ret. 33% 33% 61%
6.4.8. INCOME
Median family income in 1969 and 1974 EBI figures place St. Clair
County above average and the other two counties about in the middle for
the region. Per capita incomes for both 1969 and 1973 are very close
for all three counties, however. Increases in family income as
measured by "effective buying power" may indicate the greater numbers
of women in the labor force in urban St. Clair County.
III-D-151
-------
Table III-D-76
IL-4 INCOME
St. Clair Washington Perry
Family:
1969 Medium 9,540 7,577 7,880
1969 Farm Med. 8,914 7,163 7,238
1974 EBI 11,833 8,709 8,771
Per Capita:
1969 3,210 2,939 3,163
1973 4,386 4,805 4,693
6.4.9 IMPACT ASSESSMENT
The Illinois counties of St. Clair, Washington and Perry, while
in geographical proximity vary widely in likely environmental orien-
tations, though the latter two are quite similar.
St. Clair, urban and urbanizing, may be characterized as in-
strumental in orientation with a heavy emphasis on the economic benefit
sub-orientation. Being a coal-producing county, it is a logical site
for coal conversion and coal-fired power plants. Moreover, unless the
plants are sited in the eastern part of the state, no boom town syndrome
would be expected given the proximity of St. Louis. Even if a plant
were cited in the eastern part, Centralia would probably be the focus
of boom effects and leave the county unaffected. Given these con-
ditions, we would expect plant siting and development to be unprob-
lematic and welcomed by residents of the county.
Washington and Perry counties represent the sentimental orien-
tation, though the primordial belonginess sub-orientation would be
much stronger in Washington County, given the percentage of land in
farms and the elderliness of the population. High incomes for both
counties indicate the prestige sub-orientation is present as well.
Perry County, a coal-producing county, 60 miles from St. Louis,
seems a more receptive site than Washington County. However, the
aesthetic sub-orientation is there as well, given the recreational
and forested areas. The movement from farm to rural non-farm and the
decline in land devoted to farming suggest that land for plant siting
would be readily available. We suggest that public opinion would be
split about the desirability of a plant, because the older population
and rural population are generally not favorable to such development.
The nearness to St. Louis on the other hand, suggests urban influences
and receptivity to development.
III-D-152
-------
Washington County would seem to be non-receptive to power-plant
development since it is highly agrarian in nature and likely subject to
boomtown conditions with which it is unprepared to cope, since it lacks
economic diversification. Its location on a major interstate might
allow for commuting workers, thus mitigating some boom effects. By
and large, however, the county's characteristics would indicate nega-
tivity about that kind of development.
III-D-153
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6.5 PULASKI COUNTY (8,741)
At the southwestern tip of Illinois, Pulaski County is slated to
receive a 2 unit coal fired power plant under either of the high energy
scenarios. There are no power generating facilities in the county at
the present time.
This small county is located above the confluence of the Ohio
and Mississippi Rivers. Interstate Highway 57 will cross the river
into Missouri at this point. At present U.S. Highway 51 crosses into
Kentucky and U.S. Highway 62 forks into Missouri at the confluence.
In this southern part of the county where both rivers and highways
converge are the two major towns in the county, Mounds (1718) and Mound
City (1177). The closest Illinois towns of any size are Anna (4766)
37 miles north in Union County, and Marion (11, 724) 57 miles north
in Williamson County. Cape Girardeau, Missouri, is only a little over
30 miles north west of Mounds and Mound City is connected directly by
State Highway 3. Paducah, Kentucky, only a little further to the east,
is probably not an urban center that would be visited frequently by any
but the residents of the eastern parts of the county because of in-
direct highway access.
Pulaski County is almost surrounded by recreational areas. The
Shawnee National Forest stretches from neighboring Alexander County in
a semi-circle through Union, Johnson, Pope and Hardin Counties. There
are also many parks, conservation areas and wild life refuges in this
area. In addition, just south of Paducah in Kentucky is the large
"Land Between the Lakes" recreation area. One would also expect that
the rivers would provide water recreation facilities.
6.5.1. LAND USE
Smaller proportion of the land is devoted to farming in the
southern Illinois Counties than in the northern part of the state.
In Pulaski, 60% of the land is in farms. Slightly less than a
quarter of the land is forested. Pulaski County is outside the
areas of coal and oil production but there is a small amount of
quarrying of clay, stone, sand and gravel.
6.5.2. RESIDENCE
This county is predominantly rural, non-farm (84%). Only 16%
live on farms and this sector has been declining rapidly (-62.7% be-
tween 1960 and 1970). The population in general has been declining
as well, although not as rapidly as the farm sector. Between 1960 and
1970 the population decline by over 16% with out-migration of over 19%.
Both towns declined in size as well (Mounds - 6.4, Mound City - 29.4).
Since 1970 the population appears to have stabilized with a growth of
0.6% and in-migration of slightly over 1%.
III-D-154
-------
As one would expect from its location, only 7'"!% of the residents
of Pulaski County were born in Illinois. Most of those born in other
states appear to be from southern states.
The population does not appear to be more mobile residentially,
however. Almost 90% of the residents lived in Illinois in 1965 and a
little over 81% lived in Pulaski County.
6.5.3. AGE STRUCTURE
Median age in this county is relatively high (34.2) with over 17%
of the population over 64. As a consequence, death rate is high. The
age profile is characterized by a very sharp decline in the size of age
cohorts older than 19. Consequently less than 17% of the population is
between 20 and 40. The middle aged and elderly are predominant in this
population.
6.5.4. MARITAL STRUCTURE
Following from the age structure, there are high percentages of
widowed men and women in the population and relatively low percentages
of families with children under 18 and few intact families. Higher
death rates among men combined with the above factors explain the low
percentage of adult males in the population and the high percentages
of families with female heads.
6.5.5. EDUCATION
»
Given the age structure, it is also not surprising that educational
levels in Pulaski County are among the lowest in Illinois, and more on
a par with rural Kentucky Counties. Over 68% of the population have
not finished high school and less than 4% have finished college. There
is a small community college, Shawnee, with an apparent enrollment of
126 Or less.
6.5.6. HOUSING
Along with the decline in population during the sixties was a
decline in the numbers of households (-9.9) and housing units (-12.0).
Few houses were built during this period (12.9%) although the per-
centage lacking some plumbing was relatively high (32.5), especially
for Illinois. Housing units are overwhelmingly in one-unit structures
(91%)* although only a little over two-thirds (69.9%) are owner
occupied. House values are low (median - $5,259) as are rents
(median - $51).
6.5.7. ECONOMIC ACTIVITIES
Pulaski^is one of the few counties where jobs related to providing
services comprise the largest type of economic activity. It is possible
that there are some public service institutions in this county but, if
III-D-155
-------
so, they have not been identified. A sizeable percentage of workers
(27.4) also commute out for work, many probably to Alexander County.
Table III-D-77
IL-5 COUNTY BUSINESS PATTERNS, 1973
Total Population 8,741
In CBP 1,266
Construction 77
Manufacturing 40
Transportation 86
Trade 251
Finance 37
Services 674
Farming operations in Pulaski County are about evenly divided be-
tween livestock raising and cash crops. As the following figures indi-
cate, farming, although not as profitable as in northern Illinois, is
a more viable activity than in much of Kentucky.
Table III-D-78
IL-5 FARMING, 1969
Average value of land & buildings per acre $355
Average return per acre 52
Class I-V Farms:
Number 253
Avg. acres 280
Avg. return $15,414
Other Farms:
Number 100
Avg. acres 76
Avg. return $1,450
Over a third of the farms are not potential full-time economic activities,
however. The probably marginal nature of farming in this county may
be indicated by the large decreases in both numbers of farms (-31.6) and
farm acreage (-25.9) during the sixties.
6.5.8. INCOME
Income in this, as in some of the other southern counties of
Illinois, is on a par with the neighboring Kentucky counties and is low.
Figures for 1973 and 1974 do not reflect any change in its relative
position. In 1969, median family income was $4931 and per capita in-
III-D-156
-------
come was $2,129. By 1973 the latter figure had increased to $2,958.
Farm family income was slightly higher than the median for all families
($5,423) but was still low. Median family EBI in 1974 was $4,316, one
of the lowest in the ORBES region.
6.5.9. IMPACT ASSESSMENT
Pulaski County, Illinois, in the heart of a rather large
recreational area, probably has a symbolic orientation to the envir-
onment. The elderliness of the population and mixed-origin character
suggest it is a retirement community and thus also characterized by
the primordial belongingness sub-orientation. It is poor, suggesting
perhaps, as in Eastern Kentucky, there is natural beauty to offset
the relative poverty of the area. Also, older people generally have
low incomes. Given these prevailing orientations, we would expect
considerable opposition to a power plant site in this county. More-
over, if our assessment of aesthetic qualities is correct, it seems
likely that outside environmentalists would join in an opposition
movement, increasing its effectiveness.
III-D- 1.&7
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6.6. HAMILTON (8,665), WHITE (17,312), LAWRENCE (17,522), JASPER (10,741),
AND CLARK (16,216) COUNTIES
Five counties in southeastern Illinois are slated for coal-fired
power plant development. Jasper County will have a three-unit (550
megawatts per unit) power plant located at Newton which will go into
operation in 1977, 1981 and 1984. By 1985 the power generating capacity
of Jasper County will equal 1,650 megawatts.
The other four counties will receive power plants under the high
energy scenarios. Under Scenario I a two-unit (2,000 megawatt) plant
will be built in each of the four counties: Hamilton, White, Lawrence,
and Clark. Under Scenario II two-unit plants will be built in Hamilton,
Lawrence and Clark.
At present, Hamilton, White and Clark have very small power
generating facilities totaling 4.6, 16.7 and 5.6 megawatts, respectively.
Lawrence and Jasper Counties have no generating facilities.
White, Lawrence and Clark all border on the Wabash River and each
is fairly close to a major urban area in Indiana.
A little over a third of the residents of White County live in
the major town, Carmi (6,033), in the center of the county. There is
one other town, Norris City (1.319), and the rest of the people live
in the countryside or in places smaller than 1,000. Carmi is 42 miles
west of Evansville, Indiana, but the distance from the river to Evanesville
is less than 30 miles. A plant sited along the river could be within
commuting distance from parts of this city. There are no comparably
sized Illinois cities in the area. Mt. Vernon (15,980) in Jefferson
County, 48 miles from Carmi, and Marion (11,724) about the same distance
in Williamson County are the closest sizeable towns.
Vincennes, Indiana, is just across the river from Lawrence County,
and is 11 miles from Lawrenceville (5,863) the major town in the county.
Lawrence County has two other communities with over 1,000 residents:
Bridgeport (2,262) and Sumner (1,201). The surrounding counties show
similar population distributions: one sizeable and several smaller
communities, but no cities.
Clark County is close to Terre Haute, Indiana, but it also is
located on the fringes of the urbanized swath across northern Illinois.
Clark County itself only has three communities with over 1,000: Marshall
(3,468), Casey (2,994), and Martinsville (1,374). Terre Haute is only
16 miles east and Effingham (9,468) and Danville (42,570) are each
about 50 miles away.
III-D-158
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Hamilton County, just west of White, has one small town of less
than 3,000, McLeansboro, located at the junction of the several high-
ways crossing the county. Approximately 25 miles in any direction are
regional population centers: Carmi (20 miles east), Mt. Vernon (15,980,
28 miles northwest), Benton (6,833, 24 miles west), and Harrisburg
(9,535, 33 miles south).
Jasper County, southwest of Clark County, like Hamilton, has only
one sizeable community, Newton (3,024), site of the new plant. Newton
is only 24 miles southeast of Effingham (9,458) and 37 miles south of
Charleston (16,421). Although only Effingham and Terre Haut are close
enough to provide commuting workers, both these large towns are on the
major highway networks that characterize the northern Illinois urban-
ized strip.
Although these five counties are not contiguous, they are all
part of an area along the Wabash River which, according to our socio-
graphic maps seems to have some unity. In addition, the counties can
be characterized as being off the major transportation routes through
the state, and the major urban areas in Illinois. Although not isolated,
access to urban amenities, for many of the residents, may involve
crossing into Indiana at one of the infrequent bridges along this
stretch of the river.
Residents of the southern two counties, Hamilton and White, may
have easy access to the recreation areas in the Shawnee National
Forest about 30 miles south or those around Lake Rend to the west in
Jefferson and Franklin Counties. The residents of the other counties
are not as well placed for easy access to outdoor recreation facilities
as are those in the southwestern corner of Illinois. There are several
state parks and conservation areas scattered throughout the area, but
the large lakes are outside this area. Of course, urban recreational
facilities would be available to those living close to the Indiana
cities.
6.6.1. LAND USE
Although considered part of the forested area of Illinois, none
of these counties have more than 22% of the land in forest. Land is
largely devoted to farming, although percentages range from 70% to
over 90%.
III-D-159
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Table III-D-79
IL-6 LAND USE
% farm land 1969 % forest 1962 recreational
acreage 1973
Hamilton
White
Lawrence
Jasper
Clark
78.9
88.2
70.9
89.5
91.2
19.5
11.4
18.2
13.9
21.2
1,686
-
993
1,630
975
All of these counties are underlain by coal bearing rock but none
show any coal production for 1974. There was, however, oil production
in all counties and for Hamilton, White, Lawrence and Jasper, this was
the major extractive industry. The major extractive industry in Clark
County was the quarrying of stone. Petroleum was second in importance.
Sand and gravel mines were present in all but Hamilton County. To
give a rough idea of the relative magnatude of mineral extraction in
these five counties, figures are given for the value of the minerals
produced in 1973. Among the Illinois impact counties profiled for
this study, only St. Clair and Perry Counties in southwestern Illinois,
rivaled this group of counties in mineral extraction. In all the other
counties, mineral production was either very small or information was
withheld to prevent disclosing information about a single company.
Table III-D-80
IL-6 MINERAL PRODUCTION, 1973
Value in $1.000
Hamilton $ 4,055
White 16,260
Lawrence 16,674
Jasper 2,840
Clark W
6.6.2. RESIDENCE
All of the counties have a density of less than 50 per square mile.
Even accounting for the locations of the small towns, the rural popu-
lations of Hamilton and Jasper, the two counties not on the river,
were the most sparsely settled. Lawrence County, just across the
state line from Vincennes, Indiana, is the most densely populated.
Hamilton and Jasper Counties have especially high percentages of the
population living on farms.
III-D-160
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Table III-D-81
IL-6 DISTRIBUTION OF THE POPULATION
Density Urban Rural non-farm Farm
Hamilton
White
Lawrence
Jasper
Clark
20
34
47
22
32
30%
35
34
28
40
37%
48
50
24
35
33%
19
16
48
25
Residentially, Hamilton and Jasper Counties appear to be somewhat
more stable than the three border counties. As expected, they have
more residents who are natives of Illinois, but they also have higher
percentages of the population who lived in the same state or the same
county in 1965. The difference is not large but the pattern is
consistent. The counties as a group should be considered residentially
stable, nevertheless.
Table III-D-82
0
IL-6 RESIDENTIAL STABILITY
Hamilton White Lawrenee J a s per Clark
% residing in:
birth state
county, 1965
state, 1965
89.7
85.3
91.7
78.9
80.9
89.5
74.2
82.1
88.2
88.6
83.8
92.5
75.8
80.8
88.1
These counties experienced both moderate to small population
losses and out-migration during the sixties. Since 1970, they, like
many other counties in the ORBES region have begun to stabilize, and
trends have, at times, reversed. The most interesting reversal concerns
the two rural counties, Hamilton and Jasper. Both had comparable
levels of out-migration in the sixties which has apparently ceased.
Hamilton is now growing and has a small amount of in-migration. White
and Clark Counties do not show much change in trends for the early
1970's. With one exception, all of the counties have been losing
population from the farm sector at a rate which is characteristic
for the ORBES region. The farm population of Jasper County is declining
very slowly. This may mean that conditions here are more favorable for
farming. The somewhat lower than usual loss in neighboring Clark
County incline one to suspect such a condition there as well.
III-D-161
-------
Table III-D-83
IL-6 POPULATION SHIFTS
Hamilton White Lawrence
Jasper
Clark
change, 1960-70
population
net migration
farm population
change, 1970-74
population
net migration
-13.
-10.
-36.0
2.7
4.5
-10.6
-11.5
-35.8
- 5.1
- 3.8
- 5.5
- 7.3
-36.8
2.3
3.0
-5.3
-9.2
-5.1
0.6
0.1
-2.0
-3.6
-18.1
-0.4
6.6.3. AGE STRUCTURE
These counties are all located in an area running across southern
Illinois along the Ohio and Wabash Rivers, and having exceptionally
high median ages. Jasper is the only county with a median age less
than 35. Looking at the profiles, this appears to be due to the rela-
tively larger numbers of children in this population. Otherwise, age
profiles of these counties are very similar with large numbers of
the middle aged and elderly in the population. This tendency is most
marked in Hamilton County where the age cohorts between 50 and 70 have
almost as many individuals as those under 20. Median ages are:
Hamilton
White
Lawrence
Jasper
Clark
40.2
37.3
35.4
32.9
35.7
6.6.4. MARITAL STRUCTURE
Marital structure is predictable from the age structure and the
generally greater longevity of women. There are low percentages of
adult males, low percentages of single men or women, relatively high
percentages of widows, and few families with children under 18. Jasper
County, consistent with its slightly lower median age, exhibits these
trends to a slightly more moderate extent than the other counties.
In these rural counties, it is not surprising that relatively
low percentages of families have female heads and relatively high
percentages of families are intact.
III-D-162
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6.6.5. EDUCATION
Educational levels are, for Illinois, relatively low in these
counties. Lawrence County has the highest and Hamilton the lowest
median number of school year's completed. Similar small variations are
apparent when looking at those who have not finished high school and
those who have completed college. Lawrence, perhaps because of the
presence of Vincennes just across the river, has a slightly higher
proportion of the better educated and almost half of the population
has finished high school. There are nosignificant college populations
in these counties.
6.6.6. HOUSING
In Hamilton and Jasper, the two most rural counties, a high pro-
portion of housing units are occupied by the owner, but the other
counties all have over 70% home ownership. Houses are overwhelmingly
in one-unit structures.
Table III-D-84
IL-6 HOUSING, 1970
Hamilton White Lawrence Jasper Clark
Change 1960-70:
Households -5.7 -3.6 -1.0 -3.6 2.9
Housing units -9.7 -2.8 1.2 - .9 3.1
Average:
House value $6,812 $7,964 $8,722 $10,433 $9,846
Rent 69 75 77 73 79
% Units
One unit structures 93.4 88.3 89.8 93.6 87.6
Built since 1960 11.3 11.1 13.1 15.7 15.8
Owner occupied 80.5 71.2 76.9 84.0 77.1
Lack some plumbing 18.7 8.1 7.5 13.2 12.0
For Illinois, several of the counties (Clark, Jasper, Hamilton)
have relatively high percentages of housing units which lack some
plumbing. Examination of maps in Appendix A.will show that there is
a relationship between rents, house values and houses lacking plumbing.
These counties are in a strip of counties running diagonally south-
west to northeast across the middle of the ORBES region with moderately
valued housing and moderate levels of housing units which lack some
plumbing. Only Clark County had any increase in the number of house-
holds or housing units in the sixties. Clark County also had the
smallest population loss during this period. Considering the declines
in population, the building rates representing a relatively low level
of replacement are understandable.
HI-D-163
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6.6.7. ECONOMIC ACTIVITIES
All of these counties have substantial proportions of workers who
commute out (15 to 22%). Of the jobs available in these counties and
listed in County Business Patterns, few are in manufacturing. The
largest categories in Clark and Jasper Counties are related to trade.
Table III-D-85
IL-6 COUNTY BUSINESS PATTERNS, 1973
Hamilton White Lawrence Jasper
Clark
Total population
In CBP
Agriculture
Mining
Construction
Manufacturing
Transportation
Trade
Finance
Services
8,665
865
6
56
48
316
53
257
48
77
17,312
3,236
463
112
481
205
1,119
127
702
17,522
3,755
261
501
931
73
894
421
663
10,741
1,169
39
97
237
108
496
71
no
16,216
2,670
102
99
607
267
1,041
112
425
Several things can be seen on this table. Manufacturing is not diver-
sified. In Hamilton, White, and Jasper Counties, the only sizeable
industries produce apparel, probably accounting for the relatively
high percentage of women in the White County labor force. Lawrence
County has small manufacturing establishments producing: 1) petroleum
and coal products and 2) electrical equipment. Clark County also has
an electrical equipment industry as well as a small chemical industry.
The importance of mining, as mentioned earlier under "land use" can
be seen, especially in White and Lawrence Counties.
White and Lawrence Counties have the highest ratio of jobs to
population and Hamilton the lowest. This does not correlate with
persons who commute out, but there is a rough correlation with the
percentage of the population living on farms. The larger numbers of
potential full-time (Class I-V farms) operations, in Jasper County and
Clark County compensate for the relatively few non-agricultural jobs.
This is not true for Hamilton County.
Hamilton County has the lowest return per farm and per acre of
these five counties. The land is also markedly lower in value, perhaps
indicating lower productivity, perhaps greater difficulty in marketing.
Productivity is higher and land more valuable in the northern counties.
Hamilton County also has a more even balance between cash grain crops
and livestock raising. In all counties, cash grain crops are first
in importance and livestock secondary. Otherwise, there is little to
distinguish these counties from one another in farming.
III-D-164
-------
Table III-D-86
a
IL-6 FARMING STATISTICS, 1969
Hamilton White Lawrence Jasper Clark
Change 1964-69
Farms -9.2 -6.3 -9.3 -9.1 -6.3
Acreage 1.0 , .9 -5.6 -.6 1.6
Average: •
Land value . $244 $309 $339 $353 $352
Return per acre 39 48 57 55 63
Class I-V farms:
Number 657 699 502 1,040 934
Avg. acres 303 382 315 261 296
Avg. return $12,540 $18,938 $18,759 $17,402 $19,464
Other farms:
Number 303 - 234 210 254 312
Avg. acres 68 71 54 49 59
Avg. return $ 1,078 $ 1,103 $ 1,079 $ 1,011 $ 1,081
All the counties had some farm consolidation with little change in
acreage except for Lawrence County. *
6.6.8. INCOME
*^\
The relative poverty of Hamilton County is clearly demonstrated in
income figures. The relative unprofitability of farming in this county is
also apparent from the larger difference between median incomes for total
families and for farm families. By 1974, incomes had increased very little
in this county compared to the other counties. The per capita income in
Table III-D-87
IL-6 INCOME
1969 Median 1969 Median 1969 1973 1974 Median
Family Farm Family Per capita Per capita Family EBI
Hamilton $5,870 $4,760' $2,132 $4,721 $5,761
White 7,201 6,929 2,958 4,637 7,770
Lawrence 7,538 7,333 2,977 5.055 8,774
Jasper 7,945 7,774 2,690 6,379 5,871
Clark 8,045 8,159 3,235 5,871 9,097
White County is about the same but the difference in family incomes here may
be due to the larger percentage of women in the work force. This may be a
factor affecting family income figures in the three northern counties as well
III-D-T65
-------
6.6.9. IMPACT ASSESSMENT
The Illinois counties of Hamilton, White, Lawrence, Jasper and Clark,
while homogeneous with respect to predominant environmental orientation
(sentimental), exhibit rather interesting variations in the sub-orienta-
tions. For instance, Jasper County, a stable prosperous farming
community with families in the child-bearing and rearing cycles contrasts
sharply with Hamilton County with its remarkably elderly population and
its poverty. In the former, the prestige sub-orientation as well as
an economic benefit/instrumental orientation is probably dominant; in
the latter, primordial belonging.
All these counties, with the exception of Lawrence, are not boom-
town condidates. There are cities in Indiana providing most of the
work force, but those farthest away from cities may have "boomlets."
Lawrence County seems likely to experience a boom and seems not too
well equipped to provide needed services and amenities. The larger
nearby city of Vincennes in Indiana seems to be the most likely
recipient of the boom, however, possibly mitigating local effect.
In terms of local acceptance of development, we would expect
Jasper and Hamilton Counties to be the least receptive, for the differing
reasons described above. Clark, being the most urban would seem the
most accepting, though farming is a prosperous occupation there. White
County, being close to Evansville, Indiana should experience little
negative impact from power plant construction and possibly welcome the
infusion of money to the county.
III-D-M
-------
7. DEMOGRAPHIC PROFILES AND IMPACT ANALYSIS: INDIANA
7.1. JASPER COUNTY
Jasper County, although not slated for any power development under
the scenarios, will have extensive power development prior to 1985. This
county has two plants, a small 20 megawatt plant which will be increased
to 25 megawatts by 1985 and a large coal-fired plant with one unit under
construction and two in the planning stages. The unit under construction
will have a capacity of 520 megawatts and the additions will have 477
and 527 megawatts, respectively. The generating capacity of this county
will be 1548 megawatts by 1985. This plant is located close to the Kan-
kakee River near Wheatfield (679) in the northern part of the county.
Jasper County is fairly close to the Gary-Hammond urban areas
south of Chicago and Lake Michigan. 1-65, running along the western
border of the county, goes to this metropolitan area. Jasper County
itself is sparsely settled and serviced by minor U.S. and state high-
ways. From Wheatfield, however, it is only 20 miles north to 1-30 at
Valparaiso (20,020) and a major highway network. No other cities of
any consequence are close. Jasper County has three communities over
1,000:
Rensselaer (4,688)
DeMotte (1,697)
Remington (1,127)
Rensselaer and Remington are in the southern half of the county, 17 and
25 miles away respectively. DeMotte is just 7 miles west of Wheatfield.
7.1.1. LAND USE
Almost 90% of the land in this county is in farmland and 7% is
forested. The county is outside the coal producing areas but there is
stone, sand and gravel quarrying. Urban use of the land is probably
minimal.
7.1.2. RESIDENCE
This county has been growing at a modest rate since I960, in
spite of some out-migration during the sixties. (Jains in the 1970
Table III-D-88
IN-1 POPULATION SHIFTS
Growth Migration
_1960-70:87?- 4.3
1970-74 7.6 11.0
III-D-167
-------
population are to the rural non-farm sector of the population, both
the single urban community, Rensselaer, and the farm sector (-26.3)
having declined. Nevertheless 22% of the population lived on farms
in 1970 and 23% in Rensselaer. The remaining 55% lived in small
communities or the open countryside.
Jasper is one of the few counties in the ORBES Region which has
a significant proportion of residents who are foreign born or of
foreign/or mixed parentage (9.1%). It also has fewer than the
average percentage of residents who were born in Indiana (69.9). In
spite of the fact that more of the residents come from elsewhere, this
does not appear to be a county with excess transience or residential
mobility, although it has slightly above the average. Just over 76%
of the population lived in Jasper County in 1965 and a further 11% lived
in other counties in Indiana.
7.1.3 AGE STRUCTURE
The median age in this county is rather low (24.3) and the age
profile reflects this. There are relatively large numbers of children
but the numbers in age cohorts decline sharply between 19 and 20 and
again between 24 and 25. A probable explanation for this two step
decline is the presence of a college population of 1,145. There is a
small college, St. Joseph's, in Rensselaer. Age cohorts for ages 25
through 50 are roughly equal in size. After this, numbers begin to
decline regularly. The consequence is a population dominated by the
young and middle-aged, many of whom must have children.
7.1.4 MARITAL STRUCTURE
This county i"s one of the few in the region with above average
numbers of adult males in the population, a larger than average pro-
portion of whom appear to be single. This is a largely Catholic
population and the name of the college in Rensselaer suggests that this
is a men's college or seminary. The fact that the numbers living in
group quarters is somewhat larger than the college population supports
this contention. The balance of the population appears to be predomi-
nantly married couples in the early or middle stages of the family cycle
with children at home. Most women are married, high percentages of
families are intact and have children under 18. there are few widows
or families with a female head.
7.1.5 EDUCATION
Educational levels in this county are relatively high for the ORBES
region in terms of average level of attainment. Median number of school
years completed is 12.0 and over 58% of the adult population have com-
pleted high school. For such a rural county, the percentage who have
completed college (6.2) is respectable. Of course this figure may have
been inflated by the presence of the faculty and administrative personnel
of the college. '
III-D-168
-------
7.1.6 HOUSING
Like the population, numbers of households and housing units have
grown since 1960. One-fifth of the housing units were built between
1960 and 1970, indicating a moderate level of building activity. Housing
values($13,176) and rents ($102) are relatively high. Housing units are
overwhelmingly in one-unit structures (87.1) although only 71% are
occupied by the owner. Few (6.7%) lack any basic plumbing.
7.1.7 ECONOMIC ACTIVITIES
The non-agricultural economic activities of this county are di-
versified and a small percentage commute out for work.
Table III-D-89
IN-I COUNTY BUSINESS PATTERNS, 1973
Total Population 20,429
In CBP 3,777
Agriculture 4
Mining 43
Construction 499
Manufacturing 956
Transportation 138
Trade 1,318
Finance 128
Services 663
The value added by manufacturing for 1972 is higher than one would
expect, looking at the few manufacturing jobs in this county. The reason
may lie in the type of manufacturing done. The 1972 Census of Manufacturing
lists four large plants, employing over 250 persons each for Jasper County
as well as 18 smaller plants. Although these numbers are not in accord
with those in County Business Patterns (possibly due to differences in
collection methods, categories and year) together they provide some in-
dication of the situation. The most important industry is in 1) fabri-
cated metals but there are also industries producing: 2) lumber and
wood products; 3) electrical equipment; and 4) transportation equipment.
This many large plants is uncharacteristic of the other rural counties
profiled for the ORBES study.
Examination of the work force composition reinforces two charac-
teristics of the population suggested earlier. Relatively small per-
centages of women and working wives are in the work force. Also, a
relative high percentage of the work force is engaged in educational
services, probably as a consequence of 1) a population of children
and 2) the presence of a college.
III-D-169
-------
Farming is a very profitable economic activity in this county.
Farms are relatively large and land values are moderately high, most of
them are, at least potentially, full-time operations. In the late
sixties there was a small amount of farm consolidation but no loss*in
the total amount of land devoted to farming.
Table III-D-90
IN-1 FARMING, 1969
Changes 1964-69
Farms -3.2
Acreage 0.1
Average:
Value of land $ 420
Return per acre 116
Class I-V Farms:
Number 952
Avg. acres 328
Avg. return $ 38,936
Other Farms:
Number 242
Avg. acres 47
Avg. return $ 1,537
% Return from:
Crops 48
Dairy 1
Livestock 46
Poultry 5
The largest number of farms (620) are primarily devoted to raising cash
grain crops. There are fewer livestock farms (251) but the general
return from livestock is almost as high. The vegetable (13) and fruit
farms (7), although not numerous, are more than most counties have.
7.1.8. INCOME
Income levels in Jasper County are above average and this
relative position has persisted through 1974.
Table III-D-91
IN-1 INCOME
1969:
Median Family $ 8,776
Median Farm Family 7,978
Per capita 3,543
1973:
Per capita 5,628
1974:
Median family EBI 11,135
III-D-170
-------
7.1.9. IMPACT ASSESSMENT
Jasper County, Indiana, being affluent and rural and populated by
families in the child-rearing phase of the life cycle, would probably
be receptive to development of power plants, largely because it can
avoid the boomtown syndrome. The environmental sub-orientations pre-
dominant here are prestige and economic benefit. There is the possi-
bility of conflict should large portions of prime farm land be required
for plant siting, however, the nature of the population would indicate
favorable attitudes toward power plant development.
HI-D-171
-------
7.2. TIPPECANOE (109,378), FOUNTAIN (18,257), WARREN (8,705) AND
VERMILLION (16,793) COUNTIES
Four counties in northwestern Indiana along the Wabash River will
have power plants, both coal-fired and nuclear, under the scenarios. At
the present time the only county having generating facilities is Vermil-
lion with a coal-fired plant at Cayuga capable of generating 1,073
megawatts. No new facilities are planned for this area before 1985.
Under the high energy Scenario I, each of the four counties will
have a single unit (1,000 megawatt) coal-fired plant and in addition,
Fountain County will have a single-unit (1,000 megawatt) nuclear fueled
plant.
Scenario II, also a high energy scenario, would provide for three
coal-fired single unit plants and three nuclear-fueled single-unit
plants. Coal-fired plants would be built in Warren, Fountain and
Vermillion Counties. Nuclear plants would be built in Tippecanoe,
Fountain and Vermillion Counties.
The Wabash River runs through the two major urban areas in this
area: Lafayette/West Lafayette (64,112) in the middle of Tippecanoe
County, and Terre Haute (72,990) just a few miles south of the Vermil-
lion-Vigo County line. These cities, at the northern and southern ends
of the area, are both connected by interstate highways with Indianapolis,
75 miles away in the center of the state. Running about half way
between, and crossing Fountain and Vermillion Counties, a third major
highway route, 1-74, connects Indianapolis with Danville (42,570) and
Champaign-Urbana in Illinois. That highway passes Crawfordsville
(13,842) in neighboring Montgomery County, the next largest community
in the area.
Except for Lafayette/West Lafayette in Tippecanoe County, there
are only seven communities over 1,000 in these four counties, three
of them less than 2,000. They are:
Warren County - Williamsport (1,661)
Fountain - Attica (4,262), Covington (2,641), Veedersburg (1,837)
Vermillion - Clinton (5,340), Cayuga (1,090), Fairview Park (1,067),
As indicated above, however, the location of the two Illinois cities
and Danville, Indiana is such that any resident of these counties would
be less than 50 miles from an urban area.
7.2.1. LAND USE
Vermillion County has the largest proportion of land in forest and
the smallest proportion in farmland. It also has the largest amount of
coal production as well as some sand, gravel and clay quarrying. Fountain
also has some coal mining but it is less important than the quarrying
of sand and gravel. Tippecanoe and Warren also have some sand and gravel
quarries.
III-D-172
-------
Table III-D-92
IN-2 LAND USE
Tippecanoe Warren Fountain Vermin ion
% Land In:
Farms, 1969 85.8 88.9 91.2 66.6
Forest, 1967 6.0 8.6 10.7 20.8
1973 Mineral Production
Value W W W $15,706,000
Tippecanoe County must have a substantial proportion of the land in
urban use. Although Vermillion County is included in the Terre Haute
SMSA, current information only shows a concentration of small communities
in the southern third of the county. These may be satellite communities
of Terre Haute but whether they are dormitory communities or areas of
industrial expansion has not been determined.
7.2.2. RESIDENCE
Tippecanoe, the only urban and densely settled county of the four, has
been the most dynamic residentially. During the sixties, the population
grew substantially and exclusively in the urban sector, the rural sector
having declines. Part of this urban growth, of course, may be due to
reclassification in the 1970 census and incorporation of fringe areas
into urban areas. There was a corresponding level of in-migration. Over
30% of the population over 5 are in-migrants. Tippecanoe County also
has, relatively speaking, fewer people who lived in the same county or in
Indiana in 1965 as well as a lower percentage of Indiana natives.
Table III-D-93
IN-2 RESIDENTIAL STABILITY
Tippecanoe Warren Fountain Vermin ion
Density 219 24 46 64
% Residing in:
Birth state 67.9 69.1 72.4 72.7
County, 1965 62.8 77.6 84.7 83.5
State, 1965 80.4 90.5 91.2 90.4
Change, 1960-70
Population 22.7 1.9 - 2.4 - 5.0
Migration 6.5 - 5.1 -10.3 - 4.4
Farm population -36.7 -32.9 -29.0 -35.7
Change, 1970-74 - 1.7 - 3.9 0.1 1.8
Migration 2.6 - 2.3 1.9 1.9
f
III-D-173
-------
Since 1970, in-migration has continued, but not at a high enough rate to
offset decrease from natural causes.
The other three counties have populations which are somewhat more
stable residentiary, Fountain and Vermillion being the most stable and
Warren County having a slightly higher level of mobility within the
state than the other two. Warren County, in contrast to Fountain and
Vermillion Counties, did not experience a reversal of the out-migration
trend during the early seventies.
7.2.3. AGE STRUCTURE
Tippecanoe can be contrasted with the other counties in median age:
Tippecanoe 23.5
Warren 30.1
Fountain 30.5
Vermillion 35.7
The very low median age in Tippecanoe County is due to the large per-
centage (29%) of the population who are between 15 and 25, accounted for
in large part by the presence of Purdue University in West Lafayette with
almost 20,000 students.
Only in Vermillion County is there a marked difference in the sizes
of the young adult and middle-aged cohorts. There are larger numbers of
the middle aged. Vermillion County also has relatively small numbers of
children. Both Fountain and Warren Counties show moderate decreases in
cohort size between ages 19 and 20. After that cohorts are roughly
similar in size until age 55 when they begin to decrease gradually. All
of these counties are similar to many Illinois counties in having higher
than average percentages of the elderly.
7.2.4. MARITAL STRUCTURE
With its differences in age structure and the prestige of a major
university, Tippecanoe County also exhibits differences in marriage
patterns. There are higher than average percentages of adult males, and
single men and women. Conversely, the percentages of married and widowed
individuals are relatively low. Relatively high percentages of families
are intact and relatively few families have a female head.
Vermillion County, on the other hand, has relatively high percentages
of the widowed and the divorced in the population. This latter charac-
teristic is possibly related to the nature of the satellite communities
in the southern part of the county. There are relatively few single men
and women in this county. The lower than average proportion of adult
males in the population is characteristic of counties with high median
age.
III-D-174
-------
Fountain and Warren Counties are similar. High (males) or relatively
high (females) percentages of the adult population are married and the
percentages of intact families are also relatively high. Few are single
and there are not excessive proportions of the divorced or widowed. As
a consequence, there are relatively few families with a female head.
7.2.5. EDUCATION
The presence of a large university in Tippecanoe plus the urban
nature of the county are evident in educational levels. Very few (32%)
have not completed high school and over 20% have completed college..
The other counties are typical of the region in that median school
years completed is over 12. In Fountain and Warren Counties, approximately
half of the population have finished high school (52% and 49.8% respectively),
but the figure for Vermilljon is lower (43.3%). All have low percentages
(less than 5%) who have finished college and no substantial (less than 200)
college population.
7.2.6. HOUSING
In housing patterns, Tippecanoe County is also distinctive. Owner-
occupied dwellings are worth much more, but fewer dwellings are occupied
by the owner and few are single unit structures.
In Warren, Fountain, and Vermillion Counties, housing values are
relatively low and relatively large numbers are owner-occupied and in
single unit structures. Again, Fountain and Warren Counties are inter-
mediate between Tippecanoe and Vermillion.
Table III-D-94
IN-2 HOUSING, 1970
Tippecanoe Warren Fountain Vermillion
Change 1960-70
Households 29.7 6.8 9.9 0.2
Housing units 30.2 11.6 3.1 0.9
Average:
House value $17,557 $9,561 $9,842 $6,454
Rent 122 88 90 74
% Units
One unit structures 66.2 91.5 88.1 88.7
Built since 1960 31.0 18.0 13.6 9.5
Owner occupied 62.2 73.2 74.6 80.0
Lack some plumbing 2.4 10.9 8.8 15.8
III-D-175
-------
Tippecanoe has been building new units at the highest and Vermillion
at the lowest rate. This proportion of new structures is consistent with
the percentages of housing lacking plumbing, as well as the increases in
numbers of new households and housing units. Since only Tippecanoe County
experienced an increase in population during the sixties, these latter
figures also indicate that households must be smaller now.
7.2.7. ECONOMIC ACTIVITIES
The magnitude of all types of economic activity is greatest in
Tippecanoe County. This is also the only county with net in-commuting
also. Taking into consideration the relatively high percentage of the
labor force working in government, the high percentages in professions
or management, categories with many jobs not listed in County Business
Patterns, and the low ratio between population and workers listed in
County Business Patterns, the commuting pattern is easily understand-
able. Tippecanoe County is also characterized by relatively high
percentages of women and working wives in the work force. This county
has diversified industrial activity. The most important industry,
employing 1,159 people, produces electrical equipment. The second
largest industry prodflces fabricated metal products. Other smaller
manufacturing industries deal in: 1) food products, 2) lumber and wood
products, 3) printing and publishing, 4) chemicals, 5) rubber and
plastics, 6) primary metals, 7) machinery, 8) transport equipment, and
9) instruments.
Table III-D-95
IN-2 COUNTY BUSINESS PATTERNS, 1973
Total Population
In CBP
Agriculture
Mining
Construction
Manufacturing
Transportation
Trade
Finance
Services
Tippecanoe
109,378
32,797
39
87
1,789
12,594
915
8,807
2,521
5,988
Warren
8,705
930
-
-
81
-
72
222
241
106
Fountain
18,257
4,075
9
-
73
2,241
143
1,094
141
348
Vermillion
16,793
2,099
-
-
176
717
249
645
93
204
The predominant economic activities in Fountain County are manu-
facturing of: 1) electrical equipment, 2) primary metals and 3) rubber
and plastics
III-D-176
-------
Vermillion County, with almost as large a population, has only
about half the number of jobs listed in County Business Patterns.
Only a third of them are in manufacturing. The sizeable industry
(employing over 250 people) produces rubber and plastics.
Warren county has less than 1,000 jobs listed in County Business
Patterns and no industry employing over 20 people.
The nature of the industrial activity in Fountain and Vermillion
Counties helps to explain the relatively high percentages of crafts-
men and foremen in the civilian work force. The relatively high per-
centage of those in Warren County who work in manufacturing may form a
large segment of the out-commuting workers going to Tippecanoe or
Fountain Counties.
The characteristics of farming in Warren, Fountain and Vermillion
Counties differ from Tippecanoe in a few ways. Land is less expensive,
return per acre is lower, farms are larger and part time farming is
not so profitable.
All four counties show similar returns on full time farming
operations. Cash grain farming is the most prevalent type of farming
operation and livestock raising is second. Crops account for slightly
over half of the return and livestock accounts for slightly over 40%
(exception: Warren: 73% crops, 26% livestock) of the return.
Warren and Fountain Counties had a small amount of farm consoli-
dation. In Vermillion County, land appears to have been converted to
other uses. This may be related to urban expansion from the south.
Regardless of the small percentage living on farms, farming involves
larger numbers of people and farms in Tippecanoe than in the other counties.
Farms are smaller, but return per acre is higher as is the average
return per class I-V farm. In this county, part-time farming appears to
be especially profitable as well. However, since definitions of Class
VI and part-time farms preclude this high return per farm, we surmise
that there may be some large "abnormal" farms, perhaps conected with
Purdue Agricultural College which are inflating this figure. Tippecanoe
is the only county showing gains in number of farms during the latter
part of the sixties. This gain was slightly suggesting several possible
factors. The cost of land may discourage consolidation and enocourage
more intensive farming practices. Both profitability and rural life
style may be factors encouraging individuals to buy farms.
III-D-177
-------
Table III-D-96
IN-2 FARMING, 1969
Tippecanoe Warren Fountain Vermillion
Change 1964-69:
Farms 6.3 -2.9 -5.9 -11.6
Acreage 5.7 2.6 1.8 -15.8
Average
Land value $519 $397 $347 $347
Return per acre 84 61 65 71
Class I-V farms:
Number 882 534 673 315
Avg. acres 287 369 320 325
Avg. return $24,254 $23,695 $22,121 $24,935
Other farms:
Number 305 161 258 157
Avg. acres 70 77 64 62
Avg. return $ 5,077 $ 999 $ 1,056 $ 1,032
7.2.8. INCOME
Income levels could be predicted from the foregoing profiles, high
in Tippecanoe, moderate in the other counties.
Table III-D-97
IN-2 INCOME
Tippecanoe
Warren
Fountain
Vermillion
1969 Median
Family
$10,118
8,338
8,416
8,245
1969 Median
Farm Family
$9,156
8,011
7,699
8,015
1969
Per capita
$3,433
3,282
3,388
3,046
1973
Per capita
$4,683
5,838
5,169
4,454
1974 Median
Family EBI
$12,184
10,962
9,878
7,764
7.2.9. IMPACT ASSESSMENT
Tippecanoe, Warren, Fountain and Vermillion Counties in Western
Indiana present a mix of environmental orientations and likely reactions
to power plant development.
Tippecanoe County presents a rather complicated picture. The
economic diversity and progressive urban character of Tippecanoe County
suggest a strong economic benefit sub-orientation and thus, receptivity
to development. However, the Lafayette/West Lafayette urban complex
III-D-178
-------
does not appear able to contribute many workers to power plant con-
struction, so a boom or "boomlet" situation seems likely and there may
be negative reaction to that. The prestige sub-orientation is also
present in this county and opposition to the plant might come from
groups that have a stake in keeping things as they are. Opposition
groups would also be likely to emerge from Purdue University too. We
would suggest that receptivity to power plant development would be
mixed and conflict-laden given the mix of orientations.
Vermillion County, too, has mixed orientations. The urban influence
spreading from Terre Haute suggests the beginning of an instrumental
orientation, however, many other sub-orientations are present and much
stronger. There is the aesthetic sub-orientation and the age, stability
and occupational structures present in the population suggest a primordial
belongingness sub-orientation as well. The decline in relative wealth
bodes well for receptivity to power plant development, however, the
aesthetic and belongingness sub-orientations suggest there will be
considerable opposition to the plant. Nearness to Terre Haute means a
boomtown situation is unlikely. We suspect that the instrumental
orientation will become dominant and receptivity to power plant develop-
ment will increase.
Warren and Fountain Counties are candidates for a boomtown situ-
ation and, given their location and the lack of economic diversifica-
tion, will have difficulty in coping with the syndrome. The primary
orientation is sentimental and we would predict considerable opposition
to the power plant, given the rural nature of the population.
III-D-179
-------
7.3. SULLIVAN (19,889), GREENE (26,894), KNOX (41,546), DAVIESS (36,602),
MARTIN (10,969), GIBSON (30,444), PIKE (12,281) AND DUBOIS (30,934)
COUNTIES
In the southwestern quarter of Indiana are a cluster of eight
counties which will be subject to heavy impacts from power plant
development in the next twenty-five years.
At present, three counties, Sullivan, Gibson and Pike have large
power generating facilities with additions in the planning stages.
Sullivan has, at present, two small plants with a total generating
capacity of 510 megawatts. In 1981 and 1984 respectively, two coal-fired
units, 490 megawatts each, will go into operation at Merom on the Wabash
River.
Gibson County already has 2,672 megawatts of generating capacity
from a coal-fired plant at East Mount Carmel. A three-unit (650,668 and
668 megawatts respectively) plant is planned for Princeton.
Pike County has a plant at Petersburg generating 1,741 megawatts.
Two additions to this facility will bring the generating capacity to
2,805 by 1982.
Greene and Martin Counties have no present facilities. Knox,
Daviess and Dubois have small generating plants.
Under Scenario I, 11,000 megawatts will be divided among the eight
counties. Scenario II divides 8,000 megawatts among seven counties.
Each of the low energy scenarios would add one unit to the generating
capacity of this area. Because of the concentration of facilities in
this area, distribution of plants will be shown in chart form.
These eight counties are clustered in a rough rectangle bounded on
the west by the Wabash River and on the east by the Hoosier National
Forest. In the neighboring counties to the north and south are Terre
Haute and Evansville. About halfway between the two larger cities on
U.S. 41 is Vincennes in Knox County. Bloomington in Monroe County to
the northeast of the cluster is the fourth regional urban center. Thus,
although this cluster of counties is by-passed by all but one of the
many major highway routes crossing Indiana, most residents are within
50 miles of one of the secondary cities.
Each of the counties has several communities of over 1,000 and
excluding Vincennes, four have over 5,000 residents:
Washington (11,358) in Daviess County
Jasper (8,641) in Dubois County
Princeton (7,431) in Gibson County
Linton (5,450) in Greene County
III-D-180
-------
Table III-D-98
IN-3 POWER GENERATING CAPACITY, SOUTHWESTERN INDIANA
1975
2,000 2,000 2,000 2,000
1985 Scenario I Scenario II Scenario III Scenario IV
Sullivan:
Fossil
Nuclear
Greene
Fossil
Nuclear
Knox
Fossil
Nuclear
Daviess
Fossil
Nuclear
Martin
Fossil
Nuclear
Gibson
Fossil
Nuclear
Pike
Fossil
Nuclear
Dubois
Fossil
Nuclear
501
146
15
2,672
1,741.8
16
1,481
146
15
4,622
2,805
16
2,481* r
1 ,000*
1 ,000*
1,146*
2,015**
1 ,000*
1 ,000*
5,622*
2,805
1,016*
2,481*
1 ,000*
1 ,000*
146
1^015*
1 ,000*
1 ,000*
5,622*
3,805*
16
1,481
146
'15
600*
4,622
3,805*
16
1,481
146
1,015*
4,622
2,805
16
* = new unit
III-D-181
-------
There are several rivers near which plants could be built. The Ohio
River is the largest waterway and forms the western border of Sullivan,
Knox and Gibson Counties. The new Sullivan County plant at Merom
Station is close to the river and one would expect that other plants
would be similarly located. The White River crosses Greene County and
forms the border between Knox and Daviess Counties. The Pike County
plant at Petersburg is on the White River. On the same river where it
joins the Wabash is the East Mount Carmel Plant in Gibson County.
Princeton is on Pigeon Creek. The East Fork River crosses Martin
County and the Patolea crosses Dubois. With this complex pattern of
water ways, it is impossible to speculate about which parts of the
county are likely to be most directly affected by development.
7.3.1. LAND USE
The proportion of land which is forested varies widely among
these counties. There is an inverse relationship between proportions
of forested land and farm land. Knox, Daviess, and Gibson have the
highest proportions of land in farms and the lowest in forest.
Table III-D-99
IN-3 LAND USE
% Land in
Forest, 1967
% Land in
Farms, 1969
Coal Production,
1974
(1,000 tons)
Valuable Mineral
Production
(thousands)
Sullivan
Greene
Knox
Daviess
Martin
Gibson
Pike
Dubois
18.
28.
11.
15.2
50.
15.
37.
68.
65.
90.
83.
38.
80.
53.
3,189
822
770
5,088
34.9
77.6
$27,778
7,162
576
102
W
W
W
W
Martin and Pike have the largest amount of land in forest and the
lowest in farm land. The unusually low proportion of land in farms in
Martin County may be partly due to the Crane Naval Ammunition Depot
which covers about a fourth of the county. There is also a similarly
sized part of the Hoosier National Forest in the southern part of the
county. The Hoosier National Forest appears to be the major locus
for outdoor recreation in this area.
Sullivan and Gibson Counties are part of SMSA's but both are the
loci of satellite development, however, the extent to which land is in
urban use is undetermined.
III-D-182
-------
Both Sullivan and Pike have substantial coal production in addition
to some stone, sand and gravel quarrying. Since figures are withheld,
it is not possible to gauge the size of mineral extraction industries
in most of the other counties. In all except Knox and Daviess Counties,
however, coal is most important. Second in importance (except for Knox
and Daviess where it is most important) is the quarrying of sand and
gravel.
7.3.2. RESIDENCE
The density of all of these counties is low. The population is
mixed and residentially stable, with Dubois showing the highest level
of stability.
Table III-D-100
IN-3 DISTRIBUTION OF POPULATION
Density % Urban % Rural non-farm
% Rural farm
Sullivan
Greene
Knox
Daviess
Martin
Gibson
Pike
Dubois
44*
49
81
62
32
61
37
71
24
30
57
43
27
44
22
43
59
51
31
34
53
41
64
42
17
19
12
23
20
15
14
15
All counties except Greene experienced moderate to low levels of
out-migration during the sixties. In several counties the loss of
population due to out-migration was offset by natural increase and the
counties still gained in population. This effect was especially marked
in Dubois County which had a low level of out-migration but a net increase
of over 12%.
Table III-D-101
IN-3 RESIDENTIAL STABILITY
Birth State:
Same State. 1965
Same County, 1965
Sullivan
Greene
Knox
Daviess
Martin
Gibson
Pikje
Dubois
82.7
88.7
82.8
88.2
84.7
83.9
89.4
92.0
91.6
92.0
91.3
92.5
93.9
92.8
93.2
95.4
83.2
81.5
82.6
84.8
83.8
85.3
83.9
89.9
III-D-183
-------
Greene County, with a very small amount of in-migration, maintained
its population at about the same level.
In the early seventies, the levels of out-migration were reduced
or reversed and natural increase seems to have slowed down as well.
As a consequence, populations are relatively stable or declining
slightly. Greene County, again, was attracting migrants at a higher
rate than the other counties. This may be due to the location of
Bloomington in nearby Monroe County.
Table III-D-102
IN-3 POPULATION SHIFTS
1960-70 1970-74
[Population Migration] [Population Migration]
Sullivan
Greene
Knox
Daviess
Martin
Gibson
Pike
Duboi s
-8.4
2.2
-
-0.1
3.4
8 1.7
-4.0
12.6
-9.9
0.1
-4.2
-6.9
-11.6
-3.6
-5.4
-2.6
-2.1
3.8
-1.8
-1.3
-3.8
2.6
-1.2
0.2
-2.3
4.6
-1.5
0.3
0.2
3.2
-1.3
3.1
As was true through the ORBES region, all counties lose dispropor-
tionately from the farm sector of the population. The percentages
from Sullivan and Pike Counties were particularly large.
7.3.3. AGE STRUCTURE
*
Median ages in these counties varied from a low of 25.0 in Dubois
County to a high of 35.0 in Sullivan County:
Sullivan 35.0
Greene 34.4
Knox 31.4
Daviess 30.0
Martin 26.5
Gibson 31.0
Pike 34.7
Dubois 25.0
The age profiles for Sullivan, Greene and Pike Counties are similar
with relatively few children and young adults but relatively large
numbers of the middle-aged and elderly. Knox and Daviess Counties
exhibit a similar pattern but there are relatively more children so
the sudden decrease in the size of cohorts over 19 is more marked.
III-D-184
-------
Gibson's profile is characterized by young adult and middle-aged
cohorts which are roughly equal in size. The profile of Dubois is
interesting in that it exhibits an almost perfect pyramidal shape.
After age 19, size of cohorts gradually and regularly decreases. The
low out-migration from this county, if it has been a sufficiently long
trend, and stable birth rate, might help to account for this profile.
The profile for Martin County approaches this same shape with only a
small increase in size of cohorts for ages 50 to 59. This county had
a net out-migration of 11.6% during the sixties.
7.3.4. MARITAL STRUCTURE
Greene and Sullivan are included in an area covering much of
Illinois, southwestern Indiana3and western Kentucky which have
relatively few adult males and .median ages are high. This usually
means that there are few single men and women in the population,
higher than average numbers of widows, and fewer than average percentages
of families with children under 18. This same pattern is true in
general for Pike and Gibson.
Martin and Dubois, on the other hand, with lower age levels, have
more families in early stages of the life cycle with children under
18 and fewer widows. In all counties except Knox, moderate to high
percentages of the population are married, especially males. Divorced
women tend to concentrate in Knox and to a lesser extent in Greene
Counties. Dubois County, on the other hand, has relatively few
divorced people.
7.3.5. EDUCATION
Knox and Greene have the highest educational levels for the
counties in this cluster. Of course Knox County has the only city,
Vincennes, in this area and Greene County is close to Bloomington,
location of Ifitliaea .Uni-veps-tUy. There is a college population
in Vincennes of over 2,000. These factors probably affect educational
levels.
In general, the counties of this cluster are about average for
the ORBES region. Median school years completed are less than 12, less
than half of the the population have finished high school (except for
Knox and Greene Counties)sand between 4% and 6% have finished college.
Knox and Greene Counties have slightly higher (6.2% and 6.3%)
percentages of the adult population who have college degrees.
III-D-T85
-------
7.3.6. HOUSING
Housing patterns indicate that Dubois County is the most dynamic.
This county has the greatest increase in households and housing units,
the highest level of building activity, the most expensive units and
the fewest units lacking some plumbing. Recalling that this county
also has the highest level of residential stability and the highest
level of population growth coupled with a low level of out-migration
which apparently has not depleted the young adult population, (judging
by age profile and low median age), we would speculate that something is
occuring in Dubois County which encourages most of the young to remain
in the county, marry and establish households. Furthermore, whatever is
keeping the residents is not a large enough attraction to pull in
migrants. In essence, this looks like an unusually self-contained
county. Martin County with its young population may have some of the
same characteristics.
Considering the high median age, the higher levels of out-migra-
tion and population decline, it is not surprising that Sullivan County
has fewer households and housing units than in 1966 and the lowest
building rate among the counties. It also has a high proportion of one-
unit structures. In general these counties exhibit variation in these
characteristics which place them in the middle range for ORBES
counties. The major exception is that, except for Knox County, this is
a region with high levels of home-ownership. Building rates in this
area are also moderate to low.
III-D-186
-------
00
Sullivan
Table III-D-103
IN-3 HOUSING, 1970
Greene Knox Daviess
Martin Gibson
Pike Dubois
Change 1960-70:
Households
Housing Units
Average:
House Value
Rent
% Units:
One-Unit Structures
Built Since 1960
Owner Occupied
Lack Some Plumbing
-4.6
-1.3
_
7,103
80
91.7
10.6
82.6
15.8
5.9
7.1
7,975
77
87.9
15.6
82.2
13.7
1.8
2.1
8,854
76
86.8
12.7
73.8
• 9.0
6.3
6.3
10,035
75
86.3
17.2
78.6
10.2
12.4
11.6
8,241
75
80.7
18.6
76.2
17.9
6.2
6.6
9,959
80
86.2
16.0
78.4
8.8
1.9
7.1
7,133
79
89.5
13.3
81.9
17.4
16.7
16.8
13,331
83
85.4
21.6
83.9
7.6
-------
7.3.7. ECONOMIC ACTIVITIES
The primary non-agricultural economic activity in Dubois and
Martin Counties is manufacturing. In Knox County, trade is most
important. The other counties have more balanced job distributions.
Looking at the number of jobs in Dubois County compared with the size
of the population, it is easy to see why this county has atypical age
and housing patterns. It is also apparent why this county is a focus
for in-commuting. More than half of the manufacturing activity, which
is so important in this county is in 1) furniture (employing 3,484 persons)
Industries producing wood products 2),(with 903 employees) and 3) food
(with 350 employees) are responsible for a large part of the remaining
employment. There are also industries employing over 100 people and
producing: 4) apparel or textiles, 5) rubber and plastics, 6) stone,
clay and glass products and 7) transportation equipment.
Although Martin County appears similar on the maps, the magnitude
of the differences serves to distinguish these counties sharply. Martin
County industry is primarily in: 1) textiles and apparel and second-
arily in 2) stone, clay and glass products. The importance of the
textile industry, which usually employees a large percentage of women,
is responsible for the large percentages of women and working wives in
the work force. Martin County should also be noted for the high per-
centages of Federal employees in the civilian labor force. Many of
these may be employed at the Crane Naval Ammunition Depot.
Knox, Gibson, Daviess and Greene Counties all have more manufacturing
activity than Martin County. Gibson and Greene Counties both produce
electrical equipment. Gibson also has a rubber and plastics industry.
Greene County has a furniture industry. The following industries in
Knox County employ over 100 persons: 1) peper and printing, 2) stone,
clay and glass products, 3) fabricated metals, 4) electrical equipment,
5) lumber and wood products, 6) primary metals. The industries employing
over 100 in Daviess County are: 1) apparel and textiles, 2) machinery,
3) food, 4) transportation equipment.
Manufacturing in Pike County is negligible but Sullivan produces:
1) lumber and wood products, 2) instruments, 3) apparel or textiles and
4) rubber and plastics.
Dubois County has exceptionally profitable farming, measured both
in average return per acre and per farm. Interestingly enough land
values are relatively low. The figures in the table indicate that in
farming, as in other areas, the other counties vary around the average
for the ORBES region. Generally Daviess, Knox and Gibson are above
and Sullivan, Greene, Martin and Pike, a bit below average.
III-D- 188
-------
Table III-D-104
00
UD
IN-3 COUNTY BUSINESS PATTERNS, 1973
Sullivan Greene Knox Daviess Martin
Gibson
Pike
Dubois
Population
In CBP
Agriculture
Mining
Construction
Manufacturing
Transportation
Trade
Finance
Services
19,889
3,417
86
661
220
1,018
109
321
26,894
4,109
122
321
1,522
142
1,286
182
492
41 ,546
9,135
20
68
663
2,183
701
3,351
550
1,579
26,602
4,875
15
178
1,831
202
1,642
203
750
10,969
1,624
68
806
65
463
92
125
30,444
6,720
12
356
2,611
1 ,688
261
1,015
12,281
1,268
82
129
42
185
463
72
286
30,934
11,368
519
6,538
244
2,417
238
1,364
-------
I
o
<£>
O
Sullivan
Table III-D-105
IN-3 FARMING, 1969
Greene Knox Daviess
Martin
Gibson
Pike
Duboi s
Change 1964-69:
Farms
Acreage
Average:
Land Value
Return per Acre
Class I-V Farms:
Number
Avg. Acres
Avg. Return
Other Farms:
Number
Avg. Acres
Avg. Return
% Return From:
Crops
Dairy
Livestock
Poultry
-7.9
-3.0
$349
61
641
288
$18,563
329
49
$ 987
65
4
30
2
-6.4
1.3
$273
52
695
268
$16,283
526
81
$ 978
43
6
49
1
-8.4
.8
$431
86
1,005
289
$25,309
187
50
$ 1,172
60
2
36
1
-9.9
-2.9
$396
93
1,029
205
$20,431
346
51
$ 1.03Z
36
7
. 42
15
-5.6
-7.1
$202
52
933
212
$16,245
327
48
$ 604
18
6
61
14
-5.7
3.4
$372
84
909
266
$23,316
310
49
$ 1,128
55
3
35
7
-16.2
- 0.7
$267
70
399
250
$19,274
270
54
$ 954
41
3
36
20
-11.0
- 2.0
$286
130
896
211
$30,623
284
92
$ 1,351
8
5
41
46
-------
One distinctive characteristic of farming in Dubois County is the
low percentage return from crops and the high return from dairy farming.
However, there is nothing to indicate that this is a factor related to
the higher profitability. Generally counties in this area show con-
siderable variation in types of farming operations.
Except for Martin County, counties have all experienced some farm
consolidation with little or no loss of farm acreage.
7.3.8. INCOME
Income levels in these counties are moderate for the ORBES region.
There is little difference between median family income and median farm
family income and little variation among counties. By 1973, income had
not risen as rapidly in Martin County as in the others. Sullivan County,
however, had improved its position in relation to the others.
Table III-D-106
IN-3 INCOME
1969 Median
Family
1969 Median
Farm family
1969
Per capita
1973
Per capita
1974 Median
Family EBI
Sullivan
Greene
Knox
Daviess
Martin
Gibson
Pike
Dubois
$7,427
8,190
7,859
8,131
7,894
7,950
7,524
8,997
$6,895
8,080
8,637
7,478
8,557
8,403
6,818
8,146
$3,060
2,885
3,059
3,194
3,102
3,259
3,076
3,377
$4,594
4,014
4,623
4,521
3,781
4,987
5,369
4,698
$8,504
9,640
9,386
9,080
8,599
10,181
9,620
11,240
7.3.9. IMPACT ASSESSMENT
Sullivan, Greene, Knox, Daviess, Martin, Gibson, Pike and Dubois
Counties form a large block of counties slated for power plant develop-
ment in southwestern Indiana. They vary greatly in terms of boomtown
potential and predominant environmental orientations.
The counties which have already experienced considerable power
plant development (Gibson, Pike and Sullivan) are all within commuting
distance of a construction workforce and are likely to be amenable to
further development. Two of these counties also produce coal and two
are part of SMSA's. The orientation of Gibson and Sullivan Counties would
appear to be primarily instrumental. Pike County too has this pre-
dominant orientation as well as an aesthetic sub-orientation, given the
high proportion of the land devoted to forest.
III-D-191
-------
Candidates for the boomtown syndrome include Dubois, Daviess, and
Greene Counties, and possibly Martin County as well. Dubois and Martin
are the most economically diversified of these four and better able to
cope with boomtown demands. However, Dubois County, being affluent,
and self-contained, probably has a high sentimental environmental
orientation as well as the aesthetic sub-orientation. It is likely to
be highly resistant to power plant development. This is generally true
for Martin County as well. However, Martin County has had previous
experience with large-scale development and might be slightly more
receptive, but still basically a likely locus of opposition.
Daviess and Greene Counties have different environmental orienta-
tions, with Daviess being characterized as having the primoridal sub-
orientation and Greene having a mix of the instrumental, the aesthetic
and the prestige sub-orientations. Greene is a coal county, near a
major university, and has an older population so we would expect the
conflict of orientations to manifest itself in this county. The
instrumental orientation and attendant power plant development will
probably prevail. In Daviess County, residents would probably be
opposed to development and ineffective in their protests. The community
would seem to be inept in coping with boomtown strains as well.
Knox County has a mix of orientations present, primarily prestige
and instrumental, and lies within commuting distance from Evansville
and hence is not a boomtown candidate. Unless college students organize
opposition groups, we would expect little resistance to power plant
development and that the county would prosper from a plant.
III-D-192
-------
7.4. LAWRENCE (38,038) AND JACKSON (33,187) COUNTIES
Two counties in south-central Indiana with no current power
generating facilities will receive one single-unit coal-fired
plant under Scenario I. The east fork of the White River con-
verges with the Muscatatuck River in Jackson County and continues
across Lawrence County towards the Wabash. These adjacent counties,
about 75 miles south of Indianapolis, are each connected to that
metropolitan area by a major highway (State 37 and U.S. 65). In
addition, 27 miles north on State 37 from central Lawrence County
is Bloomington (42,890). On U.S. Highway 65, about 25 miles north
of eastern Jackson County is Columbus (27,141).
The largest town in Jackson County is Seymour (13,352), close
to both the above highway and the river, but there are also two
other communities over 1,000: Brownstown (2,376) and Crothersville
(1,663).
Lawrence County has a similar distribution of communities:
Bedford (13,087), Mitchell (4,092), Englewood (1,219) and Oolitic
(1,155).
7.4.1. LAND USE
Both Jackson and Lawrence Counties have similar proportions of
land in farms (69.9% and 60.1% repectively) and in forest (36.8%
and 43.4%). In addition to commercial forest, Lawrence contains a
large section of the Hoosier National Forest in its southwest corner.
Another section of the Hoosier National Forest covers the top parts
of these counties where they meet.
Both counties are outside the coal producing region but have
some quarrying of sand and gravel, stone, cement and clays.
7.4.2. RESIDENCE
Jackson and Lawrence predominantly are rural with relatively
sparse settlement and a relatively stable population.
Both counties experienced out-migration during the sixties and
a reversal of the trend in the early seventies. Losses from the
farm population were disproportionately large, especially in Lawrence
County. In spite of the losses due to out-migration, both counties
grew moderately in the sixties. With the reversal of migration
trends, Lawrence County is experiencing growth but Jackson is not
quite maintaining its size.
III-D-193
-------
Table III-D-107
IN-4 POPULATION DISTRIBUTION, SHIFTS AND STABILITY
Same County, 1965
Jackson
84.7
Lawrence
Density per square mile
% Urban
% Rural non-farm
% Farm
Changes 1960-70
Population
Migration
Farm sector
Changes 1970-74
Population
Migration
% Residing in
Birth state
Same state, 1965
64
40
45
15
8.6
-2.1
-21.0
-0.4
3.0
81.4
92.2
83
45
42
13
4.0
-4.6
-42.0
4.2
7.0
84.2
92.2
85.5
7.4.3. AGE STRUCTURE
Median ages in these counties are:
Jackson
Lawrence
28.8
30.4
The age profiles are similar and do not show any striking characteris-
tics.
7.4.4. MARITAL STRUCTURE
These counties have few single people and the percentages of the
widowed are moderate to low. Over 70% of men and over 65% of the women
are married. As would be expected from age levels, many families are
probably in the middle and early stages of the family cycle so there are
above average percentages of families with children under 18.
7.4.5. EDUCATION
Less than half the adult population have finished high school, the
median school years completed being slightly less than 12. A small
percentage of the resident population have gone to college (Jackson 5.3%,
Lawrence 4.8%). These counties are in the middle range for the ORBES
region. Neither county has any substantial college population.
III-D-19'4
-------
7.4.6. HOUSING
These counties are in an area where an overwhelming percentage of
housing units are occupied by the owner. Increases in numbers of house-
holds and housing units have been somewhat larger than would have been
expected from population growth figures, but not excessively so.
Building rates have been moderate. There is a marked difference in
housing values between the two counties but this may be related to the
differences in building rates and percentages of houses lacking plumbing.
That is, in Jackson County the larger percentage of new houses which
would tend to have all plumbing facilities would bring the median value
of houses up as well.
Table III-D-108
IN-4 HOUSING, 1970
Jackson Lawrence
Changes 1960-70
Households 14.4 11.6
Housing Units 16.4 14.3
Average
House Value $12,138 $19,761
Rent 92 88
% Units:
In One-Unit Structures 88.2 86.0
Built Since 1960 23.4 19.6
Owner-Occupied 80.8 81.2
Lack some plumbing 10.5 13.1
7.4.7. ECONOMIC ACTIVITIES
The predominant non-agricultural activity in both counties is
manufacturing. The most important industry in Jackson County is fabri-
cated metal and in Lawrence County it is stone, clay and glass products.
Table III-D-109
IN-4 COUNTY BUSINESS PATTERNS, 1973
Jackson Lawrence
Total
In CBP 9,153 8,226
Agriculture 16 49
Mining
Construction 328 413
Manufacturing 4,704 3,730
Transportation 414 285
Trade 2,496 2,198
Finance 299 372
Services 819 1,120
III-D-195
-------
Jackson County also has the following industries employing over 100
persons: 1) rubber and plastics, 2) transportation equipment, 3)
leather products, 4) apparel and textiles, 5) paper products and 6)
food. Lawrence County has the following industries: 1) apparel and
textiles, 2) primary metal, 3) fabricated metal, 4) transportation
equipment, and 5) food.
This industrial emphasis is consistent with the high percentages of
craftsmen and foremen in these counties.
The presence of options may be one of the reasons that such small
percentages of the farms are potentially full-time operations (class
I-V) in Lawrence County (48%) although the low profitability is un-
doubtedly a factor as well.
Table III-D-110
IN-4 FARMING, 1969
Jackson Lawrence
Average
Land Value $330 $186
Return Per Acre 89 39
Changes 1964-69
Farms -1.2 -18.6
Acreage 1.4 -7.0
Class I-V Farms
Number 898 483
Avg. Acres 227 270
Avg. Return $22,444 $ 12,967
Other Farms
Number 445 521
Avg. Acres 65 88
Avg. Return $ 1,022 $ 1,019
% Return From:
Crops 29 22
Dairy 6 11
Livestock 41 60
Poultry ,23 6
The lower profits from farming are reflected in the large decrease
in both farms and acreage and the low cost of farm land in Lawrence
County. Although there is some consolidation in both counties, sub-
stantial acreages are being removed from farming in Lawrence County.
The differing emphasis on types of farming operations are not enlightening.
HI-D-196
-------
7.4.8. INCOME
Income levels are moderate in these counties with Jackson County
consistently the higher.
Table III-D-111
IN-4 INCOME
Jackson Lawrence
1969
Median Family $ 9,007 $ 8,559
Median Farm Family 9,761 8,342
Per Capita 3,533 3,290
1973
Per Capita 4,760 ' 4,327
1974
EBI 11,231 10,688
Few in these counties are below poverty income levels.
7.4.9. IMPACT ASSESSMENT
Lawrence and Jackson Counties in Indiana have a rural non-farm,
stable population comprised mainly of married people with children. The
people work primarily in the manufacturing and trade areas. The pre-
dominant orientation is sentimental but both counties have a substantial
aesthetic sub-orientation. Lawrence is a boomtown candidate county while
Jackson might possibly escape this if workers commute from Louisville
and if the plant were sited in the southern part of the county.
Lawrence County, being the poorer of the two, is likely to be more
receptive to power plant development.
The economic infrastructure for coping with the boomtown syndrome
is relatively well-developed compared to other rural areas in the region
in both these counties and we suspect opposition to the plant would be
minimal so long as the aesthetic sub-orientation did not come into
conflict with the instrumental one.
-------
7.5. POSEY (21,740), WARRICK (27,972), SPENCER (17,134), PERRY (19,075),
CRAWFORD (8,033) AND HARRISON (20,423) COUNTIES
Most counties along the Ohio River are slated for power plant
development by the year 2000. In the western half of the state there
are six such counties. At present only two have generating facilities.
At West Franklin on the Ohio River, a few miles west of Evansville, is
a coal-fired plant with a present capacity of 225 megawatts and two
units of 265 and 350 megawatts in the planning stage. The generating
capacity by 1985 should be 870 for Posey County. Warrick has a coal-
fired plant at Yankeetown, about 15 miles east of Evansville, with a
generating capacity of 1,145 megawatts. None of the other counties
have power plants operating at present although a 980 megawatt plant
which was originally planned for Sullivan County will now be built in
Spencer County.
Under all scenarios, this area will have new power plants.
Scenario I posits eight coal and three nuclear units for the area.
Two-unit (2,000 megawatts) coal-fired plants will be sited in Perry
and Harrison Counties. Single-unit coal-fired plants will be built in
Posey, Warrick, Spencer and Crawford Counties. Single-unit nuclear
plants will be built in Spencer, Perry and Harrison Counties.
Under Scenario II there will be seven coal and six nuclear units.
Perry and Harrison Counties will each have a two-unit coal and a two-
unit nuclear plant. Spencer and Crawford will each have a single-unit
coal and a single-unit nuclear plant. Posey will have a single-unit
coal-fired plant.
Under each of the low energy Scenarios III and IV, this area will
have two single-unit plants. Scenario III would site them in Posey
and Crawford Counties. Scenario IV would site them in Perry and
Harrison Counties.
Because of the heavy concentration of plants in this area, the
above information will be presented in a chart.
These counties form a string along the Ohio River from west to
east broken only once, by Vanderburgh County, site of Evansville.
Posey County, in the southwestern tip of the state is bordered on the
west by the Wabash and on the south by the Ohio River. Seventeen miles
directly east of the major town, Mount Vernon (6,770), is Evansville.
The other counties stretch from Evansville to the Louisville/New
Albany SMSA. In Warrick and Perry Counties there are also population
centers with a little over 5,000 people: Boonville (5,736) in Warrick,
and Tell City (7,933) in Perry. Seven communities have between 1,000
and 3,000 residents.
III-D-198
-------
Table III-D-112
IN-5 POWER GENERATING CAPACITY
Posey Warrick Spencer Perry
Crawford Harrison
1975: Fossil
Nuclear
1985: Fossil
Nuclear
2000 (Scenario I)
Fossil
Nuclear
2000 (Scenario II)
Fossil
Nuclear
2000 (Scenario III)
Fossil
Nuclear
2000 (Scenario IV)
Fossil
Nuclear
225
870**
1 ,870*
1 ,870*
1,520*
870
1,145
1,145
2,145*
1,145
1,145
1,145
980
1 ,980*
1 ,000*
1 ,980*
1 ,000*
980
980
2,000**
1 ,000*
2,000**
2,000**
1 ,000*
1 ,000*
1 ,000*
1 ,000*
650
2,000**
1 ,000*
2,000**
2,000**
1 .000*
* = new unit
A major highway, 1-64, crosses the northern parts of these counties
going from Louisville to southern Illinois and crossing U.S. 41 just
north of Evansville. Otherwise this area is serviced only by minor
highways.
In Kentucky, south of Spencer County, is Owensboro. As a conse-
quence of the location of the urban centers and the highway system,
residents in all but the southern part of Perry County should have
easy access to one of the urban centers along the river. There are
few other urban areas in the southern interior of the state.
7.5.1. LAND USE
Two of these counties, Perry and Crawford, have over half of
their land in forest and less than half in farmland, most of the
counties being inside the Hoosier National Forest. Posey and Spencer
Counties, on the other hand, have most of their land devoted to
farming. Nevertheless, substantial portions of the land are forested.
The other three counties are between these two extremes.
III-D-199
-------
Table III-D-113
IN-5 LAND USE
% Land In
[Farms, 1969 Forest, 1967]
1974
Coal
Production
1,000's Tons
1973
Mineral
Production:
Value
Posey
Warrick
Spencer
Perry
Crawford
Harrison
87
52
80
40
42.9
63.6
16.0
.5
.5
30.
27.
58.4
56.8
42.9
W
9,263 $ 51,204,000
561 2,826,000
W
W
1,260,000
Posey, Warrick and Spencer Counties are all underlain by coal
bearing rock but only Warrick and Spencer produced coal in 1974.
Warrick's production was high, this being the most important mineral
in the county. Stone, sand and gravel were quarried in varying amounts
in all counties.
7.5.2. RESIDENCE
Warrick and Posey are part of the Evansville SMSA, although the
population in both counties is predominantly rural. Crawford County
is completely rural in residence and the other counties are mixed but
predominantly rural.
Table III-D-114
IN-5 POPULATION DISTRIBUTION
Density % Urban
Rural non-farm % Rural farm
Posey
Warrick
Spencer
Perry
Crawford
Harrison
53
72
43
50
26
43
31
21
15
42
0
13
49
68
56
47
75
59
20
11
29
11
25
28
Higher than average proportions of the population in Spencer,
Crawford and Harrison Counties live on farms, but as in other counties
in the ORBES region, the farm population is declining disproportionately.
These counties have especially high rates of decline.
III-D- 200
-------
Table III-D-115
IN-5 POPULATION SHIFTS
1960-70: 1970-74:
[Population Farm Net ] [Population Net ]
Population Migration Migration
Posey 13.1 -21.3 4.9 3.3 5.3
Warrick 18.6 -41.2 9.5 14.8 19.0
Spencer 6.6 -.418 .2 2.5 3.4
Perry 10.7 -40.6 .4 -2.6 -0.1
Crawford -4.1 -53.7 -8.0 6.6 8.3
Harrison 6.3 -29.4 -2.3 10.4 13.2
As can be seen in the table, except for Crawford County, these counties
grew during the sixties and in all but Harrison County, the growth was to
some extent due to in-migration. Only Posey and Warrick, the two SMSA
counties, had substantial in-migration, however. By 1974 there had been
changes. The trends in Posey and Warrick Counties continued, somewhat
accelerated in the latter. Crawford County had begun to grow and
receive in-migrants. Harrison County had also begun to have in-migra-
tion, thus increasing the rate of growth. Perry had begun to lose
population. Spencer is manufacturing its growth rate but in-migration
seems to form a larger proportion of this growth.
Table III-D-116
IN-5 RESIDENTIAL STABILITY
% Residing in: Birth State Same State, 1965 Same County. 1965
Posey
Warrick
Spencer
Perry
Crawford
Harrison
74.1
78.9
76.7
80.8
83.8
76.4
89.6
92.1
90.5
92.1
92.9
88.7
81.0
80.0
82.1
84.6
83.1
83.1
These, like many border counties, tend to have slightly higher per-
centages of the population who come from other states. In this case,
most of the migrants come from the south, probably Kentucky. Never-
theless, these counties are relatively stable in residence and, even
in the SMSA counties, over 80% of the population were residing in the
same county for a period of five years or more.
7.5.3. AGE STRUCTURE
Median ages in all these counties are about average for counties
in the ORBES region:
III-D-201
-------
Posey 29.1
Warrick 28.1
Spencer 29.0
Perry 28.0
Crawford 31.9
Harrison 28.7
Examination of age profiles indicates that Warrick has an almost
perfect age pyramid with age cohorts gradually decreasing in size from
childhood. Since most counties profiled for the ORBES study exhibit
relatively small cohorts for young adults, we suggest that the in-
migration to this county is disproportionate to these age groups.
Posey, Spencer, Perry and Harrison Counties show characteristic
profiles for the region, a sharp decline in relative numbers after the
teens, and a small increase in relative sizes of middle-aged groups. The
profile of Crawford County differs in that the increase begins later, at
age 55 or older.
7.5.4. MARITAL STRUCTURE
Marital structure varies but generally, this is an area where most
people are married, more than average numbers of families are in the
middle stages of the family cycle and most families are intact and
many children are still at home. This is not a locus for settlement
of divorced people and there are relatively few families with a female
head.
7.5.5. EDUCATION
Educational levels in the SMSA counties are somewhat higher than
in the other counties in that median numbers of school years completed
is somewhat higher. Even in Warrick County, however, with the highest
educational level, only 6.4% have completed college. In all the other
counties, less than 5% have completed college and less than half have
completed high school. There are only very small resident college
populations.
7.5.6. HOUSING
In these counties there have been substantial gains in the numbers
of households and housing units, but the building of new units has not
been especially rapid although it has been high enough to accommodate
growth and provide for some replacement. It should be noted that the
percentage of housing units which lack some plumbing is especially high
in Crawford County. Generally, median values and rents for housing units
are low in this area, but especially marked in Crawford County. This
is likely related to the large proportion of houses lacking plumbing or
other conveniences.
III-D-202
-------
Table III-D-117
IN-5 HOUSING, 1970
Posey Warrlck Spencer Perry Crawford Harrison
$11,638 $12,414
Changes 1960-70
Households 15.1 23.4
Housing Units 15.9 20.0
Average:
House Value
Rent 86 80
% Units
One-Unit Structures 87.4 88.5
Built Since 1960 21.6 26.9
Owner-Occupied 76.2 80.8
Lack Some Plumbing 9.0 10.1
8.8
10.4
$9,182
73
89.1
20.8
79.4
13.9
16.3
16.7
0.5
12.9
$11,134 $6,851
76 63
81.5
22.2
80.9
13.8
89.9
14.6
85.8
30.0
12.4
16.3
$12,051
76
89.2
21.0
84.6
17.8
7.5.7. ECONOMIC ACTIVITY
Manufacturing is the most important non-agricultural activity in
Posey, Warrick, Perry and Harrison Counties. Crawford County has more
of its few workers involved in trade than in anything else, although
a relatively high percentage are in construction. Perry is the only
county which attracts in-commuters although Warrick has about the same
ratio of jobs to population.
Table III-D-H8
IN-5 COUNTY BUSINESS PATTERNS, 1973
Perry Warrick Spencer Perry Crawford
Harrison
Total Population
In CBP
Agriculture
Mining
Construction
Manufacturing
Transportation
Trade
Finance
Services
21 ,940
4,272
-
102
314
1,938
165
1,207
108
403
27,972
7,968
-
677
1,160
4,005
354
1,023
210
499
17,134
2,449
-
-
71
582
110
744
96
488
19,075
5,111
-
-
200
3,165
132
795
307
358
8,033
600
-
113
80
48
-
190
41
57
20,423
3,248
42
81
179
1,312
164
865
108
486
III-D-203
-------
The most important industry of Warrick County is in: 1) primary
metals, but there are also factories producing, 2) apparel or textiles
and 3) electrical equipment.
Perry County, with the next largest number of manufacturing
employees, has factories making: 1) furniture, 2) electrical equip-
ment, 3) lumber and wood products, and 4) stone, clay and glass pro-
ducts.
Posey County produces: 1) chemicals and allied products, 2)
petroleum and coal products and 3) fabricated metal products.
Harrison County produces: 1) furniture, 2) food and 3) lumber
and wood products.
Spencer County industry is almost completely in stone, clay and
glass products, employing 559 persons. The rest of the manufacturing
jobs are in printing or publishing. It should be noted that for
Spencer County, which is known to have high coal production, the number
of miners is withheld. There are, however, 358 jobs unaccounted for
and many of them are likely to be in mining.
The three eastern counties and the three western counties are
easily distinguished in farming. Posey, Warrick and Spencer have
experienced some farm consolidation during the late sixties but there
has been little or no loss in farm acreage. Farming is more profit-
able in these counties and grain crops are emphasized to a greater
extent than in the other counties.
Perry, Crawford, and Harrison Counties have apparently experienced
a large diversion of farmland to other uses. The farming that is done
is more heavily involved with livestock and poultry raising and is less
profitable than in the counties to the west. Land is also less valu-
able.
Although experiencing the same trends, Harrison County has not
lost land at the same rate and land values are not as low as in Perry
and Crawford Counties. It is possible that the farm acreage is being
diverted to forest in these latter two counties since the greater part
of these two counties are within the boundaries of the national forest.
III-D-204
-------
Table III-D-119
IN-5 FARMING, 1969
Posey Warn' ck Spencer Perry Crawford Harrison
Change: 1964-69
Farms
Acreage
Average:
Land Value
Return per acre
Class I-V Farms
Number
Avg. Acres
Avg. Return
Other Farms:
Number
Avg. Acres
Avg. Return
% Return From:
Crops
Dairy
Livestock
Poultry
$21
$1
-4.6
4.4
$378
66
696
314
,627
215
53
,112
65
3
30
-5.8
-0.4
$348
58
444
249
$16,320
322
64
$ 1,066
52
9
31
-6.3
1.2
$281
64
766
230
$16,263
$1
370
73
,595
38
8
45
-29.8
-27.9
$171
36
$11
297
226
,119
285
112
$997
18
15
54
13
-29.9
-20.0
$184
36
228
231
$12,288
315
105
$906
10
13
36
39
-12.9
-12.7
$241
58
836
159
$12,509
841
74
$ 1,005
17
15
41
27
7.5.8. INCOME
Income levels are higher in the two SMSA counties and in Harrison
County which is close to the Louisville SMSA, and lowest in Crawford
County. This pattern persisted through 1974. Generally, income levels
are in the middle range for the ORBES region.
Table III-D-120
IN-5 INCOME LEVELS
1969 Median
Family
1969 Median
Farm Family
1969
Per Capita
1973
Per Capita
1974 Median
Family EBI
Posey
Warrick
Spencer
Perry
Crawford
Harrison
$ 8,483
9,162
7,785
8,003
6,655
8,478
$ 7,777
8,808
7,042
5,543
6,288
8,263
$ 3,407
3,354
2,518
2,733
2,399
2,975
$ 4,805
4,324
3,968
3,602
3,259
3,953
$10,824
12,060
10,696
10,887
8,266
10,318
III-D-205
-------
7.5.9. IMPACT ASSESSMENT
None of the six counties under consideration here, Posey, Perry,
Warrick, Spencer, Crawford, or Harrison, is a candidate for the boom-
town syndrome because of proximity either to Evansville or Louisville.
They do, however, differ in their environmental orientations and likely
receptivity to power plant development.
Perry and Crawford Counties both have primarily an aesthetic sub-
orientation, being scenic forested areas. Moreover, Perry is the site
of a seminary, suggesting the moral-religious sub-orientation is present
there as well. The population here is somewhat older and this factor
and the predominant orientation suggest that there would be considerable
opposition to power plant development in these counties, both from
within the county and from residents of nearby counties as well.
Posey and Warrick Counties, on the other hand, being part of SMSA's
and being affluent, seem to have both the instrumental and sentimental
(prestige) orientations but which are not in conflict. We predict that
a power plant would be easily accepted by the residents.
Spencer County, by virtue of being a coal-producer, is probably
instrumental in predominant orientation though the rural residents
probably have a sentimental orientation as well. We would expect
conflict between these orientations and the people holding them, but
that the instrumental one would prevail.
Harrison County, which appears to be urbanizing but as a suburban
community, probably has the prestige sub-orientation as its predominant
mode of relating to the environment. We would expect opposition to the
plant on these grounds unless it were sited in a very rural area.
III-D-206
-------
7.6. CLARK (75,876), JEFFERSON (27,006), SWITZERLAND (6,306), OHIO
(4,289) AND DEARBORN (29,430) COUNTIES
Five counties along the Ohio River north of the Louisville/New
Albany SMSA will have new power plants in the next twenty-five years.
Two counties, Clark and Switzerland, each have small plants with gener-
ating capacities of less than 65 megawatts. Ohio has no present power
facility. Both Jefferson and Dearborn already have coal-fired plants
generating over 1,000 megawatts each, and Jefferson County is the
planned site of the controversial Marble Hill nuclear power plant.
Each of these counties will receive some new facility under the high
energy scenarios. For simplicity, the distribution is presented in
table form.
Table III-D-121
IN-6 POWER GENERATING CAPACITY
Clark Jefferson Switzerland
Ohio Dearborn
1975: Fossil
Nuclear
1,303
1,098
1985:
Fossil
Nuclear
1 ,303
2,260**
1,098
2000 Scenario I
Fossil 1,000*
Nuclear
1,303
2,260
1 ,000* 1 ,000*
1 ,000*
2,098*
2000 Scenario II
Fossil 1,000** 1,303 1,000*
Nuclear 1,000 3,260* 1,000*
1,000*
1,098
1,000*
( * = new unit)
These five counties stretch in a string from the Louisville/New
Albany SMSA to the Cincinnati SMSA. Half-way between, and also on the
river, is Madison (13,081) in Jefferson County. This is the largest
community in this area outside the SMSA's. There are several other
communities with over 4,000 residents but these are either in Clark
County, close to the urban area, or in Dearborn County, close to Cincin-
nati. There are three other communities over 1,000 in the area. Since
major highways in Indiana tend to lead to Indianapolis in the center of
the state, counties along this stretch of the river, are serviced by
minor highways.
III-D- 207
-------
7.6.1. LAND USE
Ohio County has the largest percentage of land in farms, but in
these counties in general, about two-thirds of the land is farmland and
from a fifth to a third of the land is forested.
Both Clark and Dearborn Counties are included in SMSA's but it is
impossible to describe the extent and kind of urban land use.
Part of northern Jefferson County is included in the Jefferson
Proving Ground, a military installation.
These counties are all outside the coal producing areas of Indiana,
although there is a small amount of quarrying for clays, sand, gravel
and stone. This area also does not appear to have many outdoor recrea-
tional facilities. There is a falls near Madison and in neighboring
Jennings County is a wildlife refuge. Most residents, at least of Clark
and Jefferson Counties, should find the Hoosier National Forest reasonably
accessible for a long day or a weekend.
Table III-D-122
IN-6 LAND USE
% Farm Land % Forest
Clark 60.6 37.6
Jefferson 68.2 26.6
Switzerland 69.0 27.8
Ohio 78.6 24.2
Dearborn 62.5 21.3
7.6.7 RESIDENCE
Jefferson and Clark Counties are predominantly urban, but the
other counties have predominantly or completely rural residence patterns.
Table III-D-123
IN-6 POPULATION DISTRIBUTION, 1970
Density % Urban % Rural Non-Farm % Rural Farm
(per square mile)
Clark
Jefferson
Switzerland
Ohio
Dearborn
198
74
29
49
96
69
60
0
0
43
24
21
50
72
42
7
19
50
28
15
III-D-208
-------
Variation in density is striking but a large part of the population of
Clark County is concentrated in the southernmost tip, close to the
urban area.
During the sixties, the two western counties close to the Louis-
ville SMSA grew and had moderate to high in-migration. Switzerland
had a similar rate of decline. Ohio and Dearborn grew slightly even
though losing residents through out-migration.
Table III-D-124
IN-6 POPULATION SHIFTS
Clark Jefferson Switzerland Ohio Dearborn
1960-70
Population 20.8 12.2
Migration 7.9 2.5
Farm sector -13.8 -14.1
1970-74
Population 2.7 0.5
Migration 6.7 2.8
-11.1
-14.0
-22.5
5.1
5.3
3.0
-3.7
-6.6
6.4
7.1
2.6
-7.3
-37.1
2.4
4.5
Since 1970, all five counties have been growing and have had low
to moderate levels of in-migration. As in the rest of the ORBES region,
losses from the farm sector were the pattern.
Table III-D-125
IN-6 RESIDENTIAL STABILITY
Clark Jefferson Switzerland Ohio
Dearborn
Residing in:
Birth State 74.1 69.9
Same County, 1965 75.5 77.7
Same State, 1965 83.5 87.8
77.2
85.0
91.6
75.5
77.3
92.7
65.7
83.1
87.6
Dearborn has the greatest proportion of residents who were born in
another state. Nevertheless, it does not appear to be any less stable
residentially than the other counties. As expected, the two rural
counties are slightly more stable residentially.
7.6.3. AGE STRUCTURE
Median ages, though slightly higher in the two rural counties of
Switzerland and Ohio, are not particularly high for the region:
III-D-209
-------
Clark 26.4
Jefferson 28.2
Switzerland 33.9
Ohio 30.4
Dearborn 28.9
Examination of age profiles indicates that although median ages are
similar, composition varies. Jefferson, Dearborn and Switzerland have
the usual characteristics of age profiles in this region. There is a
sharp decrease in size of cohorts after the teens and the middle-aged
cohorts are larger than young adult cohorts. The major difference among
these three counties is the age of the largest adult cohort. In
Jefferson and Dearborn Counties, it is the age 45 to 49 cohort, while
in Switzerland County it is the age 55-59 cohort, thus, accounting for
the higher median age.
The profile of Clark County shows a much more regular decrease in
size of cohorts from childhood to old age with no sharp decreases or
increases. Ohio County has an atypical profile. Age cohorts for
ages 20 through 49 are roughly equal, then there is a sudden decrease
and cohorts for ages 50 through 74 are roughly equal. Since Ohio is
a very small county in area as well as population, it is possible that
this unusual profile represents local residential patterns of distri-
bution.
7.6.4. MARITAL STRUCTURE
Age structures and degree of urbanization appear to be factors,
correlating with marital structure. Rural Switzerland and Ohio have
relatively few single people. Jefferson County is a locus for single
people. Both Jefferson and Clark Counties are part of an urban cluster
with high percentages of divorced women. The moderate age levels
militate against excess numbers of the widowed except in Switzerland
and Ohio (relatively high percentages of widowed men). As a consequence.
except for Jefferson County, married individuals predominate. Except
for Switzerland County, which has an older population, above average
numbers of families have children under 18.
7.6.5. EDUCATION
Educational levels are higher in the counties close to the SMSA's
and lower in the two rural counties, especially Switzerland. Median
levels range from 9.6 in Switzerland to 11.8 in Jefferson, but in all
counties, less than half of the adult population has finished high
school. Both Clark and Jefferson Counties have college populations of
over 1,000, indicating the presence of small colleges and attendant
faculties. In Jefferson County, this "educated" segment of the population
may have inflated the percentage having attended college, but in the
populous Clark County, this small number of people is unlikely to have
affected the percentage greatly. These percentages, which are still
relatively low, are characteristic of many of the more urbanized
counties for which power plants are being suggested.
III-D-210
-------
Median
School Level
Table III-D-126
IN-6 EDUCATION
% Without
High School Diploma
Completed
College
College
Population
Clark
Jefferson
Switzerland
Ohio
Dearborn
11,
11,
9,
10,
11.3
53.4
51.3
65.5
55.7
54.7
5.6
7.2
3.8
3.8
4.2
1,370
1,065
14
177
7.6.6. HOUSING
Population trends are related in changes to numbers of house-
holds and housing units during the sixties. Switzerland was losing
households. There was still some building in this county but whether
this low level of replacement activity was cause or consequence of
the large numbers of housing units which lack plumbing is an open
question. House values were above average in Clark, Jefferson and
Dearborn. Rents and building activity were high in Clark County. This
area has higher than average levels of home-ownership for the ORBES
region. Other wise, there is little that distinguishes these counties
which are generally in the middle range for ORBES region.
Table III-D-127
IN-6 HOUSING, 1970
Clark Jefferson Switzerland
Ohio
Dearborn
Changes 1960-70:
Households 30.5 18.7
Housing Units 26.6 20.1
Median
House Value 13,287 13,015
Rent 109 95
% Housing Units:
One-Unit Structures 78.8 81.6
Built since I960 32.9 25.0
Owner Occupied 72.6 74.9
Lack Some Plumbing 6.2 8.9
-4.8
-2.1
11,189
75
89,
15,
79,
28.3
5.7
10.5
13,667
75
80.0
19.0
75.1
13.0
7.8
9.3
14,104
84
80
16
77
,2
,3
,7
10.9
III-D-211
-------
7.6.7. ECONOMIC ACTIVITIES
In the three large counties, the major non-agricultural activity is
manufacturing. The magnitude of manufacturing activity varies and
is greatest in Clark County. The major industries in this county
produce: 1) furniture or fixtures, 2) stone, clay and glass products,
3) lumber and wood products, 4) chemicals, 5) rubber and plastics,
6) fabricated metal, and 7) transportation equipment. Dearborn County
produces: 1) food, 2) lumber and wood products, 3) stone, clay and
glass products, 4) primary metals, and 5) machinery. The industries
of Jefferson County are in: 1) electrical equipment, 2) machinery,
3) leather products, 4) apparel or textiles, and 5) food.
Table III-D-128
IN-6 COUNTY BUSINESS PATTERNS, 1973
Clark Jefferson Switzerland
Ohio
Dearborn
Total Population
In CBP
Agriculture
Mining
Construction
Manufacturing
Transportation
Trade
Finance
Services
75,876
20,617
27
826
10,388
1,396
4,945
600
2,271
27,006
7,682
251
3,429
606
2,081
214
1,078
6,306
713
14
13
125
30
38
4,289
339
35
94
47
99
23
20
29,430
7,699
526
4,018
486
1,417
417
794
Switzerland and Ohio each have less than a thousand jobs listed in
County Business Patterns with no category of job emphasized. There are
493 jobs in Switzerland County, however, which are not accounted for.
They are unlikely to be in mining. These two counties also have a
substantial percentage of their population commuting out for work.
Examination of the civilian labor force figures for 1970 points
out several other characteristics. Clark, Jefferson and Switzerland
Counties have relatively large numbers of females and working wives
in the labor force. Jefferson County has relatively high percentages
of workers employed in professions or management and/or the federal
government. The latter category may be largely due to the presence of •
the Jefferson Proving Ground mentioned earlier.
Farming in these counties is just barely a viable economic activity
and in these counties there are almost as many or more "Other" farms
as class I-V farms. Also, Switzerland and Dearborn had large percentages
of farmland diverted to .other uses in the late sixties. The other three
III-D-212
-------
counties maintained about the same farm acreage although some farm
consolidation occurred in Clark County. Farming is fairly evenly
balanced between crops and livestock with dairy farming a close third.
Over half the farmers in all but Switzerland County work at least
100 days off the farm in this area.
Table III-D-129
IN-6 FARMING, 1969
Clark Jefferson Switzerland Ohio
Dearborn
Changes, 1964-69:
Farms
Acreage
Average:
Land Value
Return per Acre
Class I-V Farms
Number
Avg. Acres
Avg. Return
Other Farms
Number
Avg. Acres
Avg. Return
% Return From:
Crops
Dairy
Livestock
Poultry
-5.8
2.9
334
50
549
206
$ 12,642
494
73
$ 1,131
36
17
39
9
2.3
-0.3
254
46
694
170
$ 9,511
622
67
$ 1,263
44
14
39
3
-21.2
-18.9
221
44
469
157
$ 8,283
316
76
$ 1 ,302
46
24
28
2
3.4
2.8
237
45
169
185
$ 10,307
161
77
$ 1 ,334
35
21
39
5
-17.9
-14.3
252
37
410
162
$ 9,323
659
85
$ 1 ,051
22
24
47 .
6
7.6.8. INCOME
Switzerland has the lowest income levels of these counties. In this
county the median farm family's income is also slightly higher than median
family income.
Table III-D-130
IN-6 INCOME
Clark Jefferson Switzerland Ohio Dearborn
1969:
Per
Fami
Farm
1973:
Per
1974:
Capita $
ly
Family
Capita
Family EBI
3
9
9
4
12
,756
,899
,330
,723
,719
$ 3
8
7
4
9
,003 $
,556
,839
,102
,942
III-D-213
2
7
7
3
8
,504
,793
,804
,778
•
,374
$ 3
8
7
4
10
,020
,310
,628
,289
,548
$ 3
8
8
4
10
,630
,901
,257
,796
,929
-------
By 1974 the relative poverty of Switzerland County was apparent.
Income had risen much more rapidly in the other counties.
7.5.9. IMPACT ASSESSMENT
None of the Indiana counties, Clark, Jefferson, Switzerland,
Ohio or Dearborn, are likely to be boomtown recipients though the
relative isolation of Switzerland County suggests the possibility of
a temporary work force staying during the week and returning home on
weekends during the construction phase.
The urban counties, Clark, Jefferson and Dearborn, would appear
to have both the instrumental orientation and the prestige sub-orien-
tation. If proposed power plant construction in Dearborn County is an
addition to the existing plant, we would expect no opposition from and
minimal disruption to the residents. Clark County too would appear
receptive to power plant development. We suggest that the considerable
opposition to the proposed Marble Hill plant has its roots in a relative
shift of orientations from instrumental (economic benefit) to prestige.
Having previously experienced considerable development (the proving
ground and existing power plant), and possibly having had negative
experiences, we would expect less enthusiasm for further development.
Moreover, as people continue to make this area their home, the senti-
mental orientation tends to take hold, and given the relative affluence
of the area, and likely commitment to current prestige and stratifi-
cational patterns, the plant is seen as not needed. The fact that it
is a nuclear plant is, of course, a factor as well.
The rural counties of Switzerland and Ohio may be characterized by
the primordial belonging sub-orientation. The rurality of the residents
and their relative elderliness suggest, that they would not be in favor
of power plant development, though Ohio County would probably suffer
fewer impacts due to its proximity to the Cincinnati SMSA.
III-D- 214
-------
8.1.
3. DEMOGRAPHIC PROFILES AND IMPACT ANALYSIS: OHIO
HAMILTON (924,018), BUTLER (226,207), WARREN (84,925),
MONTGOMERY (606,148), MIAMI (84,342) and CLARK (156,946) COUNTIES
A strip of urbanized counties along the Miami and Mad Rivers in
western Ohio are slated for power related developments in the next
twenty-five years. All of the counties have some power facilities at
present ' but, except for Hamilton and Montgomery Counties, facilities
are small (less than 600 megawatt total per county). Hamilton County has
two very small plants, one medium (438 megawatts) and one moderately
large plant (1064 megawatts). With the loss of three units from these
plants and the building of a new unit (557 megawatts) at the larger plant,
Hamilton County will have a generating capacity of 1516 megawatts by
1985. Montgomery County has several plants with a total generating
capacity of 1,051 megawatts. All the extant or planned plants in these
counties are fossil-fueled.
Concentration of power plants in these counties will be heavy under
either of the high-energy scenarios or under the 100% coal low-energy
scenario. Warren County is the only county which will not have a new
plant under each of the first three scenarios. The distribution will be
displayed in chart form for simplicity. All units are coal-fired.
Table III-D-131
0-1 POWER PLANT DISTRIBUTION
(Megawatts)
Mont-
Hamilton Butler Warren gomery Miami
Clark
1975: 1309
1985: 1516
Scenario I 3516**
Scenario II 2516*
Scenario III 2116*
Scenario IV 1516
* = new unit
389
374
581
581
3374*** 3581***.
2374** 581
974* 1181*
374 581
1051
1051
3051**
3051**
1651*
1051
74
74
117
117
2074** 2117**
2074** 2117**
674* 717*
74 117
These counties extend in a northward direction from the Ohio River
at Cincinnati. Cincinnati, in Hamilton County, is one of the major cities
in Ohio and the ORBES.region. Highways run from this city toward other
major cities of the region. 1-75 runs north through these counties to
Toledo and on to Detroit, with connections all along the way to secondary
urban centers. Butler has two medium-sized cities,. Hamilton (72,354)
and Middletown (48,767). The largest communities in Warren County, just
east of Butler, are Lebanon (7,934) and Franklin (10,075) but Montgomery
County to the north contains Dayton (243,601) as well as ten other
communities with over 10,000 residents. Miami County, like Warren, has
two sizeable towns, Piqua (20,741) and Troy (17,186). Springfield
(81,926) is in Clark County.
III-D-215
-------
The distance from Cincinnati to Springfield is 71 miles. This figure
provides a good indication of the urban concentration in these six coun-
ties. In addition to the above cities and large towns, there are numerous
communities classified by the census as urban. The transportation net-
work is such that one can go in almost any direction with ease.
8.1.1 LAND USE
In spite of the highly urbanized nature of this area, over half of
the land in all but Hamilton County is devoted to agriculture. Hamilton,
on the other hand, has a slightly larger proportion of its land in forest.
Table III-D-132
0-1 LAND USE
%Forest %Farmland Mineral Production 1973
Hamilton
Butler
Warren
Montgomery
Miami
Clark
17.2
12.6
11.2
6.5
4.4
• 5.0
16.7
65.2
69.0
50.4
86.1
82.5
$7,170,000
4,787,000
W
W
W
W
These counties lie outside the coal producing area of Ohio but both
Hamilton and Butler Counties had substantial mineral production, com-
prised mostly of sand and gravel, although stone also was quarried in
Butler County. The same types of quarrying were done in the other
counties but production figures were withheld.
Recreational acreages vary greatly in these counties. There are
three state parks. Hueston Woods, on the border between Preble and
Butler Counties covers 3584 acres, 625 of them water acres. Caesar's
Creek on the border between Warren and Clinton Counties, is under de-
velopment. Buck Creek in Clark County covers 3778 acres, most of them
under water. However, the many cities in this area are likely to have
provided municipal, county, and private outdoor recreational facilities
as well as the indoor recreational and cultural amenities associated
with urban environments. Total acreage devoted to recreational usage
is largest in Hamilton County.
III-D-216
-------
Table III-D-133
0-1 RECREATIONAL LAND
Total Public Private
14,384 10,475 3,909
Montgomery 8,802 5.010 3.792
Miami 3,374 939 2,363
CUrk 7,528 6,210 1,327
8.1.2 RESIDENCE
The high density of settlement and the predominantly urban popu-
lation of these counties distinguish this area from other areas of
potential power related development.
Table III-D-134
0-1 POPULATION DISTRIBUTION
Density
(per sq. mi.) % Urban %Rural Non-farm %Rural Farm
Hamilton
Butler
Warren
Montgomery
Miami
Clark
2230
480
210
1326
207
391
96
78
43
92
58
67
4
19
48
7
32
29
0
3
9
1
10
4
The area has higher than average percentages of migrants from
other states and exhibits a somewhat higher level of residential
mobility than mnay other high impact counties. Nevertheless, the
differences are not as marked as one might expect. Approximately
77% of the population lived in the same county in 1965 and another
10% lived in another county in the same state.. Hamilton County which
retained the largest proportion of its residents for five years, seems
to draw the smallest proportion of its new residents from other
communities in Ohio. One reason for this is the net out-migration
from Hamilton County during the sixties. All the other counties ex-
perienced small to moderate in-migration. Due to natural increase,
they all grew. The unusually high rates of growth and in-migration
in Warren County should be noted, even though most of the counties
grew substantially. This growth did not affect the f.arm sector,
which decreased sharply in all counties.
III-D-23?
-------
Table III-D-135
0-1 RESIDENTIAL STABILITY
Hamilton
Butler
Warren
Montogomery
Miami
Clark
Residing in:
Birth State
66.
64,
65.
62.
79.0
74.2
.6
.4
1
.4
Same County
1965
82.2
76.6
72.7
78.2
79.6
78.1
Same Stati
1965
85.9
86.
88.
84.
90.
87.8
By the early seventies, all but Butler County were experiencing
out-migration. Only in Warren and Miami Counties was natural in-
crease sufficient to conterbalance this loss.
Table III-D-136
0-1 POPULATION SHIFTS
Hamilton Butler Warren Montgomery Miami Clark
1960-70:
Population
Migration
Farm sector
1970-74:
Population
Migration
6.8 13.6
-4.7 .7
-45.6 -20.6
-2.4
-5.0
7.1
3.2
30.1
12.1
-23.9
1.6
-3.0
15.4
1.2
-32.8
-2.1
-5.7
15.7
4.5
-29.0
3.4
-0.1
8.1.3 AGE STRUCTURE
Median ages are relatively low in these counties:
Hamilton - 28.3
Butler - 25.5
Warren - 24.3
Montgomery - 27.4
Miami - 28.1
Clark - 27.8
19.5
8.2
-21.6
-1.1
-4.2
Examination of age profiles indicates that, with small variations,
the pattern is similar in the six counties. Size of age cohorts de-
clines steadily after about age 50. Although there are slightly
smaller numbers in the adult cohorts age 25 to 40, (exception Warren
County) the difference is not large. The largest adult age cohorts are
between ages 40 and 50. Again the exception is Warren Count which has
an almost perfect pyramidal shape. The size of cohorts does not drop
sharply after age 19, probably due to the presence of sizeable college
populations. There is a decline, though not so sharp, after age 24.
III-D-218
-------
8.1.4 MARITAL STRUCTURE
Except for Hamilton and Clark Counties, this area has few widows or
widowers. There are substantial numbers of divorced women in all but
Warren County, the most rural in character. Distribution of single
people varies from county to county. Hamilton and Butler counties have
more than the average numbers of single men, Miami has few. Consistent
with the age levels, all counties have above average to high percentages
of families with children.
In regard to married couples and families, the composition varies
from county to county. Hamilton County, with its many divorced women
and above average numbers of single men, has a low percentage of intact
families and relatively high percentages of families with a female head.
In Butler County, the pattern is similar but not so marked.
Warren County, on the other hand has a high percentage of intact
families and relatively few with a female head. This is also a county
where very high percentage of women are married. Miami County presents
a pattern similar to that in Warren County but less marked.
Montgomery and Clark have fairly well balanced proportions of their
populations in the different marital categories.
8.1.5 EDUCATION
Median levels of schooling place Montgomery, Miami and Clark in the
highest range for the ORBES region, and the other counties in the middle
range. The percentages of those who have finished high-school are con-
sistent with this division. The segment of the population which has
completed college, however, appears to correlate most closely to large
urban centers and to the presence of sizeable college populations.
Table III-D-137
0-1 EDUCATIONAL LEVELS
• Hamilton Butler Warren Montgomery Miami Clark
% Without high-
school diploma
% Completed
college
College population
49.1
52.2 54.6
12.7 8.5 5.9
34,976 12,830 1,036
44.5
11.2
18,684
44.3 49.2
6.9 7.2
670 4,492
8.1.6 HOUSING
Not surprisingly, house values in these urban counties are among
the highest in the ORBES region. Also, relatively few houses lack
plumbing. Hamilton County should be noted for the low percentages of
home owners and one-unit structures. Warren County, on the other hand,
has the highest? percentages of home owners and one-unit structures, with
the percentages in Miami County being almost as high.
III-D-219
-------
All counties gained substantial numbers of households and housing
units and had moderate to high levels of building activity during the
sixties. These figures are consistent with the population growth during
the same period.
Table III-D-138
0-1 HOUSING - 1970
Hamilton Butler Warren Montgomery Miami Clark
Changes 1960-70:
Households
Housing units
Median:
House values 1
Rent
%Housing units:
In one-unit struc.
Built since 1960
Home owners
Lack some plumbing
11.7
11.8
8,710
97
53.9
22.2
56.3
3.1
19.9
18.8
17,195
109
76.4
22.6
69.4
5.5
33.5
31.3
17,171
110
84.8
30.4
73.6
7.4
23.2
21.6
18,775
120
71.6
27.2
64.1
2.3
18.6
17.6
16,517
97
82.2
22.4
73.2
3.1
23.9
22.7
16,400
96
74.3
23.0
68.0
3.8
8.1.7. ECONOMIC ACTIVITIES
These counties with the possible exception of Warren, have large
numbers of jobs listed in County Business Patterns and the distribution
shows a diversified economy with an emphasis on manufacturing.
Table III-D-139
0-1 COUNTY BUSINESS PATTERNS, 1973
Tot. Pop.
In CPB
Agric.
Mining
Const.
Manuf .
Transp.
Trade
Finance
Services
No. manuf.
establishments
employing 100
or more
Hami
924,
383,
18,
145,
24,
98,
24,
70,
Iton
018
753
518
385
378
379
401
968
081
843
237
Butler
226
60
3
29
1
12
3
8
,207
,578
67
88
,252
,930
,968
,919
,292
,878
44
Warren
84
9
2
2
,925
,539
67
16
676
,801
399
,925
—
—
7
Montgomery
606,
227,
10,
104,
10,
52,
9,
38,
148
873
262
374
946
304
680
678
506
714
111
Mi ami
84
23
13
4
1
2
,342
,760
20
51
838
,439
540
,806
,007
,992
26
Clark
156,946
40,801
79
53
1,665
17,863
1,669
10,076
1,961
7,344
26
As can be seen there are many manufacturing establishments making a
variety of products in these counties.
III-D-220
-------
Hamilton and Montgomery Counties, with the largest number of jobs
and the highest ratio of jobs to population have workers commuting to
the county for work. All the other counties have net out-commuting.
Examination of the composition of the 1970 labor force adds little
to the picture. Hamilton and Montgomery Counties have the highest per-
centages of women as well as federal civil servants and professional or
managerial people in the work force.
Figures indicate that land in the four southern counties is being
diverted to other uses with an especially high rate in Hamilton County.
In Miami and Clark Counties, on the other hand, both the number of farms
and farm land is increasing. The profitability of farming is also some-
what higher in these two counties, both per acre and per farm. Hamilton
County farming also appears to be profitable for those few farmers who
have full time operations but the very high price of land and the probable
competition for other uses must be factors in keeping this activity at a
low level of magnitude. Note the unusually small average acreages in
Hamilton and in Montgomery Counties, the most urbanized counties in this
group. Farmers in Hamilton also emphasize vegetables and fruits, more
than in the other counties.
Table III-D-140
0-1 FARMING, 1969
*
Hamilton Butler Warren Montgomery Miami Clark
Change 64-9:
Farms -19.4 -2.0 -7.5 -8.5 13.2 5.3
Acreage -17.0 -4.0 -3.4 -5.3 3.5 1.5
Average:
Land value 803 639 611 873 583 533
Ret. per acre 129 70 72 91 102 108
Class I-V Farms:
Number 244 792 729 729 1,070 795
Ave. acres 136 205 197 155 185 245
Ave. return $22,636 $16,580 $16,859 $17,404 $20,574 $28,292
Other Farms:
Number 247 544 536 747 645 429
Ave. acres 45 53 59 47 40 40
Ave. return $780 $1,038 $1,429 $1,103 $1,144 $1,032
% Return from:
Crops 70 24 47 43 45 36
Dairy 10 23 11 10 9 9
Livestock 14 51 37 43 40 50
Poultry 62 5474
Dairy farming is more important in Butler and Warren counties than
in the other counties. Otherwise there is a substantial amount of crop
farming and livestock raising, sometimes one being emphasized, sometimes
the other.
III-D-22T
-------
8.1.8 INCOME
Income levels are similar in these counties and moderate to high
for the region.
Table III-D-141
0-1 INCOME LEVELS
Hamilton Butler Warren Montgomery Miami Clark
1969:
Med. family
Med. Farm Family
Per cap.
1973:
Per capita
1974:
Family EBI
$10
10
4
5
13
,485
,381
,153
,441
,145
$10
10
3
4
13
,388
,230
,539
,489
,736
$10
11
3
4
14
,679
,131
,219
,395
,717
$11
11
4
5
14
,412
,110
,247
,367
,240
$10
9
4
5
12
,231
,972
,114
,325
,606
$ 9,994
10,235
3,560
4,765
13,481
8.1.9 IMPACT ASSESSMENT
For these Ohio Counties, Hamilton, Butler, Warren, Montgomery, Miami
and Clark, the predominant environmental sub-orientations are clearly the
economic benefit and prestige components. Warren and Miami counties are
the only ones likely to have the additional but secondary sub-orientation
of primordial belongingness, and Butler, Warren and Clark to have the
aesthetic sub-orientation.
Hamilton, Montgomery and Clark, being SMSA counties, are probably not
only receptive to power plant development but will also experience minimal
impact. There are no boomtown candidates in this group of counties. This
is generally true for Butler County as well. The more mixed orientational
character of Warren and Miami Counties suggest possible community conflict
concerning the desirability of power plants, however the general prediction
is eventual acceptance, though Warren County is likely to be more tenacious
in its resistance.
III-D-222
-------
8.2 ADAMS (18,957), CLERMONT (95,725), AND BROWN (26,635), COUNTIES
Three counties along the Ohio River east of Cincinnati are due for
power related development. Two of these counties already have large
generating facilties. Adams County has a coal-fired plant at Aberdeen
and another at Wrightsville producing a total of 3,771 megawatts. Two
new coal-fired units are planned for the latter plant which will bring
generating capacity up to 5,093 by 1985. Clermont County has a 1,442
megawatt coal-fired plant at New Richmond. A nuclear plant is located
at Moscow with one 878 megawatt unit in operation and another scheduled
to go into operation in 1979. The total generating capacity for Clermont
County will then be 3,198. There are no plants in Brown County at present.
Adams County will receive no new units under the scenarios. Both
Brown and Clermont will receive a three-unit (3,000 megawatt) coal-
fired plant under Scenario I and in addition Brown will have a single-
unit nuclear plant. Clermont will have only a two-unit coal-fired plant.
Under Scenario III there would be a two-unit (1200 megawatts) coal-fired
plant in Brown and a one-unit (600 megawatts) coal-fired plant in Clermont
County. Under Scenario IV only one plant would be built, a single unit
(1,000 megawatt) nuclear plant in Brown County.
These three counties border the Ohio River between Cincinnati and
Portsmouth, Ohio. There is one town, Mil ford (4,776) in Clermont County
with a population over 3,000. Adams and Brown Counties have three
communities each with a population between 1,000 and 3,000 and Clermont
has six. Much of the population of Clermont County, including Milford,
is located in the western half of Clermont County close to Cincinnati.
The distance between Cincinnati and Portsmouth is 100 miles so most
residents should be able to go to one or the other city for urban
amenities. Within the area, communities are small although not far
apart. In addition, although an extensive network of highways, state
and federal, link the communities, no major highways cross the area.
U.S. 52 which goes along the river, however, is likely to prove an im-
portant route for any power plant development.
Residents of at least the western two counties are fortunate in
having access to stretches of the Wayne National Forest which extends
northward from Scioto County just east of Portsmouth. There are also
a lake and several state parks in Highland and Pike Counties to the
north.
8.2.1 LAND USE
Clermont, with so much of the county urbanized, has the smallest
proportion of land devoted to agriculture. Adams and Brown Counties
both have over 70% of the land in farms. Adams also has large areas of
forest. Adams and Clermont both have state parks, although acreage is
minimal, slightly over a thousand acres in Clermont and less than a
hundred acres in Adams County. Total recreational acreage in these two
counties is substantial, however.
III-D-223
-------
There is some stone quarrying in Adams and Clermont Counties. Both
Clermont and Brown Counties have some quarrying of sand and gravel. None
of these counties are underlain by coal deposits, however.
Recreational acreage:
Public
Private
Table III-D-142
0-2 LAND USE
Clermont
15,577
12,861
2,716
Brown
Adams
% Forest
% Farm land, 1969
Value of Minerals
Produced, 1973
31.0
55.4
W
24.5
83.9
W $
49.8
72.0
1,790,000
4,279
2,190
2,089
23,744
20,041
3,703
8.2.2 RESIDENCE
Clermont, unlike neighboring Hamilton County, grew substantially
during the sixties and the trend continued into the seventies. The
other counties had different patterns. Brown County grew at a moderately
low rate in the sixties even though there was a small amount of out-
migration. Since 1970 the growth rate has accelerated, partly due to a
reversal of the migration trend. Adams County lost population and had
moderate out-migration during the sixties. Since then the trend has not
only reversed, but growth has been rapid. Farm sector losses are
characteristically large.
Table III-D-143
0-2 POPULATION SHIFTS
1960-70 changes:
Population
Migration
Farm sector
Clermont
19.1
4.4
-26.3
Brown
5.8
-1.5
-20.9
Adams
-b. I
-10.7
-37.5
1970-74:
Population
Migration
9.7
5.2
10.8
7.9
19.9
18.1
In spite of the high density in Clermont County, less than a third
of the residences are classified as urban. This area is predominantly
rural non-farm with substantial proportions of the population living on
farms, especially in Brown and Adams Counties. Even the lower per-
centage in Clermont County with its larger population, means significant
numbers.
III-D-224
-------
Table III-D-144
0-2 DISTRIBUTION OF THE POPULATION
Density, per sq. mi.
% Urban
% Rural Non-farm
% Rural Farm
Cl ermont
209
30
61
9
Brown
54
21
52
27
Adams
32
0
72
28
These counties are neither exceptionally stable nor exceptionally
mobile for the ORBES region. Clermont exhibits a slightly greater de-
gree of residential mobility than the two other counties but this is
to be expected with its higher level of urbanization.
Table III-D-145
0-2 RESIDENTIAL STABILITY
Clermont Brown
Adams
Residing in:
Birth State
Same State, 1965
Same County, 1965
79.6
92.2
81.9
70.0
88.8
75.4
74.9
91.7
78.9
8.2.3 AGE STRUCTURE
Median ages in these counties range from moderate to low in Clermont
County:
Clermont 24.9
Brown 29.0
Adams 31.9
Clermont County is characterized by adult cohorts which are roughly
equal in size until age 50 when they begin to decrease rapidly in size.
In addition there is a sharp decline in size of cohorts between ages
19 and 20. Age profiles for Brown and Adams Counties are similar in
that decreases in relative size of the older cohorts are gradual and
the largest adult cohorts are between ages 40 and 65. The smaller
size of young adult cohorts is more marked in Adams County.
To recap, Clermont County is settled by people who are for the most
part young adults or those in early middle-age. Brown and Adams County
have populations with many more of the elderly and the older middle-
aged are predominant.
^II-D-225
-------
8.2.4 MARITAL STRUCTURE
In Clermont County high percentages of both men and women are
married, relatively large proportion of families are intact and have
children under 18. The low median age militates against an excess
of the widowed in the population.
Adams County is similar in the proportion of married couples but
a relatively high percentage of divorced women and widowed men plus
the higher age levels mean that intact families and families with
children under 18 form a less prominant part in the population com-
position.
Brown as well as Adams County has an above average number of
divorced women in the population.
8.2.5 EDUCATION
Educational levels decline from west to east. Most urbanized
Clermont has the highest level, although all three counties are in the
middle range for the ORBES region, the level of Adams being low for
Ohio. There are no student populations large enough to affect these
figures.
Table III-D-146
0-2 EDUCATIONAL LEVELS
Clermont Brown
Adams
% Without high-school
diploma
% Completing college
College population
56.7
5.5
950
58.8
3.9
244
66.8
3.0
151
8.2.6 HOUSING
In all the housing variables these three counties form a continuum
with urbanized Clermont having more growth and building activity, higher
rents and fewer houses without all necessary plumbing. Adams is at the
other end with almost no growth, little building activity and low house
values. This pattern is consistent with the population growth pattern
for these counties.
III-D-226
-------
Table III-D-147
0-2 HOUSING PATTERNS, 1970
Clermont Brown
Adams
Changes 1960-70:
Households 25.1 9.6 0.3
Housing Units 21.9 12.4 4.2
Median
House value $16,219 $11,995 $8,893
Rent 111 81 75
% of Units:
One unit structures 84.5 85.5 90.6
Built since 1960 25.9 19.4 13.8
Home Owners 79.8 74.2 72.1
Lack some plumbing 9.8 26.1 34.4
8.2.7 ECONOMIC ACTIVITIES
The primary non-agricultural activity in Clermont and Brown Counties
is retail trade. The primary activity in Adams County is manufacturing
but Clermont County has more manufacturing.
Table III-D-148
COUNTY BUSINESS PATTERNS, 1973
Total Population
In CJBP
Agriculture
Mining
Construction
Manufacturing
Transportation
Trade
Finance
Services
Cl ermont
95,725
10,029
43
98
1,181
2,274
731
3,312
527
1,696
Brown
26,635
3,026
17
—
138
643
162
1,105
336
582
Adams
18,957
2,216
—
—
63
914
282
560
108
198
The manufacturing industries in Clermont County produce: 1) machinery;
2) printing or publishing; 3) paper products; and 4) textiles. Those in
Adams County are in: 1) machinery; 2) fabricated metals; and 3) apparel
or textiles. Brown County has only one factory employing over 100 and
it makes leather products.
The unusually large percentage of the jobs in construction in
Clermont County should be noted. This characteristic does not show up
in the 1970 labor force figures and suggests the presence of some large
construction project. This county should also be noted for the relatively
high percentage of working wives.
III-D-227
-------
Farming in these counties is not a profitable economic activity.
This suggestion is supported by the large number of part time and other
small farms. The price of farm land is not low but it varies from west
to east, the land in Clermont being more valuable, although not more
productive. The important factor here is probably competition for other
uses of the land in a rapidly urbanizing county.
Table III-D-149
0-2 FARMING STATISTICS
Clermont
Brown
Adams
Changes 1964-9
Farms
Acreage
Average
Land value
Return per acre
Class I-V Farms
Number
Avg. acres
Avg. return
Other Farms
Number
Avg. acres
Avg. return per acre
% Return from:
Crops
Da i ry
Livestock
Poultry
-5.1
-1.0
442
46
645
160
$ 10,059
963
51
$ 1,033
54
16
25
5
4.7
5.0
302
50
1,218
162
$ 9,724
1,034
54
$ 1,217
46
20
32
2
4.9
6.7
193
36
882
206
$ 9,637
1,088
82
$ 1,113
36
28
35
1
The emphasis on crops in Clermont is due, in part, to a large number of
tobacco farms (84) in this county.
8.2.8 INCOME
Income levels range from relatively high in Clermont County to
relatively low in Adams County. This pattern has persisted through
1974 but the differences between Clermont and the other two counties
are more marked.
III-D-228
-------
Table III-D-150
0-2 INCOME
Clermont Brown Adams
1969
Median Family $10,203 $7,674 $5,563
Median farm family 9,228 7,304 5,142
Per capita 3,125 2,673 2,358
1973
Per capita 4,137 3,433 2,991
1974
Family EBI 14,603 8,190 6,407
8.2.9 IMPACT ASSESSMENT
Clermont, Brown and Adams Counties in Southern Ohio are clearly
not boomtown candidates, though it appears Adams County has recently
experienced a modest boom due to power plant construction. However,
it has not yielded great economic returns as yet. This may be due
to the relative elderliness of the population since older people tend
not to benefit greatly from plant construction. Moreover, the rurality
of the county means the economic infrastructure to create additional
benefits was probably weak. The recreational facilities and the
rurality and age of the populace suggest the dominant orientations are
aesthetic and primordial belongingness. These orientations militate
against favorability toward future power plant development.
Clermont county, the richest, most diversified, and urban of these
three, has already experienced power plant construction and probably
would welcome more due to its instrumental orientation and strong
economic infrastructure.
Brown County seems to have a strong primordial belongingness sub-
orientation, given its rurality and older population. Impact of a
power plant would probably be minimal though we would expect consi-
derable opposition. On the other hand, Brown may wish to imitate its
Clermont neighbor and become more instrumental in orientation and
welcome power plant develppment.
III-D'-229
-------
8.3 FRANKLIN (833,249), PICKAWAY (40,071), ROSS (61,211),
PIKE (19,114) AND SCIOTO (76,951) COUNTIES
Five counties extending in a line from central Ohio to the Ohio
River are slated for power development by A.D. 2000. At present
there are no power plants in Pickaway, Pike or Scioto Counties. Ross
County has a small 67 megawatt plant and in Franklin there are four
small fossil-fueled plants with a total generating capacity of 495
megawatts. With one addition and several removals, the total for
Franklin County will be 468.5 in 1985.
Under the high-energy scenarios all counties will be affected.
Under low-energy Scenario III, only Franklin and Ross Counties will
be affected.
Scenario I proposes two-unit (2,000 megawatt) coal-fired plants
for both Franklin and Pickaway Counties, one-unit nuclear plants for
Ross, Pike and Scioto Counties and an additional three-unit (3,000
megawatt) plant for Ross County.
Under Scenario II, Franklin would have a two-unit (2,000 megawatt)
coal-fired plant. Pickaway would have a one-unit (1,000) coal-fired
plant. Ross would have two 2,000 megawatt plants, one coal and one
nuclear fueled. Pike and Scioto would each have a single-unit
(1,000 megawatt) nuclear plant.
Under Scenario III, Franklin and Ross Counties would each have
a single-unit (600 megawatt) coal-fired plant.
The Scioto River runs south through these counties to the Ohio
River. Columbus (539,637) the state capital, is in Franklin County,
the northernmost one of the group. This almost completely urban
county also contains eight other communities with over 10,000
residents and numerous smaller communities. This Central Ohio City
is the nucleus of a highway network extending to all the other major
population concentrations.
U.S. 23 follows the Scioto River and connects the other counties
in this group with Columbus. The major towns are located on this
highway. Halfway to the River is Chillicothe (24,842) in Ross County,
and in Scioto County on the Ohio River is Portsmouth (27,633). Be-
tween these larger population centers are the towns of Circleville
(11,689) in Pickaway County, Waverly (4858) in Pike County and Lucas-
vine in Scioto County, otherwise, these counties contain only
communities with less than 2,000 residents.
8.3.1 LAND USE
The proportions of land in farms and in forest vary considerably.
One factor affecting these land uses is the stretch of national forest
covering substantial portions of Pike and Scioto Counties. Ross
County contains several large state parks as well as part of the
national forest in its southeast corner.
III-D-230
-------
Table III-D-151
0-3 LAND USE
% Forest % Farmland
Value 1973
Mineral Production
Franklin
Pickaway
Ross
Pike
Scioto
5.0
4.4
38.7
59.7
66.7
46.8
96.7
65.2
44.5
29.7
$12,534,000
W
W
1,045,000
1,425,000
These counties are outside the coal-producing region but all have
some quarrying of sand, gravel, stone and clays.
As indicated above, the southern three counties are on the edge
of Appalachian Ohio and parts are covered by national forest, state
parks and forests. In addition, the "Mound City National Monument"
is close to Chillicothe in Ross County. These and nearby counties
also have a number of parks, memorials and tourist attractions.
Total recreational acreages in all of these counties are large and, in
Franklin and Scioto Counties, the proportion in private hands is sub-
stantial .
Table III-D-152
0-3 RECREATIONAL ACREAGE
Total
Public
Private
Franklin
Pickaway
Ross
Pike
Scioto
24,440
8,788
28,939
13,374
74,528
17,173
7,892
28,091
11,133
62,885
7,267
896
848
2,241
11,518
8.3.2 RESIDENCE
There is a difference in residential stability between the two
northern and the three southern counties. The southern counties have
higher levels of stability as measured by 1965 residence.
Table III-D-153
0-3 RESIDENTIAL STABILITY
Franklin Pickaway Ross Pike Scioto
% Residing in:
Birth state
Same State, 1
Same County,
965
1965
68
83
74
.0
.1
.4
76
87
73
.2
.3
.4
81.
91.
83.
1
7
6
74.
92.
80.
2
9
2
74.
91.
85.
7
9
7
III-D-231
-------
The above figures are also affected by migration. A net migration
represents only the balance of residential change, not magnitude of
change. Examination of 1965 residence is an attempt to assess magnitude.
In this case these three southern counties had moderate levels of out-
migration during the sixties high enough to more than counterbalance any
growth through natural increase. Nevertheless fifteen to twenty per-
cent of the population lived in another county in 1965 and approximately
eight percent lived in another state. Some people are moving into these
counties. It is tempting to speculate on whether these 1965 residence
figures represent a base level of residential change within a static
population in this society. That is, the lower levels of residential
stability in Franklin and Pickaway counties may simply represent the
fact that, in balance they had more in-migrants than out-migrants in
the sixties.
Table III-D-154
0-3 POPULATION SHIFTS
Franklin Pickaway Ross Pike Scioto
1960-1970:
Population
Farm sector
Migration
1970-74:
Population
Migration
22.0
-37.2
6.8
3.1
-1.0
11.8
-34.2
.6
-.9
5.8
-
-43.2
-10.8
-0.8
-3.5
-1.4
-49.0
-11.6
6.7
4.4
-8.6
-46.5
-15.8
2.4
0.5
As usual, disproportionate numbers of those who change residence come
from farm families.
By the early 1970's Ross was the only county which continued to
lose population largely through out-migration. Franklin County had
stabilized. There were a few more people leaving the county than
moving to Franklin County but the trend reversal was not dramatic.
Pickaway County seems to be the focus of new growth and in-migration.
In general, the farm sector of the population in these counties
is small, ranging from one to eleven percent. Except for metropolitan
Franklin County which is almost exclusively urban, all counties have
substantial segments of both urban and non-farm populations.
Table III-D-155
0-3 POPULATION DISTRIBUTION
Density
% Urban
% Rural
% Rural
, per sq. mi .
non-farm
farm
Franklin
1549
96
3
1
Pickaway Ross
80
29
60
11
89
41
52
7
Pike
43
25
66
9
Scioto
127
50
46
4
III-D-232
-------
8.3.3 AGE STRUCTURE
Median ages vary but in general are in the middle range for the
ORBES region:
Franklin 25.8
Pickaway 27.0
Ross 30.0
Pike 27.9
Scioto 31.1
Examination of age profiles shows two basic patterns. Both Franklin
and Pickaway have almost perfect age pyramids with gradual decrease
in size of age cohorts from childhood through old age. For both there
is a period of stability in cohort sizes from ages 30 through 50. The
three southern counties show a marked decrease in size of age cohorts
after the teens. In Pike County the sizes of the adult cohorts are
roughly equal until age 60 when attrition due to age sets in. Ross
and Scioto exhibit, to a slight degree, the pattern where middle-aged
cohorts are larger than young adult cohorts.
In general the pattern in the two northern counties is for the
young adult and early middle aged segments of the population to pre-
dominate over the older middle-aged and elderly portions of the popu-
lation. In the other counties, the young adult population is relatively
less important.
An additional point should be made about Franklin County. Probably
because of the presence of the Ohio State University, the 20 to 24 age
group is the largest single cohort.
8.3.4 MARITAL STRUCTURE
Franklin, an urban county with a relatively low median age, has an
unusually large proportion of divorced women and thus, families with a
female head. Consequently there is a low proportion of intact families.
Families with children under 18 form a larger than average part of the
population.
Pickaway County appears to have more of the suburban character-
istics of relatively high percentages of intact families and families
with children under 18. Pickaway also has relatively large numbers of
single women.
Ross County also has relatively high percentages of families with
children under 18 but relatively few unattached women.
Scioto County apparently attracts divorced women and there is a
correspondingly high percentage of families with a female head, and
low percentage of intact families. This county has an unusually low
ratio of men to women but of the men in residence, relatively high
percentages are married.
III-D-233
-------
Pike County presents an anomaly. There are above average numbers
of widowers and below average numbers of widows in this county. This
is consistent with the below average numbers of intact families but it
is difficult to envision a situation which would promote this con-
figuration. Perhaps it is a retirement community.
8.3.5 EDUCATION
The presence of the Ohio State University in Columbus is clearly
evident in the educational levels for Franklin County. Over 60% of
the adults have completed high school and almost 15% have completed
college.
Table III-D-156
0-3 EDUCATIONAL LEVELS
% Without high % Finished College
school diploma college Population
Franklin 38.9 14.5 49,754
Pickaway 47.4 5.9 500
Ross 55.2 5.8 593
Pike 61.7 6.7 89
Scioto 60.0 4.6 711
Levels of educational attainment are clearly lower in the three
southern counties when measured by median years completed and by
the percentage of high school graduates. However, the counties south
of Franklin are all comparable in the percentages of their populations
which have received higher education. In general, these counties are
in the middle range for the ORBES region.
8.3.6 HOUSING
Franklin and Pickaway Counties exhibited the greatest growth in
numbers of households and housing units, the most building activity,
the highest rents and house values and the lowest percentages of
homes which lack some plumbing.
Ross, perhaps due to the presence of Chillicothe, was in some
respects intermediate between the northern and southern counties. The
number of housing units increased by a modest proportion and the mode-
rate building rate was consistent. House values, rents and relative
numbers of houses lacking some plumbing were intermediate as well.
Pike exhibited the most typically rural traits, a low level of
building activity, lower house values, and a much higher percentage of
houses which lack some plumbing. Surprisingly, in this county the in-
creases in households and housing units were inconsistent. Although
there are substantially more households, housing units have increased
very slightly. This occurred in conjunction with a small population
loss but the significance of this change is unexplained.
III-D:234
-------
Table III-D-157
0-3 HOUSING, 1970
Frankli n Pickaway Ross Pike Scioto
Changes 1960-70
Households 29.2 20.2 8.6 10.4 -1.2
Housing units 27.0 19.5 9.7 1.3 -1.2
Median
House value $18,735 $15,425 $13,333 $9,147 $9,906
Rent 115 88 84 77 71
% of units
in one-unit structures 64.8 80.1 84.5 89.8 85.5
built since '60 31.6 27.2 18.4 12.4 12.6
lack plumbing 2.0 9.6 13.6 29.2 13.7
home owners 58.1 67.4 66.6 69.9 71.4
Scioto County lost a substantial proportion of its population
during the sixties and this is reflected in the losses in households
and housing units, the low level of building activity, low house
values and rents. Perhaps the percentage of housing units which
lack plumbing is lower than in Pike County, in part, because house-
holds may be in a position to refuse inadequate housing if there is
little housing demand.
8.3.7 ECONOMIC ACTIVITIES
The primary economic activity in Pickway and Pike Counties is
manufacturing although these are the counties with the smallest amount
of manufacturing. The others have more balanced mixes of job categories
listed in County Business Patterns.
Table III-D-158
0-3 COUNTY BUSINESS PATTERNS, 1973
Tot. Population
In CBP
Agriculture
Mining
Construction
Manufacturing
Transportation
Trade
Finance
Services
Franklin
833,249
310,629
716
571
21,747
80,973
19,904
90,508
29,762
65,860
Pickaway
40,071
7,402
33
69
387
3,993
347
1,724
272
571
Ross
61,211
11,800
—
58
626
4,497
635
3,707
462
1,778
Pike
19,114
3,236
—
—
128
1,833
75
750
91
318
Scioto
76,951
15,755
—
46
749
5,739
811
4,688
746
2,928
The large number of jobs in the trade and services category in
Franklin County are especially notable. This is also the only county
with net in-commuting for work.
III-D-235
-------
Obviously, with the magnitude of manufacturing activity in Franklin
County, it would be meaningless to list the types of manufacturing. It
is highly diversified, only two of the standard industry groups, tobacco
and coal or petroleum products, not having at least one plant which em-
ploys over 100 persons. There are eighty-one plants employing 100 to 249
employees and fifty-three plants employing over 249 as well as over eight
hundred smaller manufacturing plants.
Manufacturing in the other counties tends to have one major and
several minor industries. Pickaway County's major industry, rubber and
plastics, employed 1,473 in 1973. Other industries are: 1) food;
2) paper products; 3) chemicals; 4) stone, clay and glass products;
4) fabricated metal; 5) electrical equipment. All of these industries
employ at least 100 persons.
Pike County industries are in: 1) chemicals; 2) lumber and wood
products; and 3) fabricated metal.
The industries of Ross County are: 1) paper products; 2) leather
products; 3) fabricated metal; and 4) stone, clay and glass products.
Scioto County has industries producing: 1) primary metals and em-
ploying 2708; 2) food and employing 454; 3) stone, clay and glass pro-
ducts and employing 369; 4) textile mill products; 5) printing and
publishing; 6) chemicals; 7) leather products.
Examination of the labor force composition adds a few details to
this picture. Franklin County has a very high percentage of women in
the work force, many of them working wives. This county also has es-
pecially high percentages of the labor force working in professions,
managerial positions or in the federal civil service. Ross County
also has an unusually high percentage of the work force in federal
civilian employment.
Farming is moderately profitable in the two northern counties and
becomes less profitable to the south, both per acre and per farm. Also,
relatively more farming is done in the northern counties, judging from
the numbers of farms, in spite of high land values. The relative em-
phasis on crops in Franklin County distinguishes the farming in this
county. We surmise that this reflects an emphasis on truck farming
around the city, especially since the-average size of the farm is
smaller than in the other counties. There are sixteen vegetable or
fruit farms but 289 cash grain farms in the Class I-V categories. With-
out knowing the size of these operations, it is impossible to say whether
these few farms (admittedly more than any of the other counties) had an
important effect on these figures.
Only Pickaway has shown any increase in farm land or acreage in the
late sixties. Diversion of farm land to other uses was the pattern in
these counties, especially in the south where farming was least profit-
able. Of course it is possible that the land is being incorporated into
the National Forest rather than being developed for other uses.
III-D-236
-------
Table III-D-159
0-3 FARMING - 1969
Franklin Pickaway Ross
Changes 1964-9
Farms
Acreage
Average
Land value
Ret. per acre
Class I-V Farms
Number
Avg. acres
Avg. ret.
Other Farms
Number
Avg. acres
Avg. return
% Return from:
Crops
Dairy
Livestock
Poultry
-11.0
- 8.9
951
88
607
230
$21,690
355
o 60
2,738
55
11
32
2
8.0
4.9
410
78
925
313
$25,977
292
76
970
36
6
55
4
-10.2
- 4.6
274
49
716
335
$18,549
481
97
1,287
29
7
61
3
Pike
-21.2
- 5.8
167
34
269
308
$14,707
339
129
987
21
14
41
21
Scioto
-25.0
-13.2
220
46
313
223
$15,445
471
98
909
31
19
28
21
8.3.8 INCOME
Income levels range from high in Franklin to below average in Pike
County. This same pattern has persisted through 1974.
Table III-D-160
INCOME LEVELS
Franklin Pickaway Ross Pike Scioto
1969:
Median family
Med. farm family
Per capita
1973:
Per capita
1974:
Family EBI
$10,579
10,760
3,758
5,031
13,567
$ 8,705
10,063
3,023
4,248
11,519
$ 8,617
8,149
2,045
3,866
10,581
$6,546
5,583
2,337
3,185
7,583
$7,544
7,465
2,793
3,540
9,161
111-0-217
-------
8.3.9. IMPACT ASSESSMENT
Franklin, Pickaway, Ross, Pike and Scioto Counties present a
complex picture of environmental orientations. Franklin and Pickaway,
being urban, are likely to be instrumental in orientation, though the
latter county, being a suburban county, has a strong prestige sub-orien-
tation. Generally, there should be little impact from or reaction to
power plant siting due to a commuting labor force. Farmers, however, are
likely to be opposed because the plant would likely absorb some profitable
farmland. Some suburbanites may also be opposed.
Ross, Pike and Scioto Counties, although fairly distant from
major urban centers, are on a major four-lane highway which should miti-
gate any major boomtown effects. However, it seems likely that during the
construction phase, much of the labor force would be work week residents
of local communities, except for Ross County. This means a strain on
local temporary housing. The communities in these counties are fairly
diversified but Pike County, being the poorest and least diversified,
would be most hard pressed to cope with development. If a commuting
laboring force from Portsmouth and neighboring Ashland is sufficient to
meet construction phase demands, then Scioto County, being fairly
economically diversified, should be able to cope with its "boomlet."
All these counties have substantial symbolic orientations due to the
presence of forests, recreational areas and Indian sites. The rurality
and elderliness of the population also suggests a strong primordial
belongingness sub-orientation as well. Opposition to plants in these
counties, thus, is likely to be intense.
III-D-238
-------
8.4 LAWRENCE (56,868), GALLIA (25,239), MEIGS (19,799), ATHENS
(54,889), WASHINGTON (57,160), MONROE (15,739), BELMONT
(80,917) AND JEFFERSON (96,196), COUNTIES
Appalachian Ohio is scheduled for intensive power related develop-
ments. At present three of the counties have generating capacity in ex-
cess of 1,000 megawatts and by 1985 four of the counties will have
attained this level. All plants are fossil-fueled.
Table III-D-161
0-4 PRESENT GENERATING CAPACITY
(megawatts)
1975 Planned Units 1985
Lawrence
Gall i a
Meigs
Athens
Washington
Monroe
Belmont
Jefferson
14
3,725
25
290
1,798
-
552
4,816
_
-
-
750*
-
-
-
1,230**
14
3,725
25
1,040
1,798
-
550
6,046
* = No. of new units
This area will have further development under all scenarios. For
simplicity, developments under the various scenarios are presented in
table form. Only Jefferson County will receive no new units after 1985
but by that time it will already have a generating capacity of over
6,000 megawatts.
All of these border counties are across the Ohio River from West
Virginia and except for Steubenville in Jefferson County, the West
Virginia cities along the Ohio provide the closest urbanized areas for
the residents of these counties. Huntington is directly south of
Lawrence County, as is Ashland, Kentucky. Parkersburg is across the
river from Washington County. Wheeling is across from Belmont County
and Weirton is part of the same urban area as is Steubenville.
The nearest Ohio cities are Portsmouth, in Scioto County, and
Zanesville (33,045), seventy-five miles from the river. The only inter-
state highways serving this region are 1-70 which crosses Belmont County
going from Columbus to Wheeling; and 1-77 which runs south from the
Cleveland Area across Washington County and into West Virginia. Gallia,
Meigs and Monroe Counties each have only one town with over 1,000
residents:
III-D-239
-------
Gallia - Gallipolls (7,490)
Meigs - Middleport (2,784)
Monroe - Woodsfield (3,239)
The first two are on the river. All the other counties have at least
four communities with over 1,000 residents, one of them with over 15,000
residents. Except for Athens County, most major communities are along
the river. The population in Athens County is in the western half of the
County around the city of Athens. Highways tend to run from the river
toward central parts of the state. Only minor routes follow the river.
Residents of this area are fortunate in the ready availability of
outdoor recreational facilities. Various sections of the Wayne National
Forest parallel the river in the Appalachian Mountains and cover parts
of these and adjacent counties. Within these forested areas are numerous
parks and recreation areas plus several lakes.
Table III-D-162
0-4 GENERATING CAPACITY IN A.D.
(Megawatts)
2000
Scenario I Scenario II Scenario III Scenario IV
Lawrence
Gall i a
Meigs
Athens
Washington
Monroe
Belmont
C-3,014***
N-1,000*
C-6,725***
N-l ,000*
C-3,025***
N-1,000*
C-4,040***
C-4,798***
N-1,000*
C
N-1,000*
C-550
N-1,000*
C-1,014*
N-2,000**
C-4,725*
N-4,000****
C-2,025**
N-4,000****
C-3,040**
C-3,798**
N-l ,000*
N-4,000****
C-550
N-4,000****
C-14
C-3,725
C-625*
C-2,040*
C-1,798
*
***
C-550
N —
C-14
N-1,000*
C-3,725
N-1,000*
C-25
N-1,000*
C-1,040
C-1,798
N-1,000
N-l ,000*
C-550
N-1,000*
Jefferson
C-6,046
C-6,046
C-6,046
C-6,046
* = no. of new units
8.4.1 LAND USE
Large stretches of Wayne National Forest cover parts of these counties,
partially accounting for the relatively low percentages of land devoted to
farming, and the relatively large expanse of recreational land.
III-D-240
-------
Table III-D-163
0-4 LAND USE
Forest
% Farm Land Recreational Acreage
Lawrence
Gallia
Meigs
Athens
Washington
Monroe
Belmont
Jefferson
71.4
52.8
60.3
67.5
61.2
63.0
46.3
56.4
31.3
53.5
42.9
35.7
42.4
46.6
43.7
28.9
52,054
6,799
7,122
31,094
18,776
9,262
10,863
19,883
These counties are all underlain by coal bearing rock and in all
but Washington County, coal was mined in 1974. The value of the mineral
production, when disclosed, the tonnage of coal produced and the most
important minerals mined are presented in Table IV.
Table III-D-164
0-4 MINERAL PRODUCTION
Min. Prod. Coal Prod.
1973 (dollars) 1974 (tons)
Mineral in order
of importance
Lawrence
Gallia
Meigs
Athens
Washington
Monroe
Belmont
W
W
5,294,000
987,000
782,000
W
W
92,000
110,000
784,000
37,000
—
824,000
15,905,000
Cement, clays, sand &
gravel, stone, coal
Stone, sand & gravel,
coal
Coal , sand & gravel ,
salt
Stone, sand & gravel
Sand & gravel , stone
Coal , stone, sand &
gravel
Coal , stone, sand &
gravel
Jefferson
34,758,000 5,132,000
Coal, clays
One implication of this coal mining information is that the control of
mining must be very concentrated in Belmont County. The large amount of
coal produced and the fact that value is supressed supports this con-
tention. The same situation, though on a much smaller scale, appears to
be true in Monroe County.
III-D-241
-------
8.4.2 RESIDENCE
5
Athens County shows the most dynamic residence pattern, possibly
due to the presence of Ohio University. This county grew substantially
in the sixties, in part from in-migration, and had a high level of resi-
dential mobility with almost 40% of the population having lives in
another county in 1965. By the middle seventies this situation had
changed and the county was losing population and experiencing out-
migration.
Table III-D-165
0-4 RESIDENTIAL STABILITY
Lawrence
Gallia
Meigs
Athens
Washington
Monroe
Belmont
Jefferson
% In birth
State
66.5
70.6
69.3
73.5
65.9
77.9
76.6
76.1
% In same
County '65
85.3
82.2
84.3
62.5
80.6
84.5
88.6
88.1
% In same
State '65
87.8
91.1
91.6
82.5
86.4
92.4
92.5
91.4
Table III-D-166
0-4 POPULATION SHIFTS
1960-1970
Pop. Migration
1970-1974
Pop. Migration
Lawrence
Gal lia
Meigs
Athens
Washington
Monroe
Belmont
Jefferson
2.6
-3.4
-10.7
18.6
10.6
3.1
-3.5
-3.0
-7.8
-9.0
-13.2
8.6
2.0
-4.4
-6.7
-9.4
6.4
9.0
8.4
-4.6
3.5f
0.2
2.0
—
3.3
6.7
7.3
-6.6
1.1
-1.6
1.3
-1.5
The other counties exhibited higher levels of residential stability,
although unusually low percentages in Lawrence and Washington counties
were natives of Ohio. During the sixties, half of the counties grew and
half lost population although all but Washington sustained at least a
small loss through out-migration. By the middle seventies all the popu-
lations had stabilized or begun to grow and only Monroe County was still
experiencing out-migration.
III-D-242
-------
The distribution of the population among the urban, rural non-farm
and rural farm sectors reflects the distribution of communities and
level of urbanization discussed earlier. Meigs, Gallia and Monroe
appear to be the most rural counties.
Table III-D-167
0-4 DISTRIBUTION OF POPULATION
Density % Urban % Rural Non-farm % Rural Farm
Lawrence
Gallia
Meigs
Athens
Washington
Monroe
Belmont
Jefferson
125
54
45
111
89
35
152
234
51
30
28
51
42
21
51
58
42
56
60
45
52
58
41
38
7
14
12
4
7
21
8
4
8.4.3 AGE STRUCTURE
Median ages are, with the exception of Athens County, within a
fairly small range, 28 to 34:
Lawrence - 28.7
Gallia - 30.5
Meigs - 32.3
Athens - 22.0
Washington- 28.1
Monroe - 29.6
Belmont - 34.0
Jefferson - 31.2
The low median age in Athens County is largely a consequence of ex-
tremely large cohorts for ages 20 through 29. As mentioned earlier,
there is a large college population in this county. Profiles for
Meigs, Belmont and Jefferson Counties are similar in that middle-aged
cohorts are substantially larger than young adult cohorts. In the
other counties, adult cohorts are roughly equal in size until they
begin to decline due to age.
8.4.4 MARITAL STRUCTURE
The presence of a large college population (14,033) in Athens
County so affects the demographic profile of marital status that it is
impossible to say much about the non-student population of this county.
Gallia County, although it does not have a large college population,
exhibits some of the same traits in a less marked way. This county also
has relatively high percentages of single people and relatively low per-
centages of married people.
III-D-243
-------
High or relatively high percentages of men in all the other counties
are married although only moderate percentages of the women are. The
moderate median ages argue against any excess in numbers of the widowed
except in Monroe County (relatively high percentage of widowers). Numbers
of divorced are also low.
These are counties with at least moderate percentages of intact
families and families with children under 18. The one exception to the
latter characteristic is Belmont County which has an older population,
probably many of whom have finished raising their families.
8.4.5 EDUCATION
Educational levels in all but Athens and Washington Counties are
somewhat lower than in the northern ORBES region counties. Athens
county is predictably atypical. Over half of the adult population has
finished high school and almost 15% have finished college. The effects
of a university community on these percentages is inflationary. It is
likely that the non-university residents are similar in composition to
the other counties in Appalachian Ohio.
Three other counties, Washington, Belmont and Jefferson have modest
college populations but only in Washington county does the number appear
to have been sufficient to affect percentages noticeably. This is most
likely due to a smaller total population.
Generally, these counties have large proportions of adults who have
not finished high school and less than 5% have attended college. It is
probable that those children who go away to college tend to settle else-
where.
Table III-D-168
0-4 EDUCATIONAL LEVELS
Lawrence
Gallia
Meigs
Athens
Washington
Monroe
Belmont
Jefferson
% Without high-
school diploma
56.3
62.0
60.3
42.2
54.8
55.0
55.4
54.1
% Finished
College
4.2
5.0
2.9
14.8
7.8
4.0
4.2
' 4.8
College
Population
602
718
133
14,033
1,981
72
1,234
2,249
III-D-24'4
-------
8.4.6 HOUSING
One county, Meigs, showed a loss in numbers of households and housing
units during the sixties. This is consistent with the high population
losses during the same period. Housing values were also lowest in this
county. Although the other counties all gained in numbers of households
and housing units, the growth was most rapid in Athens and Washington
Counties. These are also the counties that grew most during the period.
Rents and housing values varied from moderate to low but are fairly uni-
form throughout the area with the exception of Meigs County.
Table III-D-169
0-4 HOUSING VALUES AND CHANGES
Lawrence
Gall i a
Meigs
Athens
Washington
Monroe
Belmont
Jefferson
Median
Value
$12,790
12,384
7,698
11,633
15,302
10,823
11,366
14,420
Median
Rent
$79
77
70
107
89
70
75
89
Change,
Households
10.8
7.1
-2.2
21.4
14.9
6.1
1.9
3.6
1960-1970
Housing Units
12.8
10.0
-1.0
23.7
15.3
4.9
1.6
2.7
Building rates varied as well with the greatest activity occurring
in those counties which were growing most rapidly. Surprisingly, Athens
and Washington Counties did not have noticeably fewer housing units which
lack some plumbing. Athens county did have more multi-unit structures.
Table III-D-170
0-4 HOUSING CHARACTERISTICS, 1970
Lawrence
Gallia
Meigs
Athens
Washington
Monroe
Belmont
Jefferson
"/One-unit
Structures
86.0
83.4
86.6
72.0
82.1
88.6
78.0
79.0
%Built since
1960
23.8
22.3
13.8
26.2
23.2
16.6
12.9
16.8
%Home
Owners
72.2
73.4
75.4
73.7
74.5
80.7
73.7
72.6
% Lack some
Plumbing
15.6
21.6
24.3
14.9
10.4
21.2
10.0
6.2
III-D-245
-------
8.4.7 ECONOMIC ACTIVITIES
Non-agricultural economic activity in these counties is balanced
among the various categories listed in the County Business Patterns
and the number of jobs listed for each county varies over a fairly wide
range as well.
The only one of the four southern Appalachian counties in which
manufacturing is of much significance is Lawrence County. These jobs
are primarily in: 1) chemicals; 2) primary metals; and 3) fabricated
metals.
Gallia has more jobs in trade and in construction than in manu-
facturing. The manufacturing in Athens County is in: 1) machinery;
2) leather products; and 3) printing and publishing. The industrial
activity in Gallia County is in: 1) primary metals and 2) food.
Meigs County only has a few small industries employing less than
100 people each.
The sizeable number of jobs in Washington County are mainly in trade
and the services, and there are more jobs in construction than in the two
populous northern counties.
Definite statements cannot be made about the jobs in Monroe County
but by comparing sources some inferences can be made. The number of jobs
unaccounted for is over 3,000. Since few of these are likely to be in
agriculture, we must assume that they are in manufacturing. Examination
of the 1972 Census of Manufacturing. Table 9, shows that Monroe County
has fourteen plants employing between 1 and 19 people each. The maxi-
mum number this could account for is 266 people. There is, however, one
primary metals plant employing over 290 people (the largest category).
Since Monroe is also the only one of these counties with new in-commuting
and this county is smaller than the surrounding counties and apparently
has less to offer in economic opportunities, we suggest that the economy
of this county must be dominated by one very large primary metals plant
which must employ close to 3,000 people.
Belmont County has almost as many people involved in mining as in
manufacturing and trade. The large coal production in this county
probably provides for the bulk of these jobs. The manufacturing activity
in this county is in: 1) fabricated metals, employing 1,530; 2) stone,
clay and glass products, employing 577; 3) food, employing 369; 4) ap-
parel and textile products; 5) primary metals; 6) machinery; and
7) transportation equipment.
Jefferson County, the largest of the eight, also has a substantial
number of jobs in mining, coal for the most part. The manufacturing
industry in this county is not diversified, 7,915 of the jobs being in
the primary metals industry. The other industries with plants employing
over 100 are: 1) stone, clay and glass products, employing 294;
2') machinery, employing 210; 3) paper products; 4) fabricated metals;
and 5) printing and publishing.
III-D- 246
-------
I
o
f\5
Table III-D-171
0-4 COUNTY BUSINESS PATTERNS, 1973
Lawrence Gallia Meigs AthensWashington Monroe Belmont Jefferson
Total population
In CBP
Agriculture
Mining
Construction
Manufacturing
Transportation
Trade
Finance
Services
56,868
7,712
17
77
350
3,014
582
2,322
343
989
25,239
5,097
7
79
932
712
463
1,168
206
1,321
19,799
2,122
—
121
116
207
209
977
102
367
54,889
7,948
43
103
467
1,331
833
2,917
536
1,681
57,160
15,013
18
169
1,465
2,801
1.025
3,698
473
3,062
15,739
4,132
—
36
333
—
61
510
44
93
80,917
18,109
55
3,624
622
4,929
1,256
4,375
610
2,591
96,196
23,987
12
1,248
869
9,486
1,937
5,622
327
2,273
All of these counties are losing agricultural land which is being diverted to other uses.
The losses are just slightly less in the southern counties. Farming is only marginally profitable
and onlh provides a minority of the farmers in these counties with a potentially viable full-
time farming operation. The ratio of Class I-V farms to "other" farms is very low.
-------
I
o
rv>
-P>
00
Changes 1964-9
Farms
Acreage
Average
Land value
Ret. per acre
Class I-V Farms
Number
Avg. acres
Avg. Ret.
Other Farms
Number
Av§. acres
Avg. return
% Return from:
Crops
Dairy
Livestock
Poultry
Lawrence
-26.2
-10.7
$ 208
36
178
237
$15,829
524
94
$ 914
19
27
27
26
Table III-D-172
0-4 FARMING, 1969
Gallia Meigs Athens
-19.2
-11.8
171
31
396
214
10,016
818
93
1,167
21
35
40
3
-29.0
-18.8
155
33
254
234
14,049
508
118
851
18
43
22
17
-23.4
-16,6
149
25
218
237
11,032
458
139
1,155
8
46
31
15
Washington
-28.0
-19.4
179
32
444
201
11,078
752
113
912
21
30
43
4
Monroe
-27.4
-20.7
122
.25
309
218
9,348
596
115
892
9
50
29
10
Belmont
-31.3
-23.0
155
42
433
223
13,204
534
100
1,013
12
50
32
5
Jefferson
-36.8
-32.1
160
34
206
206
11,056
298
112
928
25
42
24
9
Dairy farming seems to be especially important in these counties and the second most
important type of operation is livestock raising. Since this is the Appalachian part of
Ohio, it is likely that the terrain does not encourage the growing of cash crops.
-------
8.4.8 INCOME
In 1969 income levels were moderate to relatively low in all but
Belmont and Jefferson Counties. By 1974, the family income in Washington
County was on a par with these two northern counties.
Table III-D-173
0-4 INCOME
Lawrence
Gallia
Meigs
Athens
Washington
Monroe
Belmont
Jefferson
1969
Med. Fam.
7,708
6,909
6,485
7,628
8,568
7,630
8,450
9,341
1969
Med. Farm Fam
6,792
4,952
7,661
6,190
6,980
6,223
7,519
8,429
1969
. Per Cap.
2,860
2,290
2,192
2,594
2,962
2,715
3,110
3,247
1973
Per Cap.
3,675
4,081
3,422
3,217
3,823
3,295
4,438
4,530
1974
Fam. EBI
9,210
8,596
7,750
9,207
10,651
9,938
10,116
11,257
8.4.9 IMPACT ASSESSMENT
Lawrence, Gallia, Meigs, Athens, Washington, Monroe, Belmont and
Jefferson counties in Appalachian Ohio differ widely in their environ-
mental oreintations. Jefferson and Belmont Counties, with their re-
liance on coal and related industries, high incomes, older and urban
populations have mixed orientations. The instrumental orientation is
dominant and possible the territorial one is present if coal is strip
mined, and there is a healthy prestige sub-orientation. Jefferson
County's previous experience with a large power plant, and it recre-
ational areas suggest that previous contact with instrumental and
territorial orientations and the presence of the aesthetic sub- •
orientation might work against ready acceptance of further development.
Belmont, on the other hand, appears ready and welcoming. Neither
county would experience strong boomtown effects for Wheeling and
Steubenville should be able to provide the needed labor force.
The profile of Washington County is similar to that of Jefferson
though we suggest that the aesthetic and prestige sub-orientations are
stronger there, and the people less amenable to power plant develop-
ment.
Lawrence County probably has the strongest aesthetic sub-
orientation of all. It is probably used by nearby Huntington and
Ashland residents as a major recreational area. Plant siting here
would conflict with the predominant sub-orientation, though no boom
would occur.
III-D-249-
-------
Gallia, Meigs and Monroe are the most rural counties and the first
two are boomtown candidates, being rather isolated and poorly served by
highways. Their lack of economic diversification bodes ill for coping
with power plant development. As with most rural counties, with older
populations, the sentimental orientation is predominant. Gallia
probably has already experienced a boom due to power plant construction
and may or may not be eager for more though its unusual population
structure may work for acceptance. Monroe county, however, appears
to need further economic diversification, and would presumably welcome
a plant. Meigs, the most rural, would probably be opposed to a power
plant, given the age structure of the population.
Athens County presents a very mixed picture, as counties housing
universities often do. The mining of coal and percentage urban suggest
instrumental and territorial orientations. The out-migration suggests
that it is possibly those with a primordial belongingness sub-orien-
tation that are leaving. The aesthetic sub-orientation is present too.
It is our prediction that reaction to the power plant would be mixed
and conflictful. The instrumental orientation will probably win out.
There is also a likelihood of a boom, given Athens' relative isolation,
however, the infrastructure seems diverse enough to handle it.
III-D-250
-------
8.5 MORGAN (12,375), MUSKINGUM (77,826)
AND COSHOCTON (33,486) COUNTIES
Three interior counties in eastern Ohio will have power related
development before the year 2000. Morgan has no power plants at present
and Muskingum has a small 295 megawatt coal-fired plant. Coshocton,
however, has a 2,094 megawatt coal-fired plant at Conesville in the
southern part of the county on the Muskingum River. By 1978 two more
coal-fired units (375 megawatts each) will be completed, bringing
the total capacity for this plant to 2,844 megawatts.
Coshocton will receive no new units but under the scenarios,
Morgan and Muskingum Counties will. Both high energy sceanrios posit
the building of four units (4,000 megawatts) in Morgan County and one
unit (1,000 megawatts) in Muskingum County. Under Scenario I, Morgan
would have three coal and one nuclear units. Under Scenario II
Morgan would have two coal and two nuclear units. Muskingham would
have a single nuclear unit under either scenario. Scenario III
proposes a single unit coal-fired plant for Morgan (600 megawatts).
Scenario IV suggests a sjngle unit nuclear unit for Muskingum
County (1,000 megawatts).
The Muskingum River runs from Coshocton County through both
Muskingum and Morgan Counties before emptying into the Ohio River.
This river also runs through Zanesville (33,045), the largest city in
the area. Any plant located near the river in these counties could
not be more than 35 miles from this Muskingum County city. In
addition State Highway 60 follows the river south of Zanesville.
1-70 runs through Zanesville going from Wheeling, West Virginia, to
Columbus, 54 miles west in the center of the state.
Morgan is a completely rural county with only two small communi-
ties with over 1,000 residents, Malta (1,017) and McConnelsville
(2,107). Muskingum, in addition to Zanesville, has four communities
with between 2,000 and 4,000 residents. Coshocton also has a size-
able town, Coshocton (13,185), and one small community, West La-
fayette (1,719).
8.5.1. LAND USE
Between 45 and 60 percent of the land of these counties is in
farm land and just over 40 percent is forested.
Table III-174
0-5 LAND USE
Morgan
Muskingum
Coshocton
% Farm Land
47.8
59.9
54.5
% Forest Recreational Acreage
43.7
41.1
41.3
50,417
22,077
10,385
III-D-251
-------
As can be seen, these counties also have sizeable portions of their
land devoted to recreational use. There are state parks in both
Morgan and Muskingum counties and a section of national forest is
just west and south of the county lines of Morgan County.
The most important mineral produced in three of these counties
is coal, the largest amount being in Muskingum County. Sand, gravel,
stone and clays are also quarried in all three counties.
Table III-D-175
0-5 MINERAL PRODUCTION
1973 Mineral 1974 Coal Production
Value Tons
Morgan
Muskingum
Coshocton
W
$47,812,000
W
531,000
4,471,000
1,893,000
8.5.2 RESIDENCE
All three counties experienced out-migration during the sixties
although the population in Coshocton County grew in spite of this
migration rate. In the early seventies trends reversed and in-
migration led to a small growth in the population.
Table III-D-176
0-5 POPULATION SHIFTS
Morgan Muskingum Coshocton
1960-70:
Population
Farm sector
Migration
1970-74:
Population
Migration
-2.9
-47.2
-7.2
8.2
6.4
-1.7
-43.3
-10.8
2.9
0.6
3.9
-26.1
-3.1
3.3
1.4
The composition of the populations as to residential stability
was similar in these counties. All were stable. The comparative
rurality of Morgan and Coshocton are evident from figures on density
and distribution among the different sectors of the population.
III-D-252
-------
Table III-D-177
0-5 POPULATION STABILITY AND DISTRIBUTION
Morgan Muskingum* Coschocton
% Residing in:
Birth State
Same county, 1965
Same state, "
Density per sq. mi.
% Urban
% Rural Non-Farm
% Rural Farm
87.7
82.3
93.8
29
0
82
18
86.5
85.5
92.6
120
47
48
5
85.0
86.1
93.7
60
41
45
14
8.5.3 AGE STRUCTURE
Median age is only slightly lower in more urbanized Muskingum
County. Muskingum and Coshocton have very similar profiles with
small young adult cohorts and the largest adult cohorts in the 40
through 50 age range. Morgan County is characterized by roughly
equal adult cohorts through age 55. After that decline is very
gradual so that this county has relatively more of the elderly
than the other two counties. Median ages are:
Morgan - 31.3
Muskingum - 28.8
Coshocton - 31.0
8.5.4 MARITAL STRUCTURE
Most men are married in these counties. There are few single
men. On the other hand the numbers of married women are not es-
pecially high, particularly in Coshocton County. This may be a con-
sequence of higher percentages of women in the population. This low
ratio of men to women is especially marked in Muskingum County.
Nevertheless there are also relatively few single women. High or
relatively high percentages of divorced women live in Muskingum and
Coshocton Counties, probably because of the urban areas. In spite
of this, Coshocton County still has relatively large numbers of in-
tact families and few with a female head.
Morgan County is characterized by relatively large numbers of
widowed men. Recalling the unusually large numbers of the elderly
in that population and the more rural character of this county, this
consequence might be anticipated although usually one would expect
an excess of widows as well.
III-D-253
-------
8.5.5 EDUCATION
Only one of these counties, Muskingum, has any substantial
college population (2,087). This factor may be reflected in the
slightly higher percentage of the adult population who have finished
college.
In general, these counties are characteristic of the northern
ORBES region, with educational levels being slightly lower in rural
Morgan County but no great variation among the three.
Table III-D-178
0-5 EDUCATIONAL LEVELS
Morgan Muskingum Co shoe ton
% Without high
school diploma
% Finished college
52.2
3.6
50.0
5.9
48.2
5.1
Median school levels are slightly over 12 years for Muskingum and
Coshocton-and slightly under 12 years for Morgan County.
8.5.6 HOUSING
These counties are not characterized by any of the extremes in
housing patterns. There has been a modest growth in new households
and housing-units since 1960 in spite of a small decline in popu-
lation in the two southern counties. From this we infer a break up
of households into smaller units. Building rates have been similarly
low in all three counties.
Degree of urbanization seems to correlate with house values and
percentages of units lacking plumbing and in one-unit structures.
The more rural character of Morgan County is clear.
Table III-D-179
0-5 HOUSING, 1970
Morgan Muskingum Coshocton
Cliange 1960-70:
Households 3.3 3.1 7.9
Housing Units 10.2 4.3 10.1
Percentage of Units:
In one-unit structures 83.6 80.5 83.9
Built since 1960 15.7 16.4 15.4
Occupied by owner 76.3 74.2 76.8
Lack some plubming 17.4 8.7 10.0
Median:
House value $10,948 $12,172 $12,195
Rent 72 76 84
III-D-254
-------
8.5.7 ECONOMIC ACTIVITIES
The primary economic activities in these counties is manufacturing
but they differ greatly in the amount of industry.
Table III-D-180
0-5 COUNTY BUSINESS PATTERNS, 1973
Total population
In CBP
Agriculture
Mining
Construction
Manufacturing
Transportation
Trade
Finance
Services
Morgan
12,375
2,084
123
51
1,043
121
416
72
253
Muskingum
77,826
22,255
119
386
748
9,141
1,603
5,778
797
3,665
Coshocton
33,486
10,549
1,144
309
5,254
658
1,682
296
1,155
*
Morgan county has only three industries employing over 100
persons: 1) furniture and fixtures; 2) fabricated metals; and
3) transportation equipment. The mining is mostly for coal.
Muskingum County has the greatest amount of manufacturing activity:
1) electrical equipment, employing 2,198; 2) stone, clay and glass
products, employing 2,167; 3) primary metals employing 1,393; 4)
printing and publishing; 5) chemicals; 6) fabricated metals; 7)
machinery; and 8) transporation. All of these industries employ over
100 persons. The mining in Muskingum County also is primarily of
coal. Zanesville probably accounts for the large numbers employed in
trade and services.
Coshocton has the largest mining industry, mainly coal, of any
of the three counties. The manufacturing activity is primarily in:
1) primary metals and 2) rubber and plastics; but there are also
industries in: 3) printing and publishing; 4) apparel and other
textiles; 5) fabricated metals; and 6) electrical equipment.
Examination of the work force composition adds only a little to
this picture. Muskingum, as expected in a county with a small city,
has an above average percentage of women in the work force. This
county also has an above average number of civilian employees of the
federal government.
Farming is only marginally profitable in these counties, being
especially poor in Morgan County. The losses in numbers of farms and
farm acreage mirror this level of productivity. Although there
appears to be some consolidation, farm land is also being diverted to
other uses.
III-D-255
-------
Changes 1964-9
Farms
Acreage
Average
Land value
Return per acre
Class I-V farms
Number
Avg. acres
Avg. return
Other farms
Number
Avg. acres
Avg. return
% Return from
Crops
Dairy
Livestock
Poultry
Table III-D-181
0-5 FARMING, 1969
Morgan Muskingum
-22.6
-18.1
$ 120
21
252
281
$9,062
462
125
$1,015
9
31
53
5
-23.5
- 9.7
$180
36
605
249
$12,432
686
111
$981
18
23
53
3
Coshocton
-13.5
- 4.3
$218
45
626
247
$14,527
545
111
$1 ,036
18
30
48
3
The comparison of numbers of Class I-V to other farms gives an in-
dication of the unprofitability of farming. Livestock raising and
dairy farming are clearly the most important types of farming ope-
ration in these counties.
• t
8.5.8 INCOME
Income levels are in the middle range for the ORBES region.
Also, farm families have distinctly lower incomes than other families
in the population. The pattern of variation among these counties
persists through 1974.
Table III-D-182
1969
Median Family
Median Farm Family
Per capita
1973
Per capita
1974
Median Family EBI
0-5 INCOME LEVELS
Morgan Muskingum
$7,171 $8,313
6,580 7,932
2,800 3,000
3,950
$8,544
4,100
$10,103
Coshocton
$8,343
6,907
3,308
4,691
$10,717
III-D-256
-------
8.5,9 IMPACT ASSESSMENT
Coshocton, Muskingum and Morgan counties in Ohio's interior would
react differently to power plant siting. The very rural and poor
Morgan County would be ill-equipped to deal with a likely boomtown
situation. Moreover, the predominant enviornmental orientation is pri-
mordial belongingness with the aesthetic sub-orientation, meaning there
would be considerable resistance to development.
Coshocton and Muskingum counties, being more urban and economically
diversified could cope with a boom, but that is unlikely given their
proximity to large urban areas. Being coal-producing counties as well,
the predominant orientation is probably instrumental. Farming appears
to be declining and not very profitable with a corresponding decline
in the sentimental orientation. We would expect these counties to be
receptive to power plant development and capable of benefiting from
it.
III-D-257
-------
8.6 MAHONING COUNTY (303,424)
Mahoning is the only county in the highly industrialized and
urbanized northeastern corner of Ohio which has been scheduled for
power related development. At present there are two small plants
with a total capacity of 76 megawatts. Under each of the first
three scenarios, coal-fired plants will be built in Mahoning County.
Under Scenario I it will be a three-unit (3,000 megawatts) plant,
under Scenario II a two-unit (2,000 megawatts) plant, and under
Scenario III a single uni&t (600) plant.
Youngstown (139,759) is located in Mahoning county as well as
Struthers (15,343), and Campbell (12,577), and two large unincorporated
places, Austintown (29,393) and Boardman (30,852), as well as seven
smaller communities. This urbanized county is directly connected by
major highways with the other large cities in this area, Cleveland
and Akron, as well as with Pennsylvania just east across the county
line. Suburbs of Youngstown extend north into Trumbull County so
the extent of the immediate urban environment is larger than the
population figures for this county would suggest.
8.6.1 LAND USE
As expected in this urban county, only a little over a third
(36.5%) of the land is farmed. Slightly over 21% is forested and
22,298 acres, mostly public, are devoted to recreational use, never-
theless.
Mahoning has a not insignificant amount of mining. The mineral
production, valued in 1973 at $9,377,000, consisted of the extraction
of stone, coal, clays, sand, gravel, and peat. In 1974, 482,000 short
tons of coal were mined.
8.6.2 RESIDENCE
This county has had net out-migration since 1960. (1960-70,
-6.1%; 1970-74, -2.2%). Population size has remained fairly constant,
however. The population also appears to be relatively stable. Over
86% of the population were residing in Mahoning County in 1965 and a
further 4% lived in another county in Ohio.
In spite of the urban nature of this densely settled (734 per
square mile) SMSA county, 2% of the population live on farms and a
further 14% live in the countryside or in rural (less than 2,500)
communities.
8.6.3 AGE STRUCTURE
Median age is 30.5, and the largest adult age cohorts are for
ages 40 through 55 with significantly fewer in the young adult co-
horts. The decrease between ages 19 and 20 is not as sharp as in
many impacted counties, however, there is another similarly sized
III-D-258
-------
decrease between 24 and 25. The interpretation offered is that this
intermediate step represents in large part the presence of a student
population at Youngstown University.
8.6.4 MARITAL STRUCTURE
Not unexpectedly for this urban county, the only characteristics
of the marital structure which are especially noticeable are the
relatively high percentage of single men and divorced women. Possibly,
men who do not wish to marry and divorced women gravitate to a city
where they can pursue a satisfying life style. The relatively low
percentages of intact families might be expected as a consequence of
high numbers of divorced women.
Relatively high percentages of men tend to marry in this as in
many counties in the ORBES region. However, the generally greater
tendency for men to remarry coupled with the lower percentage of males
and the larger proportion of single men in this population is con-
sistent with the relatively low percentage of married women.
In general, this county is characterized by higher than average
numbers of households not organized around a married couple.
8.6.5 EDUCATION
Mahoning County is characteristic of the northern ORBES region
in having a median school level in excess of 12 years. Just over
half of the adult population (51%) have completed high school but
only 7% have completed college. In a county of this size, the
college population of 9,962 and the attendant faculty and support
personnel have not noticeably inflated this figure.
8.6.6 HOUSING
Surprisingly, the percentages of home owners and single-unit
dwellings in Mahoning County is relatively high. Of course house
values ($15,939) and rents ($100) are relatively high as well. The
housing market appears to be reasonably stable in this county. The
number of households increased by 8% between 1960 and 1970 while the
number of units grew by 7%. The fact that the size of the population
has remained stable indicates the breaking up of households into
smaller units, possibly an accompaniment of a higher divorce rate
and more single individuals establishing their own households. The
building rate (16.5%) was sufficient to provide the needed new units
and a moderate level of replacement.
8.6.7 ECONOMIC ACTIVITIES
The primary non-agricultural activity in Mahoning County is
manufacturing but trade is a close second in importance.
III-D-259
-------
Table III-D-183
0-6 COUNTY BUSINESS PATTERNS, 1973
Total Population 303,424
In CBP 94,322
Agriculture 117
Mining 252
Construction 4,866
Manufacturing 37,764
Transportation 4,577
Trade 25,639
Finance 4,422
Services 16,528
Half of the manufacturing is in the primary metals industry (18,911
employees). There are several other important industries; 1) elec-
trical equipment, employing 2,366; 2) fabricated metals, employing
2,129; 3) machinery; and numerous other plants representing all
categories listed in the manufacturing census except for tobacco
products and textiles.
For that portion of the population who have potentially full-
time farms, farming is a moderately profitable economic activity.
Nevertheless, the number of farms and farm acreage have been de-
creasing.
Farms are relatively small and the type of operation varies.
Table III-D-184
0-6 FARMING, 1969
Changes 1964-9
Farms -17.3
Acreage - 8.0
Average
Land value $422
Return per acre 89
Class I-V farms
Number 412
Avg. acres 160
Avg. return $20,029
Other Farms
Number 474
Avg. acres 65
Avg. return $828
% Return from:
Crops 28
Dairy 34
Livestock 20
Poultry 19
III-D-260-
-------
8.6.8 INCOME
Income levels are high in this county and the difference between
farm families and the rest of the population is almost non-existent.
Table III-D-185
0-6 INCOME LEVEL
1969 Median Family $10,095
Median Farm Family 10,099
Per capita 3,640
1973 Per capita 4,795
1974 Median Family EBI 13,277
8.6.9 IMPACT ASSESSMENT
Mahoning County in Ohio seems strongly instrumental in orientation
and the effects of siting a power plant there minimal, given the highly
industrial/urban nature of the county. The only opposition to be ex-
pected is possibly from those landowners who have to give up their
land and do not wish to do so.
III-D-261
-------
9. SUMMARY
Inquiry thus far into the social aspects of power plant siting
has given us a singular and somewhat isolated picture of plausible
general impacts on a county-to-county basis. We have purposely skirted
the complex and vexing question of interactive effects of simulta-
eous planning, construction and operation of power plants in geograph-
ically proximate areas.
Our paradigm and hypotheses have provided guidelines for assessing
likely impacts in a case study situation as well, but they too are of
limited usefulness in assessing interactive effects.
The Bureau of Mines (high) and the Ford Tech-Fix (low) energy
scenarios represent differing levels of magnitude of interactive
effects ana make tne general remarks which follow in this summary
contingent on these varying degrees of magnitude. One generalization
about interactive effects is virtually a truism: the larger the number
of plants being sited in geographically proximate areas, the greater
the number of potential conflicts between environmental orientations.
Social fragmentation into opposition and proponent groups,
possible accompanying acrimony and interpersonal conflict among impacted
groups should pose a problem for planners if they are confronted with
this situation and if they wish to take ameliorative or preventive
steps to mitigate some the these negative impacts. Moreover, at the
more socio-structural level interactive effects are important, particu-
larly in the construction phase, for a large, specialized migrant labor
force with several years of future job security in plant construction
may decide to reside in geographically convenient communities that
seem able to provide some amenities as well. These quasi-permanent
residents may cause a real boom in their chosen community, even if
that county itself is not slated for development.
From a social scientists' point of view, these possible inter-
active effects are important in a strictly "social" as opposed to
"socio-economic" point of view for the basic patterns of human inter-
action in boom and even "boomlet" communities are fundamentally and
irreversibly changed and in many ways for the worse among the community's
original residents. Gold's ethnographic study of western boomtowns
sheds a great deal of light on social and cultural disruption due to
power plant development (1). Oldtimer residents may suddenly find
their basic values and traditional behaviors questioned by or interfered
with by the newcomers. Gold reports that local bars, for instance,
which previously were the locus of frequent interaction among oldtime
residents are often taken over by the newcomers, who differ funda-
mentally in lifestyle and values, and that oldtime residents quit
going there.. Often there is no other locus of interaction to take the
place of the bar, and consequently, familiar interactions no longer
occur as regularly nor in such cohesive groups.
III-D-263
-------
The loss of familiar social ties to the community is usually seen
as a negative impact for oldtime residents. This, coupled with forced
interaction in public places with the newcomers, tends to have an
anomic effect on the oldtimers. New residents, too, particularly
those in temporary housing communities, also face many social strains
in a boom situation. Women with children and nothing to do, rejection
by oldtimers, crowded housing and housing communities, the lack of a
supportive network of friends and families among the newcomers, all
these factors contribute to a social malaise among new residents as
well. These are some of the true social costs that can be visited
upon those impacted by power plant development.
We stress these matters because we feel altogether too little
attention has been paid to negative social costs in the literature on
impacts of developmental forces on communities. It indeed seems
possible that these kinds of impacts, if large enough and stressful
enough, may become life-threatening for some people.
We have suggested earlier those groups most likely to be negatively
effected in boomtown situations - the old, the poor, the ill-educated,
the unskilled, and those on fixed incomes - yet we have seen little
effort on the part of development industries and agencies to make
some systematic effort to ameliorate these negative effects.
The high energy scenarios, (though we consider them implausible,
at best) if enacted, would cause fundamental and serious changes in
the quality of life and future expectations for a very large number of
people. The previously rural countryside along major rivers (themselves
drastically changed by man) would take on the industrial/urban, instru-
mental orientation with predictable changes in social and economic
activities. Should accompanying industrial growth occur with power
plant development, the decline in the rural way of life will be extremely
rapid and irreversible and be of very large scale.
The lower energy scenarios essentially mean the effects described
above will be more localized and the urban/industrial effects somewhat
less pervasive in total magnitude. Nonetheless, where rural land is
converted into industrial use, the way of life, the possible loss of
prime agricultural land, and the very residents are shifted into an
entirely different frame of reference. The people as individuals adapt
better, we think, to irreversible change, but when a way of life tied
to a specific locale is changed or land changed from agricultural to
industrial use, the original pattern or use is irretreviably lost.
III-D-264
-------
This report ends on a note of caution for we see not enough
attention being paid to the social effects of the energy development
enterprise compared to the myriad other facets. This is generally true
of all large scale development and perusual of almost any Environmental
Impact Statement will confirm this. Though we have been tied to
secondary data and know of no individuals personally impacted by power
plant development, we do see the real likelihood of social and cultural
disruption and fragmentation in some possible plant site areas and have
some vision of the enormity of the personal social costs involved.
We are not unaware of the benefits that usually eventually accrue to
communities that have large-scale installations, however, we feel more
attention has been paid to the benefit rather than the cost dimension.
The description of likely impacts should provide some information
to policy-makers if the social cost dimension is considered important by
them. The general demographic makeup of a county can only be sugges-
tive of what kinds of people live there and what their values and
attitudes toward power plant development might be. It is also only
suggestive of receptiveness to externally-imposed change. However, given
our time and money constraints, we feel it is better than nothing.
III-D-265
-------
REFERENCES
Institute for Social Science Research. A Comparative Case
Study of the Impact of Coal Development on the May of Live of
People in the Coal Areas of Eastern Montana and Northeastern
Wyoming. Final Report, Missoula, University of Montana, June
1974, 2nd Ed.
III-D-266
-------
APPENDIX A
MAPS
III-D-267
-------
MAP OF ORBES REGION
III-D-268
-------
MAP III-D-1
OHIO RIVER BASIN STUDY (ORBS) REGION
OHIO RIVER DRAINAGE BASIN
COUNTIES NOT IN FBGION
100
200
Scale in Miles
SOURCE- U.S. Bireau of the Census
Prepared by Cartographic Laboratory and
Energy Resources Center, U I C C
III-D-269
-------
INSTRUMENTAL ORIENTATION MAPS
Technological Feasibility Sub-Orientation
Map III-D-2
Economic Benefit Sub-Orientation
Maps III-D-3 through III-D-7
(See also Maps III-D-50 through III-D-53,
III-D-57 through III-D-78,
III-D-86 through III-D-94)
III-D-270
-------
Map III-D-2
COAL PRODUCING COUNTIES, 1974
SOURCE: Mineral Industry Surveys. 1976, pp. 25 - 28
Limits of coal bearing rock
Counties with less than 1.0 million short tons
Counties producing 1.0 - 4.9 million short tons
Counties producing 5.0 million short tons or more
III-D-271
-------
MAP III-D-3
PERCENTAGE OF LAND IN FARMS, 1969
SOURCE: 1969 Census of Agriculture
Less than 25.0
25.0 - 49.9
50.0 - 74.9
75.0 - 100
III-D-272
-------
SOURCES:
MAP III-D-4
PERCENTAGE OF LAUD IN FOREST
U.S. Forest Service. Resource Buls. LS-3, NE-19, HC-7, Unpub,
^m^^^^^^^^
m$m$&miimm&^
Less than 15.0
15.0 - 29.9
:;v:\ 30.0 - 49.9
50.0 - 69.9
79.9 - 84.9
85.0 or more
III-D-273
-------
SOURCE:
MAP III-D-5
SMSA'S, 1970 AND 1974
Current Population Reports, Series P-26
- Population Estimates
SMSA County, 1970
SMSA County, 1974
III-D-274
-------
MAP III-D-6
MAJOR HIGHWAY TRANSPORTATION ROUTES
III-D-275
-------
OHIO RIVER BASIN STUDY (ORRS) REGION
MAP 111-0-7
MAJOR RIVERS
III-D-276
-------
TERRITORIAL ORIENTATION MAPS
Maps III-D-8 through III-D-12
III-D-277
-------
MAP III-D-8
1975 GENERATING CAPACITY
• - .
Plants present or under construction: Number of units scheduled for
operation by 1985:
(Total megawatt capacity) (Megawatts per unit = 200 or more)
Less than 1,000
T^ 1,000 - 1,999
• Fossil fuel
2,000 - 3,499
3,500 or more
X Nuclear fuel
III-D- 278
-------
MAP III-D-9
1985 GENERATING CAPACITY WITH SCENARIO I NEW UNITS
1985 Megawatt capacity:
Additional 1,000 megawatt units:
Less than 1,000
Coal
••'..y. 1,000
• i. • • "
w*./
- 1,999
!,000 - 3,499
3,500 or more
X Nuclear
III-D-279
-------
MAP III-D-10
1985 GENERATING CAPACITY WITH SCENARIO II NEW UNITS
1985 Megawatt capacity:
Additional 1,000 megawatt units:
Less than 1,000
• •• A 1,000
* * * •
- 1,999
2,000 - 3,499
3,500 or more
Coal
Nuclear
III-D- 280
-------
MAP III-D-11
1985 GENERATING CAPACITY WITH SCENARIO III NEW UNITS
1985 Megawatt capacity:
Additional 600 megawatt units:
•••'
• •
v.
Less than 1,000
1,000 - 1,999
2,000 - 3,499
3,500 or more
Coal
III-D-281
-------
MAP III-D-12
1985 GENERATING CAPACITY WITH SCENARIO IV NEW UNITS
1985 Megawatt capacity:
Additional 1,000 megawatt units:
Less than 1,000
;.-.;•• 1,000 - 1,999
* •
77 2,000 - 3,499
3,500 or more
Nuclear
III-D-282
-------
SENTIMENTAL ORIENTATION MAPS
Primordial Belongingness Sub-Orientation
Maps III-D-13 through III-D-47
Prestige Sub-Orientation
Maps III-D-48 through III-D-94
III-D-283
-------
MAP III-D-13
RESIDENCE OF POPULATION IN 1970
SOURCE: 1970 Census of Population - Table 9
SMSA's, 1970
S
S
URBAN (50% or over), pre-
dominantly in urbanized
areas
> URBAN (50% or over), pre-
' dominantly other urban
' '
Mixed RURAL (over 50%)
and URBAN
'\ RURAL (100%) in places of
less than 2,500
RURAL (100%) in places of
less than 1,000
Changes in SMSA's, 1974
» 9 > i
III-D-284
-------
MAP III-D-14
POPULATION DENSITY
SOURCE: City County Data Book - Table 2, Item 4
1,000 or more per sq. mile
n
400 - 999
200 - 399
II II II
100 - 199 per sq. mile
50 - 99
II II II
Less than 50 per sq. mile
III-D-285
-------
MAP III-D-15
PERCENTAGE OF POPULATION LIVING ON FARMS
SOURCE: 1970 Census of Housing - Table 60
Less than 25.0
25.0 - 29.9
30.0 - 39.9
40.0 or more
III-D-286
-------
MAP III-D-16
NET MIGRATION, 1960 - 1970
SOURCE: City County Data Book - Table 2, Item 6
Loss
;\ Gain, 0-9.9
Gain, 10.0 or more
III-D-287
-------
MAP III-D-17
NET MIGRATION, 1970 - 1974
SOURCE: Current Population Reports. Series P-26 - Population Estimates
Loss, less than 0
.-«;. Gain, 0-4.9
Gain, 5.0 - 9.9
Gain, 10.0 or more
III-D-288
-------
MAP III-D-18
POPULATION CHANGE, 1960- 1970
SOURCE: City County Data Book - Table 2, Item 5
Loss, 15.0 or greater
j .-•.*« Loss, less than 15.0
Gain, less than 5.0
Gain, 10.0 - 19.9
Gain, 20.0 - 29.9
Gain, 30.0 or more
III-D-289
-------
MAP III-D-19
PERCENTAGE CHANGE IN FARM POPULATION, 1960 - 1970
SOURCE: City County Data Book - Table 2, Item 170
Loss, 40.0 or more
Loss, 15.0 - 39.9
*The only gain was in Massac County, Illinois.
:\ . Gain*, or loss of less than
.".• i5.o
III-D-290
-------
MAP III-D-20
PERCENTAGE CHANGE IN URBAN POPULATION, 1960 - 1970
SOURCE: 1970 Census of Population - Table 9
:V Loss, 0 - 4.9
Loss, 5.0 or more
Gain, 0 - 4.9
yX/ Gain, 5.0 - 9.9
Gain, 10.0 - 19.9
Gain, 20.0 or more
III-D-29.1
-------
MAP III-D-21
PERCENTAGE CHANGE IN RURAL POPULATION, I960 - 1970
SOURCE: 1970 Census of Population - Table 9
••'.«"' Loss, 0 - 4.9
',* \ * *
Loss, 5.0 or more
Gain, 0 - 4.9
Gain, 5.0 - 9.9
Gain, 10.0 - 19.9
Gain, 20.0 or more
III-D-292
-------
MAP III-D-22
PERCENTAGE OF POPULATION FOREIGN BORN OR OF FOREIGN OR MIXED PARENTAGE
SOURCE: 1970 Census of Population - Table 43
Less than 1.0
1.0 - 2.9
•«••• 3.0 - 5.9
• . . * *
6.0 - 8.9
9.0 - 12.9
13.0 or more
III-D-293
-------
MAP III-D-23
PERCENTAGE OF NATIVE POPULATION RESIDING IN STATE OF BIRTH
V ... SOIIprF- ,1970 Census of Population - Table 43
^^^^^•^•:§&^^^^^^
fti&S^itSiiiitSiKJSSiK&St:-:::-!
Less than 60.0
60.0 to 69.9
70.0 to 79.9
'.;• 80.9 to 89.9
90.0 or more
TII-D-294
-------
MAP III-D-24
PERCENTAGE OF NATIVE POPULATION BORN IN NORTHEAST
SOURCE: 1970 Census of Population - Table 119
Less than 1.0
1.0 - 2.9
3.0 - 4.9
5.0 or more
III-D-295
-------
MAP III-D-25
PERCENTAGE OF NATIVE POPULATION BORN IN THE SOUTH
SOURCE: Census of Population - T.able 119
* - * • •'•'A-.-. . .V.'.V. ^l . . f..«».. fj\ .... , •^.•.L.
Less than 3.0
V. /.' 3.0 - 5.9
6.0 - 9.9
10.0 - 13.9
14.0 or more
III-D-296
-------
MAP III-D-26
PERCENTAGE OF NATIVE POPULATION BORN IN NORTH CENTRAL U.S.'
SOURCE: 1970 Census of Population - Table 119 .
Less than 3.0
3.0 - 5.9
6.0 - 9.9
10.0 - 13.9
14.0 or more
III-D-297
-------
MAP III-D-27
PERCENTAGE JF POPULATION RESIDING IN SAME COU.'ITY II! 1965
SOURCE: 1970 Census of Population - Table 119
v.*.. ...;••••• •{•-•- ••-**"*'*'1'- • • • r.'.'.'.v.M.v.'.v"'
w«M3t.^v.\%\v^v>vi.-.'.-.-.-.•.•> !rXv. 1-5«—
*• •»-•-)-juitd^d-uOthDOC^** * • • •jj.V***'' &*+\ _ QT
.•..:-./ Less than 70.0
70.0 - 79.9
80.0 - 84.9
i.O or rcore
III-D-298
-------
MAP III-D-28
PERCENTAGE OF POPULATION RESIDING IX SAME STATE IN 1965
SOURCE: 1970 Census of Population - Table 119
N
1
•.'• Less than 80.0
80.0 - 89.9
90.0 - 94.9
95.0 or more
IJI-D-299
-------
MAP III-D-29
MEDIAN AGE, 1970
SOURCE: City County Data Book - Table 2, Item 15
•Xv^*.v£-N>y->X*>X*lv'\>;£v'
•£-%•& Vff%;.ffA'fA^Vf^^.y-'<£---l-^
•^^"^tr^-^^f^:
^X!>h#a33N?:
Less than 25.0
•T 25.0 - 27.9
28.0 - 31.9
/
32.0 - 34.9
35.0 or older
III-D-300
-------
MAP III-D-30
BIRTH RATE PER THOUSAND, 1968
SOURCE: City County Data Book - Table 2, Item 21
Less than 14.0
- 16-9
17.0 - 18.9
19.0 - 19.9
20.0 or more
(State Birth Rates:
Illinois - 17.7, Indiana - 17.9,
Kentucky - 17.7, Ohio - 17.7)
III-D-301
-------
SOURCE:
MAP III-D-31
DEATH RATE PER THOUSAND, 1969
City County Data Book - Table 2, Item 22
Less than 8.0
>••:? 3.0 - 8.9
«• • • *
,*.*.».»
~~~ 9.0 - 11.9
(State Death Rates:
12.0 - 14.9
15.0 - 16.9
17.0 or more
Illinois - 10.1, Indiana - 9.6,
Kentucky - 10.3, Ohio - 9.6)
III-D-302
-------
MAP III-D-32
PERCENTAGE OF POPULATION UNDER 18, 1970
SOURCE: City County Data Book - Table 2, Item 13
Less than 33.0
33.0 - 37.9
38.0 or more
III-D-303
-------
MAP III-D-33
PERCENTAGE OF POPULATION AGED 20 TO 29
SOURCE: 1970 Census of Population - Table 35
Less than 11.0
11.0 - 13.9
;*.»•. 14.0 - 16.9
III-D-304
-------
MAP III-D-34
PERCENTAGE OF POPULATION AGED 30 TO 54
SOURCE: 1970 Census of Population - Table 35
Less tiian 25.0
25.0 - 26.9
27.0 - 28.9
S 29-° - 30.9
v
31.0 or more
III-D-305
-------
MAP III-D-35
PERCENTAGE OF POPULATION 65 OR OLDER, 1970
SOURCE: City County Data Book - Table 2, Item 14
s .,-.'- • = ••..*r'^,". •
. 1..-.- /' •-':.-. •' i '^,•-•-,
•.*..•• Less than 9.0
9.0 - 11.9
12.0 - 15.9
16.0 or more
(State percentages: Illinois - 9.9, Indiana - 9.5,
Kentucky - 10.5, Ohio - 9.4)
III-D-306
-------
MAP III-D-36
MALES AS A PERCENTAGE OF POPULATION 18 OR OVER
SOURCE: 1970 Census of Population - Table 16
—H>t 3L i ; i .""• rvc—j r~F"i*r?l^'T/>nn
;44%WMW/-^W1
^ ..„.„.S00"0 i.'* *i--*2! 1_^~Lr-Jr-l ,''vl '«•«<"• / Ar.-rS^
N
A
Less than 47.0
47.0 - 49.9
50.0 - 54.9
m
55.0 - 59.9
60.0 - 64.9
65.0 or more
III-D-307
-------
MAP III-D-37
SINGLE MEN AS PERCENTAGE OF MALE POPULATION 14 OR OLDER
SOURCE: 1970 Census of Population - Table 37
^p?pp;^4^
Less than 22.0
,«•«,* 22.0 - 24.9
:
-------
MAP III-D-38
SINGLE WOMEN AS PERCENTAGE OF FEMALE POPULATION 14 OR OLDER
SOURCE: 1970 Census of Population - Table 37
Less than 18.0
.-.«\ 18.0 - 19.9
« «»
*•«* *
25.0 - 29.9
30.0 or more
20.0 - 24.9
III-D-309
-------
MAP III-D-39
DIVORCED MEN AS PERCENTAGE OF MALES 14 OR OVER
SOURCE: 1970 Census of Population - Table 37
^- iscojrti., ..>gjfS,v -s iv,^^''''>i^\ "*"/<""v\,i
^ J %^-->_...'Tv.,,^ f*^*co''W---,>/I
-------
MAP III-D-40
DIVORCED WOMEN AS PERCENTAGE OF FEMALES 14 OR OLDER
SOURCE: 1970 Census of Population - Table 37
N
r-
£r-:;- ^^Wfe»;"KX^-^^f^^>)/\A7"?\5U7^
Less than 2.0
2.0 - 3.4
!.5 - 3.9
4.0 or more
III-D-311
-------
MAP III-D-41
WIDOWED MEN AS PERCENTAGE OF MALES 14 OR OLDER
SOURCE: 1970 Census of Population - Table 37
\-ypq /RIV
i«lf-.t. v |^j|£Li«M"/'
4*:NBS«f
«««..«>.,?£" li/^x? -2^ • K"1^! ••"•« / /
ii-^-V^J"60MXlll r? 1. -;•"— "-?!*?,
5^^wagpi.
-:%)i6\]^:5®^ffe
N
i
Less than 3.0
3.0 - 3.9
4.0 - 4.9
5.0 or more
III-D-312
-------
MAP III-D-42
WIDOWED UOMEU AS PERCENTAGE OF FEMALES 14 OR OLDER
SOURCE: 1970 Census of Population - Table 37
Less than 10.0
r^r 10.0 - 12.9
^±L
13.0 - 15.9
16.0 - 18.9
19.0 or more
III-D-313
-------
MAP III-D-43
MARRIED MALES AS PERCENTAGE OF MALE POPULATION 14 OR OVER
SOURCE: 1970 Census of Population - Table 16
Less than 55.0
~/Tt~' 55.0 - 59.9
•••V
60.0 - 64.9
65.0 - 69.9
70.0 or more
1II-D-314
-------
MAP III-D-44
MARRIED UOMEN AS A PERCENTAGE OF FEMALES 14 OR OVER
SOURCE: 1970 Census of Population - Table 16
.«..«
Less than 55.0
55.0 - 59.9
60.0 - 64.9
65.0 - 69.9
70.0 or more
III-D-315
-------
MAP III-D-45
MUSBAUD-UIFE FAMILIES AS A PERCENTAGE OF TOTAL FAMILIES
SOURCE: 1970 Census of Population - Table 36
Less than 85.0
..-.:". 85.0 - 86.9
.V.;-
90.0 - 91.9
92.0 or more
87.0 - 89.9
III-D-316
-------
MAP III-D-46
PERCENTAGE OF FAMILIES WITH CHILDREN UNDER 18
SOURCE: 1970 Census of Population - Table 36
Less than 46.0
t-..\ 46.0 - 49.9
». * •
50.0 - 53.9
III-D-317
-------
MAP III-D-47
PERCENTAGE OF FAMILIES WITH A FEMALE HEAD
SOURCE: City County Data Book - Table 2, Item.51
Less than 6.0
6.0 - 7.9
8.0 - 10.9
11.0 - 13.9
14.0 or more
III-D-318
-------
MAP III-D-48
MEDIAN SCHOOL YEARS COMPLETED, POPULATION OVER 25
SOURCE: City County Data Book - Table 2, Item 24
•, v.vX'iX»;iiii>>K>cW!-X'"!V i H
SjF*2^^
§j """IJJ r^*' I ''"i****^^*"*
-~«.v TT J
Less than 8.0
8.0 - 8.9 -
9.0 - 9.9
UB
10.0 - 10.9
12.0 or more
III-D-3.1.9
-------
MAP III-D-49
PERCENTAGE OF PERSONS 25 OR OLDER WITH LESS THAN FOUR YEARS OF
HIGH SCHOOL, 1970
SOURCE: City County Data Book - Table 2, Item 26
Less than 40.0
40.0 - 49.9
50.0 - 69.9
70.0 - 79.9
f
80.0 or more
III-D-32Q
-------
MAP III-D-50
PAID CIVILIAN WAGE AND SALARY EMPLOYMENT COVERED IN
COUNTY BUSINESS PATTERNS. 1973
Less than 500
10,000 - 19,999
-. 500 - 999
•
1,000 - 2,999
3,000 - 9,999
S 20,000 - 49,999
50,000 - 99,999
100,000 or more
III-D-321:
-------
MAP III-D-51
RATIO OF WORKERS WORKING IN COUNTY TO WORKERS RESIDING IN COUNTY, 1970
SOURCE: Bureau of Census - Map GE-50, No. 63
More Workers than working residents: Fewer Workers than working reside/its:
ILess than .75
1.15 or more
1.00 - 1.14
Counties without a signi-
ficant volume of
commuting
0.75 - 0.84
0.85 - 0.99
III-D-322
-------
MAP III-D-52
PRIMARY ECONOMIC ACTIVITY
SOURCE: County Business Patterns. 1973 - Table 2
Manufacturing, 50% or more
40% - 50%
n
Retail Trade, 30% or more
Mining, 30% or more
Services, 30% or more
III-D-328
-------
MAP III-D-53
VALUE ADDED BY MANUFACTURE, 1972 (Millions)
Less than 15.0
15.0 - 49.9
TTT 50.0 - 99.9
200.0 - 499.9
500.0 - 999.9
1,000.0 or more
100.0 - 199.9
III-D-324-
-------
MAP HI-D-54
FEMALES AS A PERCENTAGE OF CIVILIAN WORK FORCE, 1970
SOURCE: City County Data Book - Table 2, Items 34 and 35
Less than 30.0
30.0 - 32.9
33.0 - 36.9
37.0 - 39.9
40.0 or more
III-D-32S
-------
MAP III-D-55
PERCENTAGE OF FAMILIES WITH BOTH HUSBAND AND WIFE IN WORK FORCE, 1970
SOURCE: City County Data Book - Table 2, Items 50,35,36
°K C"'K J»^)S»§3 H l>n
_
J I/.'»'.JN .-—-r ------ ,- . y?- - r
( .— .jg (•• i LL», j"™- c-- )-=fe
J- -------- J ,.^-J ' i f I«N:I | f Xj.L7T
./ I^CSWTtHjJ - lj33fe*^C>CV- ''•' ^ __ %'
- ^ .
'^ "'"' i ""'' i.*. .^_j^r*"''' wfc.":-' \ ;.** ' •„•' ^£5f
.•••:/: Less than 20.0
Ull
20.0 - 24.9
25.0 - 29.9
30.0 - 34.9
35.0 - 39.9
40.0 or more
III-D-326
-------
MAP III-D-56
UNEMPLOYED AS PERCENTAGE OF CIVILIAN WORK FORCE, 1970
SOURCE: City County Data Book - Table 2, Item 37
_ . . - - ..-____._... ,,.-.. fc., i i i y» • I —_ >"^H
W&&W3S^%3\ —
10.0 or more
8.0 - 9.9
6.0 - 7.9
3.0 - 5.9
Less than 3.0
III-D-3&I
-------
MAP III-D-57
PERCENTAGE OF EMPLOYED CIVILIAN LABOR FORCE IN PROFESSIONS OR MANAGEMENT
SOURCE: City County Data Book - Table 2, Item 45
Less than 10.0
0 - 24.9
iTvT 10.0 - 14.9
15.0 - 19.9
III-D-328
-------
MAP III-D-58
PERCENTAGE OF EMPLOYED CIVILIAN LABOR FORCE WORKING IN CONSTRUCTION, 1970
SOURCE: City County Data Book - Table 2, Item 43
Less than 5.0
5.0 - 9.9
10.0 - 14.9
15.0 or more
III-D- 329
-------
MAP III-D-59
PERCEiNTAGE OF EMPLOYED CIVILIAN LABOR FORCE WORKING IN
WHOLESALE AND RETAIL TRADE, 1970
SOURCE: City County Data Book - Table 2, Item 40
Less than 10.0
••\.\- 10.0 - 14.9
15.0 - 19.9
| 20.0 - 25.9
HI-D-330
-------
MAP III-D-60
PERCENTAGE OF CIVILIAN LABOR FORCE EMPLOYED AS CRAFTSMEN OR FOREMEN,
1970
SOURCE: City County Data Book - Table 2, Item 47 •
Less than 10.0
^r 10.0 -11.9
12.0 - 14.9
mi1
5.0 - 16.9
17.0 - 18.9
19.0 or more
III-D-331
-------
MAP III-D-61'
FEDERAL CIVILIAN EMPLOYMENT, DECEMBER 31, 1974
^£^LJ£Sj ~' -^—- — -
100 - 299
1,000 or more
III-D-332
-------
MAP III-D-62
PERCENTAGE OF EMPLOYED CIVILIAN LABOR FORCE IN GOVERNMENT, 1970
SOURCE: City County Data Book - Table 2, Item 44
20.0 - 24.9
III-D-333
-------
MAP III-D-63
PERCENTAGE OF EMPLOYED CIVILIAN LABOR FORCE WORKING IN MANUFACTURING, 1970
SOURCE: City County Data Book - Table 2, Item 39
N
/.
Less than 10.0
.•.«'. 10.0 - 19.9
30.0 - 39.9
40.0 or more
20.0 - 29.9
III-D-334
-------
MAP III-D-64
PERCENTAGE OF EMPLOYED CIVILIAN LABOR FORCE IN EDUCATIONAL SERVICES, 1970
SOURCE': City County Data Book - Table 2, Item 42
Less than 5.0
5.0 - 9.9
10.0 - 14.9
i.O - 19.9
20.0 or more
III-D-335
-------
MAP III-D-65
PERCENTAGE OF FARM OPERATORS WORKING 100 OR MORE DAYS OFF FARM, 1969
SOURCE: City County Data Book - Table 2, Item 196
N
i
Less than 30.0
30.0 - 39.9
40.0 - 49.9
50.0 - 59.9
60.0 - 69.9
70.0 or more
III-D-336
-------
MAP III-D-66
MEDIAN FAMILY INCOME, 1969
SOURCE: City County Data Book - Table 2, Item 58
Less than 4,000
;*••"*..* 4,000 - 4,999
*
5,000 - 6,999
7,000 - 8,999
9,000 - 9,999
10,000 or more
III-D-337
-------
MAP III-D-67
PERCENTAGE OF FAMILIES WITH INCOME OF $15,000 or more, 1969
SOURCE: City County Data Book - able 2, Items 56, 57
Less than 5.0
5.0 - 7.4
7.5- 14.9
15.0 - 19.9
20.0 or more
III-D-338
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MAP III-D-68
MEDIAN FAMILY INCOME FOR FARM POPULATION, 1969
SOURCE: City County Data Book - Table 2, Item 171
Less than 5,000
•—••:'. 5,000 - 5,999
* « * • •
*••«••'.
6,000 - 7,999
8,000 - 8,999
9,000 - 9,999
10,000 or more
Note: The following counties have fewer than 100 engaged in
farming, hence data are not reported: Marion in Indiana; Bell, Harlan,
Knott, Leslie, Letcher, McCreary, Martin and Perry in Kentucky.
III-D-339
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MAP III-D-69
PER CAPITA MONEY INCOME FOR 1969
SOURCE: Bureau of Census, Map GE-50, Mo. 57
Less than $1,500
T-f^ $1 ,500 - 1 ,999
J5OT $2,500 - 2,999
$3,000 - 5,446
$2,000 - 2,499
United States per capita money income for 1969: $3,119
III-D-340
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SOURCE:
MAP III-D-70
PER CAPITA PERSONAL INCOME, 1973
Survey of Current Business - Table 2, April, 1975
Less than $3,000
•«'.,• $3,000 - 3,999
$5,000 - 5,999
$6,000 or more
$4,000 - 4,999
III-D-341
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MAP III-D-71
MEDIAN HOUSEHOLD EFFECTIVE BUYING POWER, 1974
SOURCE: Sales Management. July 21, 1975
^ Less than $5,000
- 7,999
$11,000 - 12,999
$13,000 or more
,000 - 10,999
III-D-342
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MAP III-D-72
PERCENTAGE OF HOUSEHOLDS WITH EFFECTIVE BUYING POWER LESS THAN $3.,000
SOURCE: Sales Management. July 21, 1975
X*>Xv!e&iw:
-------
MAP III-D-73
PERCENTAGE OF HOUSEHOLDS WITH EFFECTIVE BUYING POWER OF $15,000 OR MORE,1974
SOURCE: Sales Management. July 21, 1975
^^S-^IW^^W
$#£&*# yf^^&^mm
&&$$& t&^Mtimm
Less than 10.0
10.0 - 19.9
11
20.0 - 29.9
30.0 - 39.9
40.0 or more
III-D-344
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MAP III-D-74
PERCENTAGE OF FAMILIES BELOW THE LOW INCOME LEVEL IN 1969
SOURCE: City County Data Book - Table 2, Item 62
!\v.'*XftX'isv';jvXvr' •'•XwvT^jiix-!-x^
•iiiS^fgs
^-R^:;^/-1^^:
?ii»aai?fc*?fcJ:*'4T^
T^.?^p:iA7»H""ir'M''* i
^?i_« _ »J> "cocir1 ril«r«_
•.,^^^•..-> i TH -cti-J.-, r._J".'J-U.c»w»l« J ^SL—iJiVI ?* »i1
^^^-ji^AAR^WS1
"••cr-;T- -- [/^^^^J^^-W-'-
'Li -'\ i? 'n/G,a5c, : :•* *!,..--0"%v.#rj/.-v_"—7"y^v:,aW'
:^p-i^SML^f^S-fi^feiclfesS
. •' *.. Less than 10.0
'.«•..
10.0 - 19.9
20.0 - 34.9
35.0 - 49.9
50.0 or more
III-D-345
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MAP III-D-75
PERCENTAGE OF LOW INCOME POPULATION 65 OR OLDER,1970
SOURCE: City County Data Book - Table 2, Item 66
' * '-' *-"-"•"•"•" .".*1'.WIVfc^^ejj£«^*"*H%*.-
Less than 10.0
T~7vV "10.0 - 19.9
• . . •,
30.0 - 34.9
36.0 or more
20.0 - 29.9
III-D-346
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MAP III-D-76
PERCENTAGE OF LOW INCOME POPULATION UNDER 18, 1970
SOURCE: City County Data Book - Table 2, Item 65
N
i
W&VS«,T> * V"-y v^> *3s
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MAP III-D-77
PUBLIC ASSISTANCE, FEBRUARY, 1972: PERCENTAGE PAID FOR OLD AGE ASSISTANCE
SOURCE: City County Data Book - Table 2, Item 74
Less than 5.0
."..\ 5.0 - 9.9
10.0 - 14.9
15.0 - 29.9
III-D-348
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MAP III-D-78
PERCENTAGE OF PUBLIC ASSISTANCE GOING TO FAMILIES WITH DEPENDENT CHILDREN
1972
x , SOURCE: City County Data Book - Table 2, Item 75
Less than 30.0
v>- • 30.0 - 44.9
45.0 - 59.9
60.0 - 74.9
75.0 or more
III-D-349
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MAP III-D-79
PERCENTAGE CHANGE IN NUMBER OF HOUSEHOLDS, 1960 - 1970
SOURCE: 1970 Census of Population - Table 16
••• . Loss
SS.
Gain, less than 5.0
Gain, 10.0 - 17.9
Gain, 18.0 - 24.9
Gain, 25.0 or more
III-D-350
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MAP III-D-80
PERCENTAGE CHANGE IN NUMBER OF YEAR ROUND HOUSING UNITS, 1960 - 1970
SOURCE: City County Data Book - Table 2, Item 78
Gain, 20.0 or more
Gain, 10.0 - 19.9
Gain, 5.0 - 9.9
Gain, 0 - 4.9
;. ... Loss, 0-4.9
»•»«i
Loss, 5.0 or more
(Note: Brown County, Indiana = 77.4% Gain)
III-D-351,
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MAP III-D-81
PERCENTAGE OF YEAR ROUND HOUSING UNITS BUILT BETWEEN 1960 and MARCH 1970
SOURCE: 1970 Census of Housing - Table 62
ym&&&f&s*t&i®
Less than 16.0
16.0 - 24.9
•• * • 25.0 or more
III-D-352
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MAP III-D-82
HOME TENURE FOR YEAR ROUND HOUSING UNITS
SOURCE: 1970 Census of Housing - Table 29
N
i
80% or more owner-occupied
75% - 79%
65% - 74% owner-occupied
:/»»*' Less than 65% owner-occupied
• 4 . .,
'
III-D-353
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MAP III-D-83
PERCENTAGE OCCUPIED HOUSING UNITS LACKING SOME OR ALL PLUMBING FACILITIES,
1970
SOURCE: City County Data Book - Table 2, Item 90
ruiioi. /JAviL'T^...? * * [;»Ti»
;.••. Less than 5.0
5.0 - 9.9
10.0 - 14.9
15.0 - 19.9
30.0 - 39.9
40.0 or more
III-D-354
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MAP III-D-84
PERCENTAGE OF OCCUPIED HOUSING UNITS WITH 1.01 OR MORE PERSONS
PER ROOM, 1970
v SOURCE: City County Data Book - Table 2, Item 91
mi
Less than 5.0
5.0 - B.9
10.0 - 14.9
15.0 or more
6.0 - 9.9
III-D-355
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MAP III-D-85
PERCENTAGE OF YEAR ROUND HOUSING UNITS IN ONE-UNIT STRUCTURES, 1970
SOURCE: City County Data Book - Table 2, Item 80
Less than 60.0
v*V" 60.0 - 69.9
A . •,"
80.0 - 89.9
90.0 or more
IT
70.0 - 79.9
III-D-356
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MAP III-D-86
MEDIAN VALUE OF OWNER-OCCUPIED SINGLE FAMILY DWELLINGS, 1970
SOURCE: City County Data Book - Table 2, Item 83
Less than $7,000
•Tv. $7,000 - 9,999
$10,000 - 12,999
-• .»«
$13,000 - 15,999
$16,000 or more
III-D-357
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MAP III-D-87
MEDIAN GROSS RENT FOR RENTER-OCCUPIED HOUSING, 1970
SOURCE: City County Data Book - Table 2, Item 89
Less than $60'
$60 - 79
- 99
$100 - 119
$120 or more
III-D-358
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MAP III-D-88
PERCENTAGE CHANGE IN NUMBER OF FARMS, 1964 - 1969
SOURCE: City County Data Book - Table 2, Item 174
I T CUHI^N
^ri-^illpist
VJ '" ' ' "'
N
i
Y" -BBBI^^K^^ij.^-''^;''"^ /<-r^'r& ^^-r
S^\l^fe^iMv^^\%^^M^^
Loss, 20.0 or more
Loss, 15.0 - 19.9
Loss, 10.0 - 14.9
Loss, 5.0 - 9.9
Loss, less than 5.0
Gain, less than 5.0
..'*. Gain, 5.0 - 9.9
Gain, 10.0 or more
III-D-359
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MAP III-D-89
PERCENTAGE CHANGE IN FARM ACREAGE, 1964 - 1969
SOURCE: City County Data Book - Table 2, Item 176
^^?^^m^^mM^y--<-^
t/SS?!^ «„„ gu.i«, p2H;':$;$^
*•"•» I " SAUC |<5, IX-WvX-X
r i« • « -i —^,^-^un* i- I r^T
\ l*o • • • sHrttv/i _T Iv'coLllryT
\\-^-Jm=f-m
' *> >• *''. \ rV, v * I
V / '"crrfT '\ | j.s.r»I \.\ / y"N(
N
A
4a2f5l^^¥3ligiS»
^^ip!i^p?^P?^^|fS^
^iX^^^^^-^^^^^'^ffl
!fe^^38ffls^^^^}iMiiilrl
•""v>,-
-------
MAP III-D-90
AVERAGE VALUE OF FARM LAND AND BUILDINGS PER ACRE
SOURCE: 1969 Census of Agriculture
^/WiSS-jS^^
'/S^SiiS;^
D
Less than $200
$200 - 299
$300 - 399
$400 - 499
$500 or more
III-D-361
-------
MAP III-D-91
AVERAGE VALUE OF AGRICULTURAL PRODUCTS PER ACRE
SOURCE: 1969 Census Of Agriculture
or less
$85 or more
dl
$41 - 84
III-D- 362
-------
MAP III-D-92
AVERAGE NUMBER OF ACRES PER FARM
SOURCE: 1969 Census of Agriculture
ttEffl
Less than 100
100 - 149
150 - 199
III-D- 363
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MAP III-D-93
PERCENTAGE OF FARMS WITH SALES OF $2,500 OR MORE, 1969
SOURCE: 1969 Census of Agriculture - Table 1, County Summary
Less than 20.0
20.0 - 39.9
40.0 - 49.9
50.0 - 69.9
70.0 - 79.9
80.0 - 89.9
90.0 or more
III-D-364
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MAP III-D-94
PERCENTAGE OF CLASS I-V FARMS WITH SALES OF $10,000 OR MORE, 1969
SOURCE: City County Data Book - Table 2, Items 185 and 186
Less than 15.0
fv7\Yl is.
!••• % ••
I •"".•!
.0 - 24.5
25.0 - 34.9
50.0 - 59.9
60.0 - 74.9
75.0 or more
35.0 - 49.9
III-D-365
-------
SYMBOLIC ORIENTATION MAPS
III-D-366
-------
HAP III-D-95
STATE AND NATIONAL OUTDOOR RECREATION AREAS
SOURCES: "Ohio State Parks"
Illinois Outdoor Recreation
Facilities Guide to Kentucky State Parks
State Highway Maps
National Forests
State Parks and recreation areas ( where infor
mation was available)
III-D-367
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MAP III-D-96
RANKING CHRISTIAN DENOMINATIONS, 1971
SOURCE: Map, Glenmary Research Center
(Reported Church Membership^
50% or more: .
'Baptist
Catholic
Methodist
25% or more:
Baptist
Catholic
••••"•"? Methodist
•::-v?v
*. *!••*•*
Lutheran
Presbyterian
III-D-368
-------
MAP III-D-97
MUSEUMS LISTED IN THE 1975 OFFICIAL MUSEUM DIRECTORY
&ttMMiX'i*if9ft!'--'"',-'''>*itri&
III-D-369
-------
MAP III-D-98
NATIONAL REGISTER OF HISTORIC PLACES. 1976
XO'XvJ^}wI£v)-WCCCxIx?Xfc_^i.'k
:SSS^SS3Msj®Sfl^.
dumber of olaces listed:
One
Ten
III-D-370
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