The relation of college-level attendance to selected characteristics of the population
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THE RELATION OF COLLEGE-LEVEL ATTENDANCE TO SELECTED CHARACTERISTICS OF THE POPULATION
A Dissertation Presented, to ,7 the Faculty of the School, of. Education The University of Southern California'
In Partial Fulfillment of the Requirements f o r .the Degree Doctor of Education
by J Jay N. Holliday June 1950 *
UMI Number: DP25780
All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion.
DlsssrlM&n Publishing
UMI DP25780 Published by ProQuest LLC (2014). Copyright in the Dissertation held by the Author. Microform Edition © ProQuest LLC. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code
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T h is disse rta tio n , w r it t e n u n d e r the d ir e c t io n o f the C h a ir m a n o f the c a n d id a te ’s G u id a n c e C o m m itte e a n d a p p r o v e d by a l l m em b ers o f the C o m m itte e , has been pre se n te d to a n d a ccep ted by the F a c u l t y o f the S c h o o l o f E d u c a t io n in p a r t i a l f u l f i l l m e n t o f the re q u ire m e n ts f o r the degree o f D o c t o r o f E d u c a tio n . Date.
L ..
Dean Guidance Committee
Chairman
TABLE OF CONTENTS
CHAPTER I*
PAGE
THE PROBLEM AND P R O C E D U R E ................... The prediction of enrollment
II.
1
.............
1
Statement of the p r o b l e m .................
3
Importance of the study . . . .............
4
Definitions of the terms u s e d .............
5
Limitations of the study
...............
6
Procedure of the s t u d y ...................
7
Organization of the study .................
8
REVIEW OF THE DATA AND LITERATURE PERTAINING TO COLLEGE-LEVEL ATTENDANCE . . . ........
9
Studies relating to predictions of college-level attendance
...............
9
Extent of the literature
.
9
...........
The changing concepts of higher education
.....................
9
...............
10
Predictions in school surveys ...........
11
Predictions for individual colleges . . .
17
Types of predictions
•
Predictions and forecasts of national e n r o l l m e n t .......................
23
The College-Age Population Study* 1947-64 ................................
31
iii CHAPTER
PAGE ...............
33
Government publications ...................
33
Other related literature
Biennial surveys of higher education
. .
33
The Residence and Migration of College S t u d e n t s .............................. Sources of statistical data
.............
The limitation of statistical data
III.
• . .
3436 36
Census d a t a ..............................
38
S u m m a r y ....................................
39
Limitations of the l i t e r a t u r e ...........
39
Contributions of the literature . * • . .
40
AN EVALUATION OF SIGNIFICANT FACTORS INFLUENCING ATTENDANCE
..................
41
The distribution and residence of the population
• • • • • • • •
.............
41
The purpose of the c h a p t e r ............
41
Distribution of the population
........
41
Urban and rural r e s i d e n c e ...............
42
Differentials due to sex, race, nativity, and i n t e l l i g e n c e ............
45
Sex as a factor in attendance . . . . . .
45
Race and nativity as measurable factors •
47
Intelligence and college-level attendance
50
Variables in the social or economic
iv CHAPTER
PAGE e n v i r o n m e n t ..............................
52
Educational o p p o r t u n i t y .................
52
Economic changes as a factor in collegelevel attendance... • ..................
53
The need for higher e d u c a t i o n ............
54
Occupational status... ...................
5?
Modification of thec u r r i c u l a ............
56
College student mortality ........
57
...
Ability of the state to support education
59
The esteem in which education is held • .
59
High school attendance or graduation
60
...................
61
..................................
61
College attendance Summary
. .
The distribution and residence of the p o p u l a t i o n ..............
.
61
Differentials due to sex, race, nativity, and i n t e l l i g e n c e .....................
62
Variables in the social and economic i
e n v i r o n m e n t .............................
62
The relation of occupational status to other factors . . IV.
. ..................
63
THE SOCIAL-ECONOMIC CLASSIFICATION OF THE LABOR FORCE AS AN INDEX OF COLLEGE-LEVEL A T T E N D A N C E ................................
65
V
CHAPTER
PAGE The relation between education and the labor f o r c e .........................
65
The purpose of the c h a p t e r .............
65
The relation of education to occupation .
65
The extent to which occupation is a common factor
. . . .......................
68
Distribution and residence of the popu lation and o c c u p a t i o n ................. Sex and occupation
.
Race and occupation
................. ..........
Nativity and occupation .
68 69 69
.............
The role of intelligence in occupation
•
70 71
Occupation and the need for higher e d u c a t i o n ..............................
72
Modification of the curriculum and o c c u p a t i o n s ............
73
Economic changes and occupations
. . . .
Educational opportunity and occupation
75 .
76
Extent and limitations of social-economic data
...............
77
The United States Census classification of occupations S u m m a r y ........
. . . . . . . . . . . .
77
- ............
80
The relation between education and
vi CHAPTER
PAGE occupations
.....................
80
The extent to which occupation is a common factor
• • • • • • • • .
........
. .
81
The extent and limitations of social81
economic data • V.
THE BASIS FOR THE PREDICTION OF COLLEGE-LEVEL ATTENDANCE FROM CHARACTERISTICS OF THE POPULATION
..............................
Sources of data .
.......................
The purpose of the c h a p t e r ............. • ............
The United States Census
83 83 83 83
Methods of e n u m e r a t i o n .................
84
College-age population
...........
84
Defining college-age population . . . . .
85
..
Factors that reflect educational .......................
89
Educational o p p o r t u n i t y .................
89
opportunity
The relative value of privately and publicly controlled colleges in de termining
attendance
• • • • • • • • •
91
The degree to which distant colleges affect attendance ..................... Opportunity
on the secondary level
Opportunity
on the college level
92
...
93
. . . .
93
vii CHAPTER
PAGE S u m m a r y .................................... Sources of data .
...........
94 * 94
Factors that reflected educational o p p o r t u n i t y ............................ VI •
95
AN ESTIMATE OF COLLEGE-LEVEL ATTENDANCE BASED ON SELECTED CHARACTERISTICS OF THE P O P U L A T I O N ................ ...............
96
The factors selected and their objective relationship to college-level attendance
96
The purpose of thischapter .
96
..........
96
Characteristics of thepopulation . . . . I
' Characteristics of the population
selected for use in prediction
. . . .
97
The relationship of the major occupation groups to college-level attendance
. .
The methods used for prediction . . . . . . Selection of factors
101 106
. . . . . . . . . .
106
Application of the technique to data for 1910, 1920, 1930, 194-0, and 194-8
. . . .
110
Comparison of the labor group— 1910 to 1948
.
..............................
Estimating attendance
bystates ...........
Attendance in the States in 194-0
. . . .
S u m m a r y ..................................
110 114 114
•
120
viii CHAPTER VII.
PAGE
THE PREDICTION OF COLLEGE-LEVEL ATTENDANCE IN A C O L L E G E - C O M M U N I T Y .....................
123
An evaluation of the method used in estimating attendance for the nation and the several s t a t e s ....................................
123
The purpose of
123
the chapter
•• • • . . . •
I/* A review of the method of prediction
. . .
123
^/iTalues reflected by the factors used in p r e d i c t i o n ..............................
12*+
Estimating the value of a non-quantitative f a c t o r ....................................
126
The method used . ..........................
126
\TThe importance of c o n t i g u i t y .............
128
Jrypes of educational insti t u t i o n s ........
129
^The counties as college-communities . . . .
130
The relative influence of types of colleges 4 Definitions of
the g r o u p s ........
133
Application of
the m e t h o d ........
13*+
The net influence of the new variable . . .
131
13*+
\ Potential a t t e n d a n c e ........................
l*+2
S u m m a r y .........................................
l*+3
An evaluation of the estimate by states . .
l*+3
Establishing the value of contiguity
lMt
. . .
Estimating potential* a t t e n d a n c e ..............
l*+5
ix CHAPTER
PAGE
VIII.SUMMARY AND C O N C L U S I O N S ............................. Summary . . . . . . . . . . .
..................
lV6 1^6
The purpose of the s t u d y ..........
lV6
Definition of terms
1^7
The procedure
. . . . . . .
...................
The factors that influenced attendance
1^8 . •
1V8
The selection of factors used in prediction
1^9
The development and application of the ...................
formula
.
151
Application of the formula to state estimates
.........................
1?2
National and state estimates compared . . .
153
Evaluating the influence of contiguity
153
Potential attendance Conclusions
• •
. . . . . .
15^
• • • • • • • • • • • • • • • • •
155
The relationships established ................
155
The value of the study
156
................
Suggestions for additional research . . . . .
158
Equality of educational opportunity . . . .
158
Types of educational institutions . . . . .
.159
An age-grade study Race and nativity
.
.................
.
159
..................
B I B L I O G R A P H Y .................. ......................
160 161
CHAPTER
PAGE
A P P E N D I C E S ....................................... Appendix A:
174-
Definitions and an Explanation of the
Classification of the Labor Force ..................
175
Definitions of school attendance and the eleven classifications of the labor force
176
.............
Significance of the social-economic groups
. .
.
l8 l
Sufficiency of the social-economic groups as a 185
scale • • • • • • • • . . « » • • • • » . » » • Appendix B:
Data Used in P r e d i c t i o n .........
192
A List of California junior and senior colleges in 1940 ..................... ..
.
..............
An explanation of the grouping of the counties Appendix C:
.
193 201
The Calculation of Multiple R, and
Beta Weights and Data Pertaining to Reliability The source and reliability of the data
...........
The estimates for attendance, 1910-1948 . . . • The calculation of new values
211
.
214
.............
The estimates for states and c o u n t i e s .......
215 216
The method employed to estimate attendance in c o u n t i e s ...................................
212
217
LIST OF TABLES TABLE I*
PAGE School Attendance for Persons l*f to 2b Years Old, hy Employment Status, Single Years of Age, and Sex, for the United States: 19^0
II.
•
*f6
Employment for Persons 1^ to 2b Years Old, Not Attending School, by Single Years of Age, and Sex, for
III.
Population
IV.
Population in 19^0, by
V.
the United States: 19b0
•
*+9
l*fto 2b Years Attending College
.
8?
18to 2b
Years Old Attending School
Grade L e v e l s ...................
88
The Correlation between College-Level Attend ance and Selected Factors and the Correlation between Factors
VI.
. . . . . . . .
107
The Intereorrelation of Attendance 18 to 2b with Attendance 16 to 17 and Three Classifications of the Major Occupation
VII. VIII.
G r o u p s ................. -....................
108
School Attendance College-Age Group (18 to 2b)
113
The Correlation of Each Factor with CollegeLevel Attendance (0) and with Each Other . .
IX.
College-Level Attendance for Each of the *f8 States and the Attendance Predicted From Certain Characteristics of the Population for 19^0 Expressed as a Percentage of the
116
TABLE
PAGE 18 to 2b Age Group •
X.
117
College-Level Attendance in 19^0, Attendance Estimated by Linear Regression on Four Factors, Residual z* Attendance Estimated by Including the
Non-Quantitative
Factor,
and Residual z ff
for Cbunties in Group I .
135
X I * . College-Level Attendance in 19^0, Estimated Attendance by Linear Regression on Four Factors, Residual z*, Attendance Estimated by Including the
Non-Quantitative
Factor,
and Residual z fl
for the. Counties
in Group
II . . . XII.
. ..........
136
College-Level Attendance in 19*+0, Attendance Estimated by Linear Regression on Four Factors, Residual z 1, Attendance Estimated by Including the Non-Quantitative Factor, and Residual z 11 for Counties in Group III
XIII.
137
College-Level Attendance in 19^0, Attendance Estimated by Linear Regression on Four Factors, Residual z 1.,, Attendance Estimated by Including the Non-Quantitative Factor, and Residual z tl for Counties in Group IV .
XIV.
Values of the Non-Quantitative Variable . . .
138 139
xiii TABLE XV.
PAGE A Comparison of the Value of the Independent V a r i a b l e s ..............
XVI.
School Attendance, by Age and Sex, for the United States: 19^0 .
XVII.
1^1
...............
Employed Workers, by Major Occupation Group and Sex, for the United States: 19*+0
XVIII.
178
. ...
182
Wage or Salary Income Received in 1939 by Experienced Workers in the Labor Force (Except Those on Public Emergency Work), in Selected Major Occupation Groups in 19*+0, Who Worked 12 Months in 1939, for the United S t a t e s ...............................
XIX.
187
Years of School Completed by Experienced Workers
in the Labor Force (Except Those on
Public Emergency Work), by Major Occupation Group, for the United States: 1 9 ^ * 0 ..... XX.
188
Characteristics of the Population of the United States Used in Prediction Expressed as Percentages of the Respective Age Groups or of the Labor Force
XXI.
.....................
190
Characteristics of the Population Used in Prediction for State of California by Count^ ies Expressed as a Percentage of the r
Respective Age Groups or the Labor Force
. •
208
TABLE XXII.
PAGE Characteristics of the Population Used in Estimates of Attendance for 1910-1948 Expressed as Percentages of the Respect ive Age Group (16-17) in theLabor
XXIII.
Force. .
215
The intercorrelation of Attendance 18 to 24 with Attendance 16 to 17 and Three Classifications of the Major Occupation 220
Groups.................................. XXIV.
Determination of the Beta Coefficients for Estimate, 1910-1948 .......................
XXV. XXVI. XXVII. XXVIII.
V Values for Estimates, 1910-1948
221
..
222
Z Values for Estimates, 1910-1948 . . . . . . Absolute Values for Estimates 1910-1948 . .
223 .
The Correlation of Each Factor with CollegeLevel Attendance (0) and with Each Other. .
XXIX.
224
226
Determination of the Beta Coefficients for State and County E s t i m a t e ............
227
XXX.
V Values for State and County Estimates . .
.
228
XXXI.
Z Values for State and County Estimates . .
•
229
XXXII.
Absolute Values for State and County Estimates
XXXIII.
..................................
230
Beta Values for Estimates for State and Counties......................... ...........
231
CHAPTER I THE PROBLEM AND PROCEDURE The prediction of enrollment.
The prediction of enroll
ment is a basic factor in educational planning.
Predictions
are not necessarily forecasts— they can be estimates of pre sent enrollment under varying degrees of educational opportunity.
Many of the early elementary school surveys
were estimates of the number that would attend if schools were available.
Legislation compelling attendance plus in
creased opportunity has made the school-age population the most important factor to be determined in estimating attendance below the college level. Compulsory attendance laws affect college-level attendance only indirectly.
The prediction of college-level
attendance still depends upon more complex influences.
The
variables that affect college-level attendance have increased rather than diminished while the prediction of elementary and secondary education has become somewhat stabilized.
The
college-age population may be numerically the same in two communitiest but ten students may attend college from one community for every student who attends from the other. College communities that wish to provide additional college-level opportunity are thus faced with the problem earlier studies sought to solve for the elementary and
secondary levels
r,How many students would attend if facil
ities were available in the community?" Some current estimates and many national predictions are based upon a projection of past high school or college attendance*
Bunn emphasized present dissatisfaction with
that method of prediction: • • . Recent experience has created the impression that estimates now in use need reappraisal , especially since a number of predictions seem to have been high.l There is increasing evidence that a population study is necessary to determine and objectively measure the dif ferentials that influence college-level attendance in a community.
Residence, sex, race, nativity, occupation, and
mean educational level are characteristics of the population that are popularly suggested as differentials,
Deutsch,
Douglass, and Strayer stated: . . . JL population study includes the number of per sons, their origin, distribution, age, characteristics and vitality. 2
1 John W. Bunn, "Reappraisal of Enrollment Trends and Implications," Current Trends in Higher Education, 1948, Part II. Department of Higher Education. Washington, D. C.: National Education of the United States, June, 1948, p. 39» 2 Monroe E. Deutsch, Aubrey A. Douglass, and George D. Strayer, A Report of a Survey of the Needs of California in Higher Education. The Regents of the University of California and the State Board of Education, March 1, 1948, p. 52.
Many previous studies suggested the relations of charac teristics of the population to college-level attendance but objective data were difficult to obtain to measure the in fluence*
This study attempted to find a method of predicting
college-level enrollment from selected characteristics of the population. Statement of the problem.
The purpose of this study
was to devise a method for predicting potential college-level attendance in a community. Answers were sought to the following general questions: 1.
What factors have previous investigators considered ci
influential in determining college-level attenance in the nation? 2.
What assumptions are basic to the prediction of
college-level attendance? 3.
What is the value of the social-economic classifi
cation of the labor force in predicting attendance? 4.
What data are available to define and measure the
extent to which education opportunity affects attendance? The practical purpose of this study was to offer a com parative index of the degree to which a community offers educational opportunity at the college, level; to enable com parisons to be made between communities with diverse populations and to predict the potential population that could be expected under certain defined degrees of educational opportunity.
Answers were therefore sought to the following specific questions: 1*
Can a formula be devised to estimate national
college-level attendance from selected characteristics of the population? 2.
Will that formula yield reasonably accurate pre
dictions when applied to data for previous years? 3.
Will the selected formula yield reasonably accu
rate predictions of attendance when applied to states? 4.
How will such a formula have to be modified to
predict the potential attendance in a college community under defined degrees of educational opportunity? Importance of the study.
Many communities are
interested in the degree to which they are providing the type of education that attracts the maximum number of stu dents.
Some cities and college communities wish to estimate
the number of students who would attend college-type insti tutions if such were established.
A comparative measure of
potential attendance is needed as a guide to educational planning. The importance.of estimates and forecasts was attested by the United States Office of Education: Great interest has been shown? both by institutions of higher education and by large numbers of interested citi zens? in the probable future trends of enrollment. The institutions are concerned about the practicability of
5 expanding their facilities on a permanent basis. Parents are concerned about the opportunity for their younger children to enter college in the years that lie ahead. The members of the staff of the divisions of higher education have been besieged with requests for prediction of future trends in college enrollment. . . .3 A report of Conference Group F of the Third Annual National Conference on Higher Education^" also emphasized the importance of predictions of enrollment. Accurate forecasts
©f college and university enroll
ment are vital to college administrators.
Budgets, expan
sion of physical facilities, hiring of faculty, and other necessary long-range planning depend upon the number of students who seek admission to college. An objective estimate of the number who would cur rently attend if offered certain defined degrees of oppor tunity is basic to present and future planning. Definitions of the terms used.
De jure population:
The de jure population was defined as those persons claiming a given area as their usual place of residence.
The term
"population,*1 unless qualified, referred to the de jure population.
3 John W. Studebaker, U. S. Commissioner of Education, Annual Report of the Federal Security Agency* 1947? Section 2, Office of Education. Washington, D. C.: United States Government Printing Office, 1948, p. 207. 4 Bunn, op. cit., pp. 39-45.
De facto populations
The de facto population
com
prised those persons physically present in an area or po litical sub-division. College-age populations
The term r,college-age popu
lation11 referred to the de jure population, ages 18 to 24 inclusive. College-level attendances
College-level attendance
was arbitrarily defined to mean the de jure population in the age group 18 to 24 who were attending any regular school or college during the month of March of any calendar year.
The
college may have been remote from the place of residence. College-communitys
The term college-community re
ferred to a contiguous area with a de jure population of fifteen thousand or more residing within fifty miles of the center of population and not separated from that center by physical or political barriers. Potential attendance.
Potential attendance was the
attendance expected if defined, degrees of opportunity were available. Limitations of the study.
The prediction of popula
tion changes was not included in the study. sions were considered unpredictable.
Wars and depres
No attempt was made to
discuss the historical development of higher education or the basic issues and factors that influence attendance at individual colleges.
The study was limited to a search for* 1.
Influences and factors that were useful in predict
ing attendance* 2.
4 method of ascertaining the influence of certain
characteristics of the population on attendance* 3*
4 formula that would afford a comparative index
of potential enrollment* Procedure of the study*
The historical method was
used in collecting data from the literature in the field, appraising methods used in former predictions, and ascertain ing what factors previous investigators considered influen tial in determining attendance. The literature consisted of predictions of attendance, surveys, research studies, and census data. Pearson product-moment correlation, Ezekiel's
method
of determining value for a non-quantitative independent fac tor, and other statistical techniques were used to evaluate and weight the factors selected for use in prediction.
The
detailed procedure followed in connection with each aspect of the problem was discussed as the need for explanation developed•
5 Mordecal Ezekiel, Methods of Correlation 4nalvsis% Second ed. (New York: John Wiley and Sons, Inc*, 1941), pp. 302-1 1 *
Organization of the study.
Chapter I stated the
problem and its importance, defined certain terms used* presented the scope and limitations of the study, and outlined the method of procedure. Chapter II presented a brief review of the literature in the field and sources of data, and commented on the de gree to which previous studies had defined the problem. Chapter III considered the sources of college-level 1/ attendance and appraised their relevance, limitations, and respective values in terms of prediction. Chapter IV considered the extent to which the social ly economic classification of the labor force reflected factors influencing attendance. Chapter V was an appraisal and determination of tech- ' niques for the estimation of the prediction of attendance.
^
Chapter VI was concerned with the application of the selected techniques to data for the United States and each state• Chapter VII appraised the problem of prediction for a single community. Chapter VIII summarized the study. ^
t/
CHAPTER II
'
REVIEW OF THE DATA AND LITERATURE PERTAINING TO COLLEGEi-LEVEL ATTENDANCE STUDIES RELATING TO PREDICTIONS OF COLLEGE-LEVEL ATTENDANCE Extent of the literature.
The literature pertaining
to attendance is so diverse that a complete study could be devoted to its review.
The entire history of higher educa
tion and all literature dealing with demography could be related in some way to college-level attendance.
Since no
historical discussion of attendance was attempted, and be cause the prediction of changes in the population was outside the scope of the study, consideration was limited to a com prehensive review of data and representative studies that suggested factors influencing attendance or techniques useful in prediction.
The literature was divided into three arbi
trary classifications:
studies relating to predictions of
college-level attendance, government publications, and sources of statistical data. The changing concepts of higher education.
Any
history of education, such as the one by Knight,^ will re veal the extent to which the definition of higher education
1 Edgar W. Knight, Twenty Centuries of Education (Boston: Ginn and Company, 1940), 622 pp.
10 has changed.
The various curriculum changes that help
define higher education were stressed by Butts,2 who pre sented the current controversies in higher education.
Cur
rent aspects of the attempt to define higher education were o
a
discussed by Fine,-3 by the Harvard Committee,
and by re
ports on the National Conferences on Higher Education edited by McDonald^ and by McDonald and McCaskill.^
The changing
concept of what constitutes higher education made it neces sary to define college-level attendance in terms of attend ance ^n-^terms— e^-a^tendanee at certain age levels. Types of predictions.
Previous studies dealing
exclusively with actual or potential attendance were rare. Forecasts of future attendance, however, were more numerous
2 R. Freeman Butts, The College Charts its Course. First ed. (New York: McGraw-Hill Book Company, Inc., 1939)> 464 pp. 3 Benjamin Fine, Democratic Education (New York: Thomas Y. Crowell Company, 1 9 4 5 ) , 2 ^ 1 pp. 4 Harvard Committee, General Education in a Free Society (Cambridge, Massachusetts: Harvard University Press, 1946), 267 pp. 5 Ralph W. McDonald, editor, Current Trends in Higher Education. Department of Higher Education (Washington, D. C.: National Education Association of the United States, 1947), 277 PP. 6 Ralph W. McDonald, and James L. McCaskill, editors, Current Trends in Higher Education. 1948. Department of Higher Education (Washington, D. C.: National Education Association of the United States, June, 1948), 199 PP.
11 and offered useful data.
The forecasts were chiefly pre
dictions included in school surveys, estimates of enrollment for individual colleges, and prophecies of national or state enrollment in hooks and periodicals. Forecasts were included covering a period from 1916 to date, and were selected as representative of predictions in the decade, or as suggesting factors or techniques not duplicated in other studies.
An extensive survey of the
studies selected was considered profitable to define the status of prediction. Predictions in school surveys.
One of the earlier and
most concrete attempts to survey the factors which condition higher education was made by Capen and Stevens? in 1916 as part of a survey of the University of Nevada.
This survey
was unique in that a single public institution, the University of Nevada, offered the only opportunity for collegiate educa tion in that state.
Capen and Stevens considered the propor
tion of rural to urban population, the racial composition of the population, the occupational character of the population, the age distribution, and the ratio of males to females in
7 Samuel Paul Capen, and Edwin B. Stevens, Report of a Survey of the University of Nevada. Bureau of Education, Bulletin 1917, No. 19. Washington, D. C.s United States Government Printing Office, 191?> 184 pp.
/
12 the study.
The summary, and the actual prediction of enroll
ment stated that future enrollment 11to he fairly estimated, therefore, must be viewed against the background of the
8
secondary schools.11
The prediction concluded:
In reports made on other school systems of education the Bureau of Education has indicated by extending up ward the enrollment curves the number that might be expected in schools and colleges at various future periods. While of course an accurate forecast of enroll ment cannot thus be easily obtained, undoubtedly the general tendency is by this means vividly illustrated. It will be noted that the actual gain in secondary en rollment in the last two years has been considerably greater than the number indicated by the projected curve for this period. The hypothetical enrollment figure for 192?, therefore, is probably a very conserva tive prophecy.9 This survey used a technique or method of prediction that has remained popular despite its inadequacy.
The enrollment
of the University of Nevada was estimated at 1,750 for 192J. The University of Maine completed a survey of the need for higher education in Maine in 1929 which included 11a con sideration of the student load, present and future.11^
The
scope of the study is illustrated by the following excerpts: First, a study was made of student productivity in
8 Ibid.. p. 49. 9 L o c . cit. 10 H. S. Boardman, and 0. S. Lutes, Survey of Higher Education in Maine, b1 the University of Maine, in Coopera tion with Bates. Bowdoin and Colby Colleges (Under the direction of Teachers College, Columbia University, New York), p. 30.
13 relationship to the population of the state, including comparisons with the rest of the country in this regard. Second, the location of the four colleges with regard to each other and the center of the population was investi gated, and a map was prepared . . . to show the over lapping of the territory served by each college. Third, certain facts were collected relative to the existing facilities in higher education for the two sexes, in cluding the college and normal schools. Lastly, an attempt was made to predict the probable demand for higher education in Maine for the next twenty years
2I930 to 19507.11 The above quotation indicated that a study was con ducted relative to the factors of student productivity, con tiguity to college, and facilities for higher education. Additional factors also studied, but not mentioned in the above quotation, were the state as an economic organism, the need of the state for graduates of certain selected types of professional training, and the ability of the state to sup port higher education.
Those studies were apparently used
only for evaluation, since the following assumption was used as the basis for the prediction of enrollment: An attempt has been made to predict the probable stu dent load the Maine institutions may be expected to carry for the next 20 years, assuming that future growth will continue at the average rate of the last 20 years. This assumption is naturally open to question since the introduction of a new factor into the situation might at any time change the current of growth in either the secondary or the college population of the State, and thus upset the predictions made. Such new factors cannot be foreseen in advance, however, and policies and plans must be based on the normal expectancy if educational
^
Ibid.« et passim, pp. 30-47.
14 programs are to be intelligently planned for a period of years. Hence the desirability of making such pre dictions, even though subject to considerable fluctua tion as caused by time and circumstance. 12 The technique used in prediction was based on past attendance with an index year as a base: In the tables prepared in connection with this study index numbers were computed for each time series with the year 1913-14 as a base, since this year seems to have been a normal and average year in many respects. The actual difference in the index numbers of successive years were found, and the geometric mean of these dif ferences determined. This mean, in terms of the base year, was taken as the average per cent of change per two-year interval, and the predictions were calculated upon that per cent of change. 13 The extent to which predictions were inaccurate was indicated by a comparison of the estimates made for 1940. College registration for the United States was predicted as 918,990^4’ for 1939-40.
The registration as reported by the
United States Office of Education was 1,494,203•
The pre
dicted registration at the University of Maine for 1939-40 was 1 ,7 0 1 , ^ while the actual registration reported was 2 ,7 0 6 . The significance of the survey is the number of fac tors considered and the stability of the population of the
1^ Loc. cit. 13 Ibid.. p. 30 1^ Ibid.. et passim, pp. 30-47. 15 Loc. cit.
1? state where the survey was made. than many other states.
Maine has changed less
Despite this advantage, the pre
diction of enrollment did not yield a valid estimate. Under the direction of George D. Strayer-^ a survey was made of public education in the State of Yfashington in 1945.
The forecast placed the number of children in the
schools of Washington in i960 at 53 per cent above current enrollment (194-5)# Among the items considered in evaluating the task of higher education in Yfashington were the following pertinent factors: 1.
Population growth.
2.
Age groups in the population.
3#
Demand for higher education
in the United States.
4.
Demand for higher education
in Washington.
5#
Relation of the distribution of population and
college attendance. 6 . Distribution of college enrollment in Washington. 7# ■ 8. 9#
Basic industries. Professional preparation. The labor force.
16 George D. Strayer, "Report of a Survey of Public Education in the State of Washington," Public Education in Washington, Submitted to Governor Mon C. Wallgren September 5> 1946, 664 pp.
16 The report indicated a recognition of the influence of many factors besides high school and college enrollment in determining college-level enrollment.
No objective
method for measuring those factors was suggested. The State Legislature of California authorized a sur vey of the needs of higher education by Assembly Bill No. 2273 i*1 1947*
A committee composed of Monroe E. Deutsch,
Aubrey A. Douglass, and George D. Strayer**-? completed the report March 7> 1947. The survey included an estimate of future enrollment, - and represented the most recent forecast for California. Excerpts from that study illustrate some of the factors con sidered pertinent: The needs of California for facilities in higher edu cation must be based upon present and future college and university attendance. The estimates presented in this Report take account of the distribution of facilities for higher education, the curricular offerings of the various types of institutions, the general level of education, and the past record and habits of college attendance in the State of California. Fundamental to all of the esti mates of need for facilities for higher education is the prediction of the State*s population. A population study includes the number of persons, their origin, distribu tion, age, characteristics, and vitality. The number of college-age youth who will attend school must be estimated on the basis of past attendance. The
17 Monroe E. Deutsch, Aubrey A. Douglass, and George D. Strayer, A Report of a Survey of the Needs- of California in Higher Education. The Regents of the University of Cali fornia and the State Board of Education, March 1, 1948, 132 pp.
17 published surveys of the United States Office of Educa tion have analyzed attendance in terms of the 18 to 21 year age group. California's past attendance shows that from 1931 to 19^2 over twenty per cent of the college-age groups were enrolled in institutions of higher education. Just prior to World War II a quarter of the college-age youth were in attendance in college or. university. What percentage of youth ought to be' attending college or. university? No arbitrary or catagorical answer can be given. It is generally assumed by educators that the years ahead will probably see a larger percentage of youth secur ing higher education. This opinion is based-upon such factors as the steady rise in college attendance between the two great w a r s , the provision of higher education in local institutions, notably the junior colleges, a greater variety of burricular offerings, the general acceptance of the value of higher education, and the subsidizing of worthy students by the State or Nation. An estimate of the future population, of the state was made.
The committee then divided the state into ten areas
and predicted the college-level enrollment for each area. The technique apparently consisted of a nominal evaluation of the relative effect of all factors listed and the general assump^ tion that enrollment would increase. Predictions for individual colleges.
The University
of Minnesota surveyed its prospective growth for the years 1920 to 19^5 in a report prepared by West and K o o s . ^
The
18 Ibid.. pp. 52, 57-58 ^ Rodney M. West, and L. V. K o o s , "I. The Growth of the University in the Next Quarter Century, ”1 The Bulletin of the University of Minnesota. Vol. XXIII, 25:^9-50, June 21, 1920. Minneapolis, Minnesota: The University of Minnesota, 1920, 50 pp.
18 committee outlined ,,:some of the factors which have in the past and will in the future influence the increase in the student body. " 20 The authors classified the factors as ex ternal and internal: External, such as: 1. Growth in state population. 2. Development of Secondary Education in its relation to freshman enrollment. 3. Development of other collegiate institutions in the state; and Internal, such as: 1. Modification of curricula. 2. Establishment of new colleges. 3 . Better articulation with the state school system, etc. 21 In commenting on the relative strength of the factors listed, the committee added: The state population as a limiting factor in the growth of the university is and, for a considerable number of years, will continue to be negligible . . . The factors of greatest importance are the enrollment in secondary schools, the proportion of graduates to enrollments in these schools, and the relation between the number of these graduates and the number entering institutions of collegiate rank. 22 The committee made the further assumption that: . . . all forces apparently operative at the present time and during the last thirty years as concerns the growth of secondary education, the increase in the number of graduates, and the relationship between the number of graduates and the number of university freshmen, will con tinue to be consistently operative during the next twenty
20 Ibid., p. 59. 2 ^ Doc. cit. 22 Loc. cit.
19 years.23 From the freshmen enrollment thus predicted, they pro ceded, with certain assumptions, to predict undergraduate en rollment.
The influence of the Minnesota survey was reflect
ed in a recent estimate of enrollment for the University of California by Marchus2lf where an adaptation of the same tech niques was utilized. ¥hile the Minnesota study considered many factors in fluencing enrollment, the basis finally selected was a pro jection of the relation between the secondary schools of the* state and freshman enrollment in the University over a t h i r t y year period.
The assumption that the relationship would be
consistently operative for the next twenty years was questionab le. The survey made of the University of Chicago in 1933 by Beeves, Miller, and
Russell2 ^
presented a prediction of
future enrollment trends for a single privately-controlled institution.
^
Comparable statistics were available.
The
loc. cit.
Floyd Irvin Marchus, “Forecasting University En rollment.“ Unpublished Doctor!s dissertation, The University of California, Berkeley, 19^7, 1^2 pp. Floyd ¥. Reeves, Ernest C. Miller, and John Dale Russell, ”The University of Chicago Survey, 11 Trends in Univer sity Growth. Vol. I. Chicago: University of Chicago Press, 1933, 21+2 pp.
20 committee prepared charts and curves of growth or decay that showed the changes in enrollment by quarters , yearly enroll ment at each level, the trend in graduate school enrollment, enrollment by sex, and other factors.
They concluded:
One of the common uses of a study of trends is for the purpose of predicting the future. The charts that have been presented in this study of enrollment trends do not afford a satisfactory basis for prediction. The curves themselves are, for the most part, so irregular that it would not be possible to project them accurately into.the future as the basis of prediction,^® The enumeration of factors that affected enrollment were of interest, even though no prediction was made: Furthermore, there are numerous factors, both within and without the institution, which affect the enrollment in any one of the divisions of the university, and which cannot be predicted from a study of previous trends. As examples of factors within the institution may be cited: (1 ) changes in admission requirements, (2 ) changes in requirements for degrees, (3 ) changes in tuition fees, (^) the discontinuance or establishment of entire units of the university, (5 ) changes in emphasis on the publi city program, and (6 ) increasing eminence of faculty mem bers in certain fields. As examples of outside forces which affect enrollments may be mentioned: (1 ) general economic conditions, (2 ) establishment, growth, or decline of other institutions in the territory, (3 ) demand and supply in vocations for which the university prepares, and (b) number of high school graduates. Wo study has ever been made to show the precise effect of factors such as those mentioned above, either singly or conjointly. Such a study would demand a larger body of data than has been gathered in this survey.^7 The Chicago study recognized the extent to which
2^ Ibid. , P* *+3 • 27 Ibid. , p. bb.
/ '
21 enrollment was affected by curriculum, cost of education, the economic environment, the demand for graduates in the professions, entrance requirements, and the number of graduates from high school who met entrance requirements. One of the most recent forecasts of attendance was made by M a r c h u s . ^
The study predicted attendance for the
United States, the State of California, and the University of California for the period 19?0 to i9 6 0 .
Marchus analyzed
eight social and economic factorsi 1.
The median number of years of school completed by the total population over 2 5 years of age.
2.
The number of high school graduates per 10,000 of total population.
3.
The per capita public expenditure spent for higher education in each state.
4.
The per capita wealth of each state for the year 1937*
5.
The per capita income of each state.
6.
The number of professional workers per 1,000 of total population in each state.
7.
The ratio of the number of women to men enrolled in institutions of higher education in each state.
8.
The per capita savings of each
state
The relationship of these factors to higher education enrollment was objectively expressed in terms of Pearson
28 Marchus, Loc. cit. 29 Ibid.. p. 10.
22 product-moment coefficients of correlation.
Marchus1 evalu
ation follows: The relationship found between the number enrolled in the institutions of higher education and the median number of years of schooling completed by the total population over 25 years of age (r * 0 .8 3 3 ) k&s im portant implications in the anticipation of future en rollments. It indicates that the enrollments of higher education will continue to increase in the future, and it is highly probable that the number of years of school completed by the population over 25 years of age will continue to increase. . . . The relationship between the number of high school graduates per 1 0 ,0 0 0 of total population and the develop ment of higher education is sufficiently high (r = 0 .6 6 5 ) to lend support to a technique for anticipating enroll ments in institutions of higher education based upon high school graduates or high school seniors. The number of students in institutions of higher edu cation is related to per capita public expenditures for the operation of universities and colleges (r = Q.61 3 ). While per capita public expenditures for higher education are not employed in the present study as a basis for forecasting enrollments, they do indicate increased en rollments. It is highly probable, in view of present trends, that expenditures for the universities, colleges, and professional schools will increase. The five remaining factors have a low coefficient of correlation with higher education enrollments. . . .3 0 Despite the relationship found, the number of high school graduates was the factor used in prediction. Two types of estimates were made.
The first was
based on an analysis of the growth trends of the five year aggregate of high school graduates in relation to survival
3° Ibid.. pp. 17-18
trends in all levels of education, and the second was derived from an analysis of the growth trends of the enroll ments of higher education in relation to the aggregate of high school graduates from 1890 to 1940*
Another forecast
was then made on the basis of the rate of growth of enroll ment compared with two population factors s and the age group 18 to 21.
total population,
The final forecast for the
United States of 1,768,000 for 1950 and 2,138,000 for i960 was an average of the other estimates. The study offered reason to believe that social and economic factors are closely related to college-level attendance.
The methods and techniques used were adaptations
of techniques used by other investigators.
Basing a pre
diction on an average of two estimates revealed indecision as to which estimate was valid. Predictions and forecasts of national enrollment. Many current predictions and forecasts of enrollment have been published in periodicals or other publications.
Kelly^1
made a prediction in 1946> for example, which included as important assumptions; 1.
The widespread esteem in which education is held.
3^ Fred J. Kelly, “College Population Trends, 11 Higher Education, Vol. XI, 18:1-5, May 15, 19^6.
24 2*
Our dependence upon higher education to per petrate our complex social system,
3*
The growing influence of the masses in determin ing the economic policies of our society,
4,
The trend of high school attendance.
The influence of some of those factors must certainly he considered in forecasting attendance. Hungate32
also discussed enrollment in connection
with the problem of financing higher education.
Two im
portant assumptions were: (1) That enrollments in the near future will increase as in the past. . . . (2) That enrollments in the future will be more largely composed of full-time students. 33 A method of prediction was also assumed: It is reasonable to suppose that the growth in en rollment will continue until opportunities of those qualified are fully provided. If for purposes of esti mate it is assumed that the growth will tend to reach a limit, under present conditions, when approximately three out of ten young people in the United States are in college, and that the rate of growth experienced during the first forty years of this century will con tinue in the near future, the equation (for method see Frederick C. Mills, Statistical Methods, pp. 6?5 ff*3 i
1 0 0 .0 0 0 .0 0 0 = 35.40 ♦ 6 2 0 .1 8 (.7211X )
y
empirically arrived at, may serve as a basis for extra polation of enrollment in future years.34
32 Thad Lev/is Hungate, Financing the Future of Higher Education (Hew Yorks Bureau of Publication, Teachers Col lege, Columbia University, 1946), 310 pp. 33 Ibid.,
pp.
34 Ibid.,
p.
222-2 3 < 223.
25 The assumption that future enrollment will be more largely composed of full-time students, and that there is a predictable ceiling for future enrollment, is worthy of consideration. John Dale
Russell^?
summarized some of the more re
cent efforts to predict enrollment in an article published in 1947.
Excerpts from his summary of the factors to be
considered follow: There is a natural tendency to assume that the trends of enrollments in previous years gives an important clue to the probable future enrollments. Previous trends un doubtedly are better than a simple guess as a basis for making a prediction of the future. Nevertheless, the prediction of future trends, even with the most refined type of projection based upon previous trends, offers considerable hazards. To illustrate the hazards of such predictions I wish to refer to studies that have been published by two different students of the problem. 36 Russell here gave as an illustration the prediction made by Ronald S. Valle, Professor of Economics at the University of Minnesota, in an article entitled "Enrollment After the War," published in the Annals of the American Academy of Political and Social Science in January, 1944. Professor Vaile predicted 1,750,000 in 1948, and suggested cautiously that the total might never be reached.
The second
35 John Dale Russell, "Enrollment Trends in Higher Education," College and University, Vol. XXII, 4:413-31, July, 1947.
36 ibid.. p. 413
26 illustration was the estimate already cited by T. L. Hungate, Comptroller of Teachers College, Columbia University, in advancing the future of higher education.
Russell called
attention to the fact that the actual enrollment for 1946 was approximately the same as the total that Hungate pro phesied would not be reached until 19&0 , and mentioned the factors to be considered in predicting future enrollments. He discussed the factor of veteran enrollment and its im-* plications and continued! A second factor affecting future enrollment trends is the increasing number of high school graduates. . . . The third factor affecting enrollment trends is the general tendency that is developing in our society to look upon some college experience as a part of the necessary education for young people. . . .3 7 Russell then remarked on the trend in enrollments at the secondary level, and stated that a similar development in the next two or three decades in higher education was no more impossible or improbable than the actual development in secondary enrollment would have been considered back in 1910. He again commented on the marked upswing in college enrollments after the end of World War I, and stated that it had occurred after every major war in this country during the last century.
He also said!
37 ibid.. p. 419
"We are undoubtedly in the
27 beginning of a period which will see a great democrat oration on the opportunities of higher education,f,3® Russell suggested foreign students as a possible source of future increase in college enrollment.
He felt
that factors which might interfere with the trends toward increased enrollment were the trend in the birth rate, a universal military training, and economic depression.
He
pointed out, however, that during the period of severe financial depression, 1930-1934, college enrollments were affected adversely for only one year, and during all the rest of the depression total college enrollments continued. to rise.
He further stated:
It is entirely probable that, in the event of another depression, unemployment would be heaviest among young people. Unemployed young people would decide, as they have usually done, that it is better to remain in school or college than to seek a job in an overcrowded labor market. 39 Russell also mentioned the possibility that facilities would limit future enrollment, and predicted a plateau in enrollments about 1950 or 1953. *
The prediction by Dean
0. E. Partch of Rutgers University, mentioned by Russell, was based in general on two factors:
first, the rate of
increase in regular students that was occurring before the
38 Ibid.. p. 420. 39 Ibid.. p. 430.
28 war 5 and second, the number of students who would have to be educated, based on the experience and education of veterans eligible for rehabilitation by training following World War I. Bussell included the following important enumeration of factors and assumptions made by Anita Kury, member of the Statistical Section of the United States Office of Education, in a prediction of future enrollment trends in the United States for the President’s Commission on Higher Education: 1.
It is more appropriate to project attendance rates than enrollment.
2.
The trend of college attendance of women is dif ferent from that of men.
3.
There will be no significant shifts in social attitudes toward higher education, the method of financing students, the organization of higher education assistance; in other words the estimates are based on social and educational 11environments’1 which will continue to have the same trends as in the past; any ideas that one might have as to changes in such factors would result in an adjustment of the figures presented.
4.
The economic ’’environment11 will continue in the same fashion as in the past.
5.
The "past1* particularly refers to 1934 through 1942 for male college enrollees and to 1934 through 1940 for female enrollees.
6.
The veteran enrollment represents a special factor and should be treated as such for males.
7.
The Armed Service students are factors to be ignored in considering trends.
29 8.
The provisions of Public Laws 16 and 3^6 will not be applicable after about 1 9 5 6 .
9.
A straight line seems to be the curve of best fit for the past data.
10.
The "past11 consists of the years specified above for the purpose of curve fitting, since it appears that 19M+ in both cases started a new trend. It is not possible now to evaluate the implications of the figures for 19M+ in later years since it is not yet clear whether new trends are being established. It will be noted, however, that the proportion of females in colleges in 19^7 falls very close to the trend line.^ 0
Some important considerations were raised by Dewhurst^-5* in a survey of America’s needs and resources.
He pointed out
in his study that: The first step in determining the cost of organized schooling is to determine how many persons should receive it. Most children from 3 to 5 years of age could benefit greatly from pre-school education. The number who should receive it, however, depends on the home environment and nearness_to school and transportation. It has been sug gested £ National Resources Development Report. p.69* Part I, National Resources Planning Board, 19^3_/ that ,3at least half of all children between the ages of 3 and 5 inclusive should be receiving pre-school education.*1 It has been recommended above National Resources Development Report^/ that, in addition, all children go to school for ten years, that is to say from the age of 6 to 16 or until they have normally completed two years of high school; and that, further, half continue for another four years, which means that half of all 20-year olds would complete the second year of college. In the upper divisions of college, the 2 5 $? increase in enrollments
^
Ibid. , p. *+29.
1 j. Frederic Dewhurst and associates, America's Needs and Resources (New York: Twentieth-Century Fund, 19*+7 ) , §12 pp.
30 that has been recommended would be. equivalent to about 18$ of all 21 and 22 years of a g e . ^ A footnote added: . . • Another criterion of the number who should attend college is those capable of taking advanced educa tion with profit to themselves and society. A n intelli gence quotient of 110 appears to be adequate for success in college, as college standards now generally define success. According to Lewis M. Terman (The Measurement of Intelligence. Houghton Mifflin Company, New York, 1916) about 20$ of the 1 9 -2 0 year-olds have an intelligence quotient of 120 or higher. In 19*+0 there were 9*5 million persons in this age group of which 1 .5 million or 16$ were enrolled in institutions of higher education. A 2 0 $ en rollment would mean an increase of approximately 1/h- above pres ent lev eIs.^3 Dewhurst stated that he believed America would demand the best educational program that it could afford.
His fore
cast was based on the opinion that the public would continue to believe in the value of education. Goldthorpe ,l+if in his summary of nine estimates of college-level enrollment in 19^7 ? stated: Most studies of estimates of prospective enrollments have presented them as gross national figures based on varying premises. The merit of the VEFP estimates is that they are based upon the ambitions, hopes , and pro grams of the same group of institutions which presumably have studied their long-range plans and the means of
1+2 Ibid., pp. 320-21. 1+3 Ibid.. p. 321. ^ J. Harold Goldthorpe, "Estimates of Future College and University Enrollment," Higher Education. Vol. IV, lH-s 157-59, March 15, 19**8.
31 financing these plans. On the other hand, a serious limi t a t i o n of these figures is that, in the nature of the case, they do not take account of the birth and develop ment of new institutions over the coming decade. Present indications suggest that in some parts of the country there will be a substantial increase in the number of new institutions, particularly those of the junior or “commu nity” college type and technical institutes. . . . It must, however, be borne in mind that different assumptions and premises have been made by the authors of these several studies, and that the introduction of new factors in the coming decade, such as the inauguration of a broad program of Federal scholarships or the appearance of prolonged economic depression, would upset these esti mate s. The College-Age Population Study. 1947-64^6 predicted the population, ages 18 to 21, for five Pacific-Western states. Tables were appended giving probability levels of enrollment, college age 18 to 21, for each state.
To use the tables,
. . . it is necessary simply to select for a state the level which recent experience indicates is most appropri ate. For example, in California the 1930fs closed with about 27 percent of California’s college-age youth in college. On the judgment that about this percentage will continue throughout 1948, the prediction for that year would be- 140,913* ' The tables gave a definite prediction of native-born and migrant population, and columns indicated the college
Ibid.. p. 1 5 7 . 4° Alvin C. Eurich, chairman, Pacific Coast Committee of the American Council of Education, College-Age Population Study. 1947-64. Arizona. California. Nevada. Oregon. Washing ton. Series 1— Reports of Committees and Conferences— No. 29 Vol. XI; Washington D. C. r American Council on Education Studies, 1947, 22 pp. 47 Ibid.. pp. 13-15.
32 enrollment for any estimate form fifteen to thirty per cent which a reader wished to assume would best represent the pro portion of college-age youth that would attend in any given year.
The tables afforded a prediction of enrollment within
a range of fifteen per cent. The study developed important considerations concerning the prediction of the college-age population.
It also suggest
ed as variables affecting college attendance? . . . the amount and distribution of wealth, the propor tion of rural and urban populations, and the relative avail ability of higher education. . . .48 In considering the problem of "How many?11 the study stated: Evidently, the remaining unknown factor is the percent age of the college-age population that actually will attend college. . . . Past performance is less a guide than might be hoped. . . . It seems likely that, as the years go by, the percent age of actual college attendance will shift and that any single assumption for the whole period under consideration would be only temporarily useful. 9 In further considering the problem, it was said: . . . Demands are emerging to subsidize students and more nearly to equalize educational opportunity in the secondary schools; either of these factors would radically alter the pattern of college attendance.5^
48 Ibid.. p. 2. 49 Ibid., pp. 12-13. 5° Ibid., p. 25.
33 The study of college-age population was shown to be a necessary preliminary to a prediction of attendance.
The
prediction of attendance in the study cited was vague, but the prediction of population was definite. Other related literature.
The effect:of economic
changes on colleges is a vital short-term factor.
Edwards^l
contributed a study of the effect of depression on college enrollment in 1931 which predicted with some accuracy the changes that occurred during succeeding years. An excellent review of the successive changes that occurred in higher education during the depression of 1930-34 was published as 11A Report of Committee Y of the American Association of University Professors. GOVERNMENT PUBLICATIONS Biennial surveys of higher education.
A series of
Biennial Surveys of Higher education made by the United States Office of Education offered the most complete factual and statistical data available on higher education.
No purpose
51 Marcia Edwards, “The Relation of College Enrollment to Economic Depression in the United States, 1890 to 1930,” (unpublished Master*s thesis, University of Minnesota, Minneapolis, 1931)? 144 pp. 52 Malcolm Willey, Depression. Recovery and Higher Education (New Yorks McGraw-Hill Book Company, Inc., 1937)» 543 PP.
3^ would have been served by listing each survey except in a bibliography.
-
Some of the subjects considered, however, aside
from the statistical data included, were of exceptional interest. The Biennial Survey of Education in the United States for 193738^3 was an excellent example of the type of information offer ed.
Part 1 , ^ devoted to general findings and interpretations,
discussed the problem'of compiling statistics of higher educa tion, presented a historical summary, and considered socialeconomic factors that influence attendance.
Statistical data
about finances, faculty, students, and enrollment were included in Part 1,55 and summarized for'the United States and each state in Part II. 56 *?7 The Residence and Migration of College Students. 1 issued in 1926, and a companion publication by Kelly and P a t t e r s o n ^ ±n 193*+, offered invaluable information regarding 53 Henry G. Badger, Frederick J. Kelly, and John H. McUeely, Statistics of Higher Education, 1937-3&. Chapter IV, Bulletin 19*+0, No. 2, Office of Education, Biennial Survey of Education in the United States; Washington, D. C.: United States Government Printing Office, 19^+1, 377 pp. 5^ Ibid.. Part I, pp. 1-39. 55 Loc. cit. 56 Ibid.. Part II, pp. *+l-6 l. 57 George F. Zook, The Residence and Migration of Univer sity and College Students. Office of Education, Pamphlet N o . *+8. Washington, D. C.: United States Government Printing Office, 19*+1, 377 pp. 58 Frederick J. Kelly and Betty A. Patterson, Residence and Migration of College Students. Office of Education, Pamphlet Ho. k-8 . Washington, D. C.: United States Government Printing Office, 193^, 22 pp.
35 the migration of students from state to state and the in fluence of proximity on o n e fs choice of college. A bulletin published in 1935, by Kelly and McNeely,^9 gave valuable data on the effect of federal aid on enrollment. The implications of ah extension’ of public supported education to areas now largely filled by private institutions was suggest ed by E c k elberry^ in; 1932*
A review was made in 193*+ hy
Badger^l of the economic and financial outlook among institu tions of higher education for that year. ^p Kelly and Rateliffe0 *1 -presented a historical summary of the part played by privately controlled institutions in higher education. Chapter IV^3 of the biennial survey of education for 59 Fred J. Kelly and John H. McNeely, Federal Student Aid Program. Office of Education, Bulletin 1935, No. l*f. " Washington, D. C.: United States Government Printing Office. 1935, 39 pp. 60 Eckelberry, The History of the Municipal University in the United States. Office of Education, Bulletin, 1932, No. 2. Washington, D. C . : United States Government Printing Office, 1932, 213 PP. ^ Henry G. Badger, The Economic Outlook in Higher Educa tion for 193*+-35. Office of Education, Pamphlet N o . 58• Washington, D. C.s United States Government Printing Office, 193*+, 59 pp. Fred J. Kelly and Ella B. Ratcliffe, Privately Con trolled Education in the United States. Office of Education, Bulletin, 193*+, No. 12. Washington, D. C.: United States Government Printing Office, 193^, 5o pp. ^3 w, S. Deffenbaugh, Effects of the Depression upon Public Elementary and Secondary Schools and upon Colleges and Universities. Office of Education. Biennial Survey of Education in the United States« 193^-30. Vol. I; Washington, D. C.: United States Government Printing Office, 193&, 59 pp.
36 1 9 3 ^ -3 6 was especially worthy of note as a summary of the effects of depression on attendance. SOURCES OF STATISTICAL DATA The limitation of statistical data.
The problem of
obtaining statistics on higher education was complicated by the changing definition of education, and the fact that institu tions offering higher education were not compelled to report their enrollment to a central agency.
In this connection, the
United States Office of Education stated: . . . Whether or not an institution is to be regarded as a college for purposes of these statistical compilations depends upon certain arbitrarily chosen facts such as en rollment , accreditation, etc. Several fairly large groups of institutions which provide education at a level above the high school are not included in the compilations. Typi cal of these groups are private business colleges, private art schools, and schools specialized in training for certain healing cults not approved by the medical profession. ^ Commenting that ’’each institution is more or less free to go its own
w a y ,
”6 ? the Office of Education continued:
. . . It follows from this lack of uniformity that the United States Office of Education in its efforts to report statistical data for the colleges and universities works under severe limitations. Furthermore, it must rely upon the voluntary cooperation of each institution in supplying the requested data. In general, the cooperation is most
6U-
Emery M. Foster, et a l . , Statistics of Higher Education. 1933-3*+. Part I, Chapter IV, Bulletin 1935. Ibid., p. 2.
37 cordial. A few find the labor of filling out the blanks more than they are willing to give to the task. It is obvious, therefore, that statistical compilations of the Office of Education can never report data for 100 percent of the colleges and universities of the country. One biennium certain institutions will have to be ommitted and another biennium certain others. The institutions omitted will not necessarily be the same in succeeding bienniums. Furthermore, an institution may^supply some data, but not all that the blanks call for. ^ Another difficulty in terms of the comparability of data was also definedt In studying statistical tables on higher education with a view to determining trends the factor of comparability of items and of total from one biennium to another looms large. This factor is affected by (1) the number of in stitutions reporting the various items at different times, (2 ) variations in interpretation of the items in the questionnaires, and (3 ) changes made by the U. S. Office of Education in the questions asked or in the manner of editing the returns received*67 President W a l t e r s ^ of the University of Cincinnati compiles an annual report on enrollment in colleges that are on approved lists. 69 " Kerr 7 published a ten-year study of enrollments and degrees as a special report of the American Association of
^
Loc. c i t .
^
Badger, Kelly, and McNelly, op. cit., p. 3*
^ Raymond Walters, ‘’Statistics of Registration in American Universities and Colleges,” School and Society« annually in December. ^ Fred L. Kerr, ”A 10-year Study of Enrollments and Degrees,” College and University. Vol. XVI, 1*5-17, October,
19*+0 .
38 Collegiate Registrars. These data were subject to the same limitations recog nized by the United States Office of Education.
The statis
tical accuracy of the data was difficult to evaluate because of the selectivity of the sampling in addition to the dis crepancies noted. Census data.
The 19^0 Rational Census?0 was the latest
of sixteen decennial reports of population^available in 1 9 5 0 . The reports begun as a simple enumeration of inhabitants, now contain additional reports on internal migration, families, fertility, parentage, mother tongue, and other special subjects. The census offered the only complete record of school attend ance for 1930 and 19^0 , and possibly the most adequate record available for the past fifty years. Census data in regards to school attendance has limi tations, however, there is a ten year lapse between reports. There is a source of error in the possibility that individuals exaggerate their educational attainment to the enumerator. Also, attendance during any census year was taken to mean attendance at some "regular11 school between March 1 and April 1 of the census year.
A wide discrepancy could occur in the
^ Sixteenth Census of the United States s 19*+0. Bureau of the Census, "Reports on Population," b vols. and Special Reports. Washington, D. C.: United States Govern ment Printing Office.
39 interpretation of the term "regular11♦
Advantages so far
outweighed limitations however that census data were uti lized in this study. SUMMARY Limitations of the literature.
Much of the literature
on attendance dealt only with college-level attendance in colleges and universities, ignoring the fluctuations due to the encroachment of other types of post-high school education when colleges were unwilling or unable to meet the needs and demands of their contemporary culture.
It was difficult to
assess the annual fluctuation of such a factor and impossible to ignore it. The problem of complete data has always plagued re search in college-level attendance.
Colleges have not been
obliged to report their enrollment to any fact-collecting agency, and voluntary surveys have often been incomplete because of the number participating, overlapping of enroll ment, duplicate enrollment, and confusion resulting from the terminology defining attendance and enrollment. Despite the inadequacy of enrollment and attendance data, most studies utilized past high school or college en rollment or attendance, or some composite of the two, as the basis for prediction. objective data.
Few attempts were made to use other
*fO Insufficient objective data for prediction, disagree ment as to the relative factors determining attendance, and prediction based on a limited number of factors have thus characterized the literature. Contributions of the literature.
No unanimity of
opinion existed regarding the relative weight of the factors that had an influence on college-level attendance.
Social
and economic factors that appeared to limit opportunity were frequently mentioned by many studies. High school attendance and/or graduation was almost universally recognized as a valuable index of college enroll ment.
Some type of projection of trends in high school and
college enrollment was the technique most frequently used.
CHAPTER III AN EVALUATION OF SIGNIFICANT FACTORS INFLUENCING ATTENDANCE THE DISTRIBUTION AND RESIDENCE OF THE POPULATION The purpose of the chapter.
The purpose of this
chapter was to examine the extent to which factors considered significant affected attendance; and to consider the extent to which available data made them useful in prediction.
The
many factors suggested by previous investigators made nec essary a discussion of their interrelation.
The factors are
summarized as: 1.
Factors relative to the number, distribution,
age, and residence of the population. 2.
Differentials due to sex, race, nativity, and
intelligence. 3.
Variables in the social or economic environment.
The number, distribution, sex, age, race, nativity, and rural or urban residence of the population, also, ex hibited certain differentials of possible value in prediction. Distribution of the population.
The distribution of
the population is represented by urban-rural classifications to some extent; and of course by density of population.
No
reliable index was offered in the studies cited for evaluating
b2
the effect of density of population on college-level attend ance.
The problem was found to be complicated by extreme
differences in transportation. ed in highly populated areas.
Significant differences exist The very sparsely populated
and the very densely populated areas apparently.each con tributed a smaller percentage of college-level attendance in proportion to the size of the group than areas with a density of population closer to the mean of the nation. The usual measure of density of population, area divid ed by population, was a very intangible index to use.
Vast
areas of uninhabited desert or mountains may surround a relatively densely populated area.
The area of cultivable
land divided by the population gave a better index of dis tribution, despite differences due to the crops produced. Density of population was of questionable value in prediction except in incorporated cities and very sparsely populated areas. Urban and rural residence.
The median number of
school years completed (19^0) by the population over 25 years of age was 12.0 years for the urban communities, 10.7 years in rural non-farm areas, and 8.8 years in rural farm areas. Such a differential suggested a corresponding difference in previous attendance and a probable use in prediction.
All
statistics available for urban, rural non-farm and rural populations originated from data supplied by the United
^3 States Census Bureau.
The Bureau's definition of urban, rural
non-farm, and rural for 19^0 is illuminating: Urban and rural areas.— Urban population, as defined by the Bureau of the Census, is in general that residing in cities and other incorporated places having 2,500 inhabitants or more. In addition, certain densely popu lated townships or other civil divisions, not incorporated as municipalities, have been classified as urban under special rules. The remainder of the population is classi fied as rural and is subdivided*into the rura1-farm popu lation, which comprises all rural residents living on farms, without regard to occupation, and the rural-nonfarm population, which comprises the remaining rural population. The rural-urban classification has been included in the census since 1910, but the rural non-farm category was introduced in 1920. As constituted in 19*+0, the divisions mean little in terms of attendance.
Granted that differences in the mean
educational level completed did exist in the dichotomy used, these differences can be ascribed to occupation or education al opportunity instead of rural-urban residence.
The urban
classification did not include the fringes of the great cities or metropolitan districts which are far more urban than rural. The rural farm classification reflects residence and not occupation.
Leon E. Truesdell, A. Ross Eckler, et a l . , Characteristics by A g e . Part I, United States Summary, Population, Vol. IV, 183 PP* Bureau of the Census, Sixteenth Census of the United States: 19^0. Washington, D. C.: United States Government Printing Office, 19^3, P. 2.
kb The rural non-farm category was criticized by Smith: The rural-nonfarm /sic7 category is a hodgepodge em bracing some of the most”widely divergent segments of the entire population. As the class was introduced in 1920 and as it persisted in 1940, it does -violence to almost every rule of logical division. . . .2 An index of the extent to which the population of an area is urban or rural is needed, however.
Smith suggested
a usable index: . . . After considerable exploratory study the author arrived at the conclusion that the best available index for use in the type of problem mentioned above is the proportion of the county*s population that is resident in incorporated centers.3 Shevky and Williams4 suggested what may be an even more satisfactory index of urbanization in terms of its use in the prediction of attendance.
They suggested:
To measure the degree of urbanization of different population groups over the range of variation encountered in the urban area, a composite index is used. The variables combined in this index— fertility, women in the labor force, and single-family dwelling units— are related to urbanization in the following manner.: The ratio of children to women, or fertility, is inversely related to urbanization; the lower the fertility, the higher the degree of urbanization. The population of women in paid occupations
York:
2 T. Lynn Smith, Population Analysis. First ed. McGraw-Hill Book Company, Inc., 194b), p. 33.*
(New
3 Ibid.. p. 3 9 . 4 Eshref Shevky and Marilyn Williams, The Social Areas of Los Angeles (Analysis and Typology) (Berkeley, California: University of California Press, 1949), 172 pp.
k-5 (women in the labor force) is directly related to urbanization. The higher the proportion of women in paid occupations, in the total population of women fourteen years old or over, the higher the urbanization. The proportion of dwellings which are single-family units is inversely related to urbanization. The lower the proportion of single-family dwelling units, the higher the urbanization.5 Such an index indicated that a comparable index might be constructed using other factors to measure the degree to which urbanization affects college-level attendance. Present classifications make urban-rural data unsatisfactory for predicting attendance in a given area.
Improvement of
transportation facilities is decreasing the effect of con tiguity and other factors may in time erase the differential. DIFFERENTIALS DUE TO SEX, RACE NATIVITY, AND INTELLIGENCE Sex as a factor in attendance.
The ratio of males
to females in the college-age population offered a differen tial of possible value in prediction.
Table I illustrates
age-differences in the college-level attendance of each sex. It is apparent that more girls than boys attended school at age 16 In 194-0. one to one.
The ratio, however, was almost
The ratio declined with advancing age, became
very marked at 21, the usual age of graduation from college,
5 Ibid.. p. 42.
46 TABLE I SCHOOL ATTENDANCE FOB PERSONS 14 TO 24 YEARS OLD, BY EMPLOYMENT STATUS, SINGLE YEARS OF AGE, AND SEX, FOR THE UNITED STATES : 19406
ATTENDING SCHOOL Employed AGE AND SEX
Total
. 5,106,138
Number
Per Cent of Total 5 .9 2 .3 3 .2 4.4 5.8 7-9 10.7 13.1 16.5 20.9 26.9 •33-2 3-2 0.6 0.8 1.3 2.1 5.0 10.4 15.7 19.7 2 5 .8
14 15 16 17 18 19 20 21 22 23 24
Male, 14 to 24 years ............... years . . . . . . . . years ............... years ............... y e a r s ........... years ............... years ............... years ............... ............... years years ............... years . . . . . . . .
. 1,122,703 . 1,067,177 945,009 734,581 488,650 2 8 1 ,1 2 3 166,081 1 2 2 ,0 3 8 8 2 ,8 3 3 55,625 40,318
299,566 25,322 34,074 4.1,481 42,706 38,429 29,989 21,762 20,162 17,271 14,965 13,405
14 15 lo 17 18 19 20 21 22 23 24
Female, 14 to 24 years ............... years ............... years ............... years ............... years . . . . . . . . years ............... years . ............. years . . ........... years ............... years ............... years ...............
. 4,813,055 . 1,101,967 . 1,055,818 952,170 729,446 4 5 1 ,4 5 5 2 2 8 ,2 5 7 128,881 . 8 0 ,2 8 8 43,023 2 4 ,7 9 8 16,952
151,880 6,904 8,721 12,282 15*272 22,460 2 3 ,8 0 0 2 0 ,2 7 7 15,790 11,119 8,513 6,742
39.8
Adapted from Table XV, Sixteenth Census of the United States: 1940. Vol. IV, "Characteristics by Age,u Part I, U. S. Summary, p. 7«
^7 and became almost a ratio of five males to two females at age 24. A comparison of employment of the two sexes while at school (Table I) and after leaving school (Table II) indi cated that the males left school to enter the labor force and the females to enter the labor force or to become house wives.
Some qualification, however, of the ages given have
been made.
Smith suggested that an error had been introduced
into the use of census figures for certain ages due to dis crepancies In the reported ages; Most obvious of all discrepancies in census data is the tendency for ages to cluster in the even years, in the numbers ending with 5* and especially in the ages ending with 0. . . .7 This error would especially affect the data for age 18 and age 24, the college-age group.
An examination of the
age and sex pyramid compiled by the United States Census Bureau for 1940 revealed that the error was more pronounced for female than for male ages.
Smith suggested a useful
technique for gauging the amount of error, but it was not used in this study.
It was believed that the accuracy of
the data used in predicting attendance trends did not justify that refinement in technique. Race and nativity as measurable factors.
7 Smith, op. cit.. p. 8 9 .
Race was
b8 even more significant as a factor in college enrollments, particularly in certain regions.
Data for 194-0 indicated
that 11 per cent of the white population twenty years of age or over had completed at least one year, and almost 5 per cent had finished four years of college; whereas, for the non-whites (over 95 per cent of whom were Negroes) only a little more than 3 P©r cent had completed at least one year in college, and less than 1.5 Pe^ cent had completed 9 a full course. Data for race indicated that social and economic environment and educational opportunity might be the factors really measured by the differential.
That cultural differ
ences due to nativity might be more influential than race and even stronger than some social and economic factors, was suggested by incomplete data for Mexican enrollment in higher education in California.
Enrollment of Negroes in
certain junior colleges from 193° to 1942 exceeded the Mexican enrollment in areas where the social and economic environment was apparently the same and educational oppor tunity was equal. Race and nativity are important in certain regions and in certain areas of cities, but their use as a pre dictable differential has been limited because of incomplete
9 Table 39, C£. cit.. p. 140.
49 TABLE II EMPLOYMENT FOR PERSONS 14 TO 24 Y E A R S •OLD• NOT ATTENDING SCHOOL, BY SINGLE YEARS OF AGE, AND SEX, FOR THE UNITED STATES: 19408
NOT ATTENDING SCHOOL Employed
14 15 16 17 18 19 20 21 22 23 24
years years years years years years years years years years years
14 15 lb 17 18 19 20 21 22 23 24
years years years years years years years years years years years
Per Cent of Total
Total
Number
Male, 14 to 2J
7 ,9 8 4 ,5 2 3 95,413 155,160 304,157 4 7 8 ,6 9 6 7 9 2 ,9 8 8 9 3 2 ,6 1 2 984,582 1 ,0 5 6 ,7 6 8 1,040,881 1,059,984 1 ,0 8 3 ,2 8 2
5,444,462 3 6 ,3 8 6 72,796 150,984 241,741 448,478 5 8 6 ,1 9 0 666,827 765,390 787,689 824,918 8 6 3 ,0 6 3
68.2 3 8 .I 46.9 49.6 50.5 5 6 .6 6 2 .9 6 7.7 72.4 75.7 77.8 79.7
Female, 14 to 24
8,423,372 85,647 144,364
3,039,079
3 6 .1 9.2
17,300 49,736 108,765 277,764 3 8 1 ,2 1 1 4 3 5 ,6 4 2 454,875 437,487 4 5 4 ,3 5 2 414,103
12.0
AGE AND SEX
8
287,760 460,351 849,555 994,194 1 ,0 8 7 ,4 9 8 1,108,567 1,139,824 1 ,1 2 5 ,1 0 5 1 ,1 4 0 ,5 0 7
Adapted from Table XV, 0£. cit,, p. 7*
17.3 2 3 .6 32.7 38.3 40.1 41.0 38.4 40.4 36.3
50 data and lack of an objective evaluation of their importance. Intelligence and college-level attendance.
Several
investigators have attempted to determine the ultimate growth of college-level attendance by assuming a limit to the num ber of persons in the population who could profit by posthigh school training.
Hungate
10
worked out a formula as a
basis for extrapolation of enrollment in future years on the assumption that three out of ten young people would be in college.
Kelly
11
assumed that high school graduation might
increase 50 per cent.
Russell
12
suggested that 80 per cent
of our young people of high school age might in a short time graduate from high school and, by inference, be eligible for post-high school training.
Dewhurst suggested:
An intelligence quotient of 110 appears to be ade quate for success in college, as college standards now define success.13 Hughes and Lancelot stated: Again, if junior colleges with both vocational and college preparatory courses were widely available and accessible without cost, judging by the experience in California, 35 per cent would complete one or two years of such courses with profit; and perhaps 13 per cent Thad Lewis Hungate, Financing the Future of Higher Education (New York: Bureau of Publications, Teachers College, Columbia University, 1946), 310 pp. Fred J. Kelly, "College Population Trends," Education. Vol. II, 18:1-5, May 15, 1946.
Higher
John Dale Russell, "Enrollment Trends in Higher Edu cation," College and University. Vol. XXII, 4:413-31* July, 1947. ■13 J. Frederic Dewhurst and Associates, America1s Needs and Resources (New York: Twentieth-Century Fund, 1947), p. 69.
51 could eventually graduate from four-year college courses.14 The Pr e s i d e n t s Commission on Higher Education re ported: 1. At least 49 per cent of our population has the mental ability to complete 14 years of schooling with a curriculum of general and vocational studies that should lead either to gainful employment or to further study at a more advanced level. 2. At least 32 per cent of our population has the mental ability to complete an advanced liberal or specialized professional education. 15 It would appear from the foregoing opinions that, unless the growth of college-level attendance is unprecedent ed, forecasters need not be concerned for the next two decades at least about the limiting action of intelligence. The upgrading of schools and courses formerly con sidered on the secondary level has extended the curriculum of the post-high school training program.
It has been sug
gested that the colleges assume responsibility for all train ing requiring more than twelve years of attendance.
Such
a program might change the level now considered adequate .for success.
Raymond M. Hughes and William H. Lancelot, Educa tion. America1s Magic (Ames, Iowa: The Iowa State College Press, 1946), p^;1 1 8 . x 5 George F. Zook, chairman, The Presid e n t s Commis sion on Higher Education, Higher Education for American Democracy. Vol. I (New York: Harper & Brothers, 1947), p.'41;,.
52 There have been, also, some suggestions that improved teaching methods and less stress on the prestige value of certain subjects might reduce the mortality in colleges and thus increase attendance. VARIABLES IN THE SOCIAL OR ECONOMIC ENVIRONMENT Educational opportunity. measured by many things:
Educational opportunity is
economic status., social status,
health, contiguity to school, the type of training offered, and even the esteem in which education is held.
^ ^
This complex ^
factor is equalized in a large area like the United States by ^ increased attendance where opportunity is available and de-
^
creased attendance in areas that offer little opportunity,
^
but in the prediction of attendance for smaller areas it
^
must be considered.1 The exact degree of opportunity is
^
difficult to measure.
For example:
one measure suggested by a
casual examination of data was the amount per capita spent on higher education.
The correlation between current receipts
per capita for higher education, 1938 to 1940, and collegelevel attendance in each state for 1940, when computed by the produet-moment method, gave a Pearson’s r of O.6 8 9 .
The
value of the correlation was reduced by a wide variation in attendance between a few states that spent almost the same amount per capita.
Opportunity can probably best be measured
by assuming that if many students go to high school or college,
53 opportunity is present.
High school or college attendance,
or graduation, has been used in many studies as an index of opportunity.
In this study, for reasons enumerated later,
attendance of the age group 16 to 17 inclusive was used for the secondary level, and educational attainment of the adult population was used as an index for the college level. Economic changes as a factor in college-level attend ance .
The effect of depression on attendance has been noted 1z by many investigators. The attempt by Marcia Edwardsxo to measure its effect with some degree of success has already been cited.
The relation of family income to college attend
ance was commented on by Tead^? in the 19*+7 Inglis Lecture as follows s On the score of the relation of family income to actual college entrance, the evidence of a number of representa tive studies is conclusive. Dr. Vannevar Bush has includ ed in his Report to the President, Science, the Endless Frontier, a convenient summarizing Appendix of the avail able data from the United States Office of Education and from private studies in Pennsylvania, Minnesota, Kentucky, and elsewhere. And it indicates that for the country as a whole about one-half of today’s high school graduates who are otherwise qualified for college entrance do not entertain the idea of going to college because of in adequate financial resources. What this means in terms
3-6 Marcia Edwards, "The Relation of College Enrollment to Economic Depression in the United States, 1890 to 1930," (unpublished Master’s thesis, University of Minnesota, Minneap olis, 1931), l1^ pp. ^ Ordway Tead, "Equalizing Educational Opportunities Beyond the Secondary School," Inglis Lecture. 19*+7 (Cambridge, Massachusetts; Harvard University Press, 19^7), 53 PP*
5^ of national failure to identify the latent intellectual talent and potentialities of our citizens is appalling to contemplate. While many of those students actually did take some type of post-high school training, perhaps shorter in dura tion, a definite limitation of attendance occurred. sion increased the stress.
Depres
Depression, like war, was consid
ered unpredictable in this study.
Its effect on attendance
varies with social trends, and can be predicted to some ex tent.
Apparently, it accelerates long-term trends.
College-
level attendance was found to be geared, apparently, to the number of employed in the labor force.
Unless students are
artificially added to the labor force by paying them a stipend for attendance, the size of the labor force determines attend ance.
That assumption will be further explored in this study. The need for higher education.
The need for higher
education has been cited as a factor in increasing collegelevel attendance.
Certainly the increased need for profes
sional training has been paralleled by increased facilities and attendance.
Modern war has consistently stimulated
college-level attendance both in America and in Europe since 1870 as attested by the upward swing of the growth curve of college-level attendance for Germany, France, England, and
^
Loc. c i t .
the United States after every major war.
The degree to which
the need for higher education remains a factor may depend, however, upon the extent to which educational institutions are willing to break away from a thousand years of tradition to meet the needs of contemporary. Occupational Status.
The part played by occupational
status in determining college-level attendance has been acknowledged by almost every investigator. Shevky and Williams noted the growth of an occupational hierarchy as a condition of urbanization, and suggested its influence in other areas: The transfer of workers from agriculture to manufacture and trade was the necessary condition of rapid urbanization throughout the last one hundred years. Shifts in the character of economic opportunity brought about by increas ing urbanization and industrialization caused changes in the regional distribution of workers. A complex occupational hierarchy developed, giving rise to differentials with ramifications in other social areas.19 One of the ramifications in other social areas might well be a profound influence on college-level attendance. Smith, in a discussion of occupational status stated:
t!Among
all of the social attributes of a given individual or group, occupation is of paramount importance.*'^ Fortunately, occupational statistics were available in
^
Shevky and Williams, o p . c i t .* p. 11.
20 Smith, o p . c i t .. p. 16M-.
56 the Sixteenth Census.
Unfortunately, only incomplete data were
available from previous censuses for purposes of comparison. It seemed conceivable that the growth of college-level attend ance since 1900 had been so closely correlated with the growth of certain occupational groups in the labor force that predic tion of one might become possible from the other.
The use of
occupational status or relative rank in the occupational hi erarchy would indicate and give value to many of the factors already noted as influencing attendance.
Sex, race, residence,
nativity and intelligence have each contributed to the rank acquired by an individual in the occupational hierarchy. Modification of the curricula.
Modification of the
curricula progresses slowly in the established colleges and universities.
Harold Benjamin has aptly said:
Occasionally the college stirs uneasily in its senile slumber and announces that it is going to embark upon a new course. Sometimes it actually makes changes in its procedures, but, because these innovations are almost as likely to be retrogressions as advances in any one case, the total picture remains about as dynamic as that of any octogenarian dozing in the sun. Once in a while an indi vidual institution, under the stimulus of a new adminis tration, rises to its feet and makes threatening gestures in the direction of reform, but college administrations wear off, like the effect of drugs, and unlike some drugs they do not commonly appear to be habit-forming in nature. Thus the institution that has lately staggered into changed ways often sinks back to its old repose under the soothing influence of a new administration.21
21
H. Freeman Butts, The College Charts Its Course. First Ed. (New York: McGraw-Hill Book Company, Inc., 1939), P* xv.
57 Modification may take place more rapidly than is im~ plied, however, by the upgrading of secondary institutions to post-high school or collegiate rank and by the adoption of courses taught in ‘’marginal1* schools into the curricula of junior colleges and technical schools.
The term “marginal1*
is used to designate institutions not accepted"as collegiate in character that offer training which usually requires high school graduation or its equivalent as a prerequisite. Changes in the curriculum are important to attendance, and some weight must be given the factor in the prediction of attendance. College student mortality.
A study made of student
mortality in 25 universities by McNeely in 1937 indicated that, • . • out of every 100 students originally registering, 62 left the universities during the M— year period without obtaining degrees. Of this latter number, however, approx imately 17 out of every 100 students either transf-erred to some other institution or returned at a later date to continue their work. The result was that *+5 out of every 100 students withdrew from the universities permanently as denoted by the percentage giving the net mortality.22 By years, McNeely found that 33*8 per cent left the university at the end of the first year, 16.7 per cent the second year, 7.7 per cent the third year, and 3.9 per cent in t**
the fourth.
f c
The study was based on students entering the
22 J. H. McNeely, College Student Mortality. Office of Education Bulletin, 1937? No. 11. Washington, D. C.: United States Government Printing Office, 1938), p* 10.
universities in 1931-32, which was certainly not a typical year; but the reasons students gave for withdrawal emphasized lower academic achievement rather than economic stress* their case for leaving the university, 1 2 A
As
per cent listed
financial difficulties, while l8.*f were dismissed for failure in work*
Some question could be raised as to the validity of
these percentages, since the cause of b$ per cent leaving the universities was listed as unknown. The causes of student mortality were beyond the scope of this study, however Tead in the 19^7 Ingles Lecture stated And, unquestionably, there is tied up with the reality of high mortality from college in the first two years the fact that for a combination of reasons the first two years of instruction have repelled rather than attracted many students. To these there seems to be little object in completing the course.^3 Although college mortality is undoubtedly a factor in total college attendance some evidence indicates that many students enroll in other types of post-high school training and minimize the effect when college-level attendance is measured as all individuals attending school in the 18 to 2b year age group. The number of junior colleges increased rapidly after 1937* and aided in minimizing student mortality.
Tead, op. c i t .. pp. 12-1^.
Ability of the state to support education.
An analy
sis of the comparative effort of the state to support educa tion was attempted by Hughes and L a n c e l o t ^ on the basis of income per child (5 to 17 inclusive) for 1937 through 1939. At that time the average income per child in the forty-eight states ranged from $673 in Mississippi to $*+,320 in New York. Although these figures are obsolete, they illustrate extreme differences in the ability of states to support education. Obviously the problem of the esteem in which education is held enters into the amount spent.
There is no real evidence, when
educational expenditures are compared with other government al cost, that any state has ever approached its maximum ability to support education.
It would seem that there is a need for
an objective measure of the extent to which each state chooses to support education. The esteem in which education is held. held in high esteem after World War I and II.
Education was Optimists, and
they prevailed among the writers after each war, believed that the public would demand more and more education.
More
critical writers remembered the HPh. D.*s are a dime a dozen11 attitude of the early depression years and the educational doldrums of 1890 to 1900.
pit
The answer as to the future esteem
Hughes and Lancelot, loc. c i t .
60 in which education is held probably depends upon the economic opportunities available to each graduating class and the de mand for semi-technical, technical, and professional train ing.
Esteem apparently is positively related to the occupa
tional status and extent of participation in the labor force of graduates. High school attendance o r 'graduation.
The number that
graduate from high school each year is certainly related to college-level attendance.
High school attendance however, is
a product of a number of factors.
Compulsory attendance laws
and.the age of the student influence high attendance to a degree that leaves it unsatisfactory as a measure of potential attendance after age 18.
The use in prediction of attendance
in the last two years of high school, which traditionally is the age group 16 to 17 inclusive, partially eliminates the effect of compulsory/ attendance and has a closer relationship to college-level attendance than attendance for the age group 1*+ to 1? inclusive. High school graduation terminates the formal education of so many students that it has not proved entirely satis factory as a statistic that could be used for prediction. Marchus2 ^ however, found a correlation of .665 between the
25 Floyd Irvin Marchus, "Forecasting University Enroll ment," (unpublished Doctor's dissertation, The University of California, Berkeley, 19*+7) ? p. 25-.
}
6l number of high school graduates per 10,000 of population and the development of higher education in the United States. relationship was significant.
The
A correlation of •580 existed
between the percentage' attending school age 16 to 17 inclusive and college-level attendance for the 18 to United States.
2b-
group in the
High school attendance and graduation were not
used as a factor in the prediction of trends in this study. Attendance ages 16 to 17 inclusive was used as a measure of the extent to which the state offered opportunity for second ary education. College attendance.
The projection of past enrollment
of college presumed that all the factors operative in the £>ast. would continue to operate to the same degree in the future.
Such an assumption is untenable.
Past college en
rollment was found, however, to be an indication of the ex tent to which facilities were available for education in the state, and gave some measure of the extent to which educational opportunity existed. SUMMARY The distribution and residence of the population. Urban and rural areas have differed in their respective con tributions to attendance.
The classification afforded by the
United States census did not adequately reflect the real
62 differences that existed.
If rural and urban differences are
used in prediction, another index of urbanization must be con structed.
The real reason for the differences in the contri
bution of rural and urban areas may be contiguity to educational institutions.
Improved transportation and more schools may
tend to erase the differential.
Density of population, alone,
is of questionable value in prediction. Differentials due to s e x , race, nativity, and intelli gence.
The college-age population is comprised of various
groups that differ significantly in sex, race, and nativity. Each of these groups also differs significantly in their re spective contribution to college-level attendance.
Race and
nativity differentials were considered of doubtful value in prediction due to incomplete data available. were of probable value.
Sex differentials
Occupational status reflected to some
extent sex differentials in attendance.
The decrease in the
percentage of females attending school beginning at age 16 was reflected by the occupational status of the sex. gence was considered as a limiting factor.
Intelli
The reservoir of
intelligent college-age students in the population offered little evidence that college-level enrollment would be limit ed by intelligence until attendance increased one hundred per cent • Variables in the social and economic environment.
College
student mortality has been high.
This is due to the cur
riculum offered, to economic difficulties, to emotional and health problems, and to other undetermined causes. Economic inequality has been a distinct barrier to college attendance.
Changes in the prosperity of the nation
affect attendance, but such changes were considered unpre dictable in this study.
Some evidence indicated, also, that
depressions may have been short-term factors that did not perceptibly alter long-range trends in attendance. Educational opportunity was deemed fundamental to college-level attendance.
Attendance of the 16 to 17 year
age group was selected as the most valuable objective index for the degree of educational opportunity offered on the secondary level.
The number of adults who had attended
college one or more years was suggested as an index available on the college level. No data was found to indicate that any state had ever attempted to provide maximum opportunity as measured by a comparison of the amount spent for education with other ex penditures.
The real ability of a state to provide education
had apparently never been tested. The relation of occupational status to other factors. Occupational status suggests a measure of the utilization of education by society.
Differences in age and sex are reflected
&*
by the ratio of participation in certain occupational groups. Race and nativity also have a bearing on the occupation of the individual and the extent to which he perseveres in an attempt to secure an education.
Rural or urban residence is
reflected in the numbers from each area who are in certain occupations.-
The total size of the labor force determines
economic changes and is reflected in attendance.
It might
also be feasible to assume that the esteem in which education is held and the extent to which facilities are provided de pend in part upon the extent to which education is rewarded by occupational status. The evaluation of factors influencing attendance in this chapter led to the selection of the relation of the labor force to college-level attendance and certain measures of educational opportunity as worthy of further analysis and investigation.
CHAPTER IV THE SOCIAL-ECONOMIC CLASSIFICATION OF THE LABOR FORCE AS AN INDEX OF COLLEGE-LEVEL ATTENDANCE THE RELATION BETWEEN EDUCATION AND THE LABOR FORCE The purpose of the chapter.
The purpose of this
chapter was to define the value of occupational status as an index of college-level attendance by indicating its relation ship to the major occupation groups as defined in the United States census. The relation of education to occupation.
The need
for occupational skill has always been a factor in the growth of education.
In primitive cultures training was provided
by members of the family or tribe.
The development of oc
cupational specialization brought apprenticeships and schools. Social values were attached to certain vocations in primitive cultures.
In general the occupations that require extensive
training have a high social value in contemporary culture. Counts1 in a study of 17,265 high school youth in 1919 found a positive relation between certain vocations followed by parents and the secondary school attendance of
1 G. S. Counts, The Selective Character of Secondary Education (Chicago: University of Chicago Press, 1922), p. 6 2 .
66 youth.
Kefauver,. Noll, and Drake2 verified the relationship
by duplicating the study in two cities in 1930.
The American
Youth Commission3 in a study of 30,000 youth in Pennsylvania in 1938 found a positive relation between economic background and school attendance. Shevky and Williams stated the relationship of educa tion and occupation clearly: Occupation, income and education may be taken as the chief indicators of position in society. This is because modern society is organized on an occupational basis, and income is roughly correlated with occupation. Education, or level of schooling, as an element of social distinc tion is a function of the increasing occupational organiza tion of society and the growing stress on professional training and skill in all walks of life. It is a matter of common observation that occupations are elevated and generally accorded honor and esteem on a scale of prestige which corresponds to their relative importance as determinants of social position. This is recognized by everyone, and influences behavior. Relations among occupations in a complex society may best be understood if occupations are conceived as posi tions within a system. Occupational structure, so con ceived, implies a hierarchy of functions. . .
2 G. N. Kefauver, W. H. Noll, and C. E. Drake, The Secondarv-school Population. National Survey of Secondary Education, Monograph *+, U. S. Office of Education Bulletin 1Z, 1231, P. 23. 3 American Youth Commission, Report on Secondary Edu cation (Washington, D. C.: American Council of Education, 1937), p. 5. ^ Eshref Shevky and Marilyn Williams, The Social Areas of Los Angeles (Analysis and Typology) (Berkeley, California: University of California Press, 19*+9) , PP* 37-38.
E d w a r d s 5 stated in the preface to his report to the
Secretary of Commerce on the social-economic classification of the labor forces The most nearly dominant single influence in a man's • life is probably his occupation. More than anything else, perhaps, a man's occupation determines his course and his contribution in life. . .6 Anderson and Davidson gave additional evidence of the extent to which it is believed that occupation affects society: The standard of living of well over 90 per cent of all families is determined by the gainful employment of one or more of its members. A man's occupation exerts a most powerful influence in assigning to him and to his imme diate family their place in society, in deciding their place of residence, and in determining the occupational status of the children when they enter employment. The work a man does to earn his livelihood stamps him with mental and physical traits characteristic of the form and level of his labor, defines his circle of friends and ac quaintances, affects the use of his leisure, influences his political affiliations, limits his interests and the attainment of his aspirations, and tends to set the bound aries of his culture. In a word, except for those few persons whose way of life and future are secured and fixed by the inheritance of great wealth, occupation is the supreme determinant of human careers.7 That occupational hierarchies or levels of societies tend to perpetuate themselves was strongly suggested by
Alba M. Edwards, Comparative Occupation Statistics for the United States. 1870 to 19h-0 . Bureau of the Census, Sixteenth Census of the United States s 19^0. Washington, D. C.s United States Government Printing Office, 19^3, 206 pp. ^ Ibid., p. x i . 7 ' H. Dewey Anderson and Percy E. Davidson, Occupational Trends in the United States (Palo Alto, California: Stanford University Press, 19*+0), p . 1.
68 Q
Anderson and Davidson in another study. The distribution of occupations in a community estab lishes the economic and cultural level.
The type and extent
of the training youth is urged and assisted to secure is also a reciprocal relationship and will correlate closely with the cultural level of the community. THE EXTENT TO WHICH OCCUPATION IS A COMMON FACTOR Distribution and residence of the population and occupation.
Density of the population leads to specialization
in occupations, and thus urbanization is characterized by a decline in agricultural pursuits and an increase in manu facturing, mechanical pursuits, and the professions. Thompson stated: . . . Man apparently never loses an opportunity to use any surplus -above mere necessity to establish more or less permanent centers where he can trade and where he can employ his fellows in specialized occupations to make things which satisfy his cravings for greater variety. . . .9 Perhaps the best single index that could be secured, aside from an actual enumeration, of the character and density of population Qf a community would be an occupational
Percy E. Davidson and H. Dewey Anderson, Occupational Mobility in an American Community (Palo Alto, California: Stanford University Press, 1937), 203 PP* 9
Warren S. Thompson, Population Problems. First ed. (New York: McGraw-Hill Book Company, Inc., 1930), p. 271*
69 inventory. Sex and occupation.
Occupational data revealed a sig
nificant difference between the number of men and women in the labor force.
The proportion has changed from a ratio
of 8 to 2 in 1870 to 7 to 3 in 19^0 . The degree to which occupation is related to education and measures the respective differences was indicated indirectly by Edwards: The proportion of female workers engaged in manual pursuits— skilled, semiskilled, and unskilled— decreased rapidly from 7 1 .8 percent in 1910 to 5*+^? percent in 19*+0 , while the proportion engaged in intellectual pursuits— professional and clerical— increased strikingly from 2 3 .1 to *+1.3 percent. During this period, smaller and smaller proportions of the female workers were becoming hand workers and larger and larger proportions of them were becoming head workers. . . .1 0 The increase in the social-economic status of women workers and an increase in the proportion of the number of women who were gainfully employed was measured in occupational data, and correlated roughly with a change in educational status and college-level attendance for women. Race and occupation.
If the labor force were classi
fied in six broad social-economic classifications in terms of the formal education required, the first three groups— professional; proprietors, managers and officials; and the
Edwards,
ojd.
c i t .. p. 18^.
70 clerical group— would be the "head11 groups and the last three groups— skilled, semi-skilled, and unskilled workers— would be the hand workers.
Edwards said:
In 19^0, U-7.2 percent of the employed white workers, as against 20.8 percent of the employed Negro workers, were in the first three main groups— the groups compris ing the "head workers." And, on the other hand, 52.8 percent of the White workers as compared with 79.2 per cent of the Negro workers were in the last three main groups— the groups comprising the hand workers. Professional workers formed only 2.6 percent of the employed Negro workers in 19^0 as compared with 7.5 percent of the white workers. . . .1 1 Colored workers were highly concentrated in the personal services and in agriculture, forestry, and fisheries.
The
percentage of Negroes engaged in recreation and amusement represented the only area where parity was present in 19^0 . The median education attainment as of 19*+0 for Negroes over 2? in the United States was 5*7 years; for native-born Whites, 8 .8 years.
Occupation reflected racial differences to
a degree roughly corresponding to educational differences. Nativity and occupation.
The relation of nativity to
occupation was not so evident today as it was in the period from 1856 to 1875 when signs in New York relating to employ ment often stated, "No Irish Need Apply!" Warner and Srole called attention to the part nativity played in occupation in the Yankee City Series by describing
11 Ibid.. p. 188
71 the occupational status of immigrant groups: . . • the occupational system in a complex economy appears as a graded series of positions, resembling in pattern a hierarchical organization. . . • The workers of the newly arrived groups started out at the very bottom of the occupational hierarchy and, through the generations, climbed out of it and moved up to jobs with higher pay and increased prestige. Each new ethnic group tended to repeat the occupational history of the pr ec ed ing ones •12 The role of intelligence in occupation.
Intelligence
was difficult to separate from training except at the extreme ends of the curve that represented the distribution of intel ligence and educational training in the population. If intelligence is defined as the ability to comprehend printed symbols, occupation is, to a degree, a measure of intelligence.
As early as 1922, R. Fryer set up occupational
13 intelligence standards based on scores made on certain tests. J Ample evidence exists that there is in our population a substantial number of individuals whose training is not adequate to enable them to compete for the place in the occu pational hierarchy that they would occupy
if a perfect posi
tive correlation existed between the potential ability to
12
W. Lloyd Warner and Leo Srole, The Social Systems of American Ethnic Groups (New Haven, Connecticut: Yale Univer sity Press, 191*?), PP. 57, 63. 13 A. T. Poffenberger, Principles of Applied Psychology (New York: D. Appleton-Century Company, I n c ., 19^-2), p . 295
72 comprehend printed symbols, and occupational status.
There
is additional evidence, beyond the scope of this study, that other phases' of intelligence might offer training possibi lities that would reflect substantial growth in occupational status.
Such areas might have been neglected by schools be
cause of the lingering halo and the clerical mantle retained by higher education from the strong control exercised by the church in the middle ages.
The halo by transference might
have fixed the idea that education, as represented by our pres ent traditional curriculum and methods, was an end in itself. Suffice it to say, however, that occupation was found related to intelligence, and the correlation between occupa tion and intelligence is a rough measure of level of schooling. Occupation and the need for higher education.
The
present relation between the professions and higher education has been exemplified by increasing requirements for entrance to the professions.
Edwards
lU
suggested that the trend toward
specialization was increasing in the upper classes and de clining in the lower three classes of the labor force.
The
relation, too, between the professions and education might be spurious in the sense that many of the requirements were seiiective only and had little or no relation to occupational
Edwards, oja. c i t .. p. 186.
73 aptitude or competency. Industry, also has used education as a selective device to an extent difficult to justify.
The need for higher edu
cation as a ' prerequisite for attainment of military rank in the Army has impressed industry and potential students alike and perhaps accounts for part of the current demand for higher education.1 ^ Our concern was with the relation of occupation to a need for higher education as expressed by current demand. Securing a representative place in the hierarchy of occupa tions depended upon educational training to a substantial degree and thus reflected the need for higher education. Modification of the curriculum and occupations.
The
history of higher education, since the establishment of the first medical school in the United States at the University of Philadelphia in 1765, presented a picture of reluctant and painful concessions made by the leaders of higher education to occupational needs. The status of the relation between the curriculum and occupations was best stated by Anderson and Davidson: . . . Educators, while accepting increasing responsi bility for vocational guidance and training, are still prone to approach the problems involved in terms of their
John Dale Russell, “Enrollment Trends in Higher Education," College and University, Vol. XXII, b:b13-3 1 , July, 19^7.
7*+ formal academic training, and with relatively little knowledge of the vocational needs of society or the conditions at work in the labor market. The result is frequently a vague and diffused training in the arts and sciences, which may have value as occupational-training material, but largely unknown direct influence on oc cupational competency. Or, when formal vocational train ing does become specific, as in the case of typing and bookkeeping, it is planned frequently without any regard to the needs of industry, and often, by flooding the labor market in these relatively low-circumstanced call ings, causes a reduction in real wages and chaow in the ranks of labor which has been weakened by the influx of many new undisciplined and unorganized workers.1® The urgent need for increased efficiency in occupa tional training received impetus during World War II; but the demand for higher education after the War entrenched the ad vocates of the traditional by removing pressures to reform. "If sales are excellent (enrollment), why change the product! 11 The "good old days" have been so closely associated with the "good old curriculum" in wistful thinking, according to some investigators, that emotional stresses occur in educational circles when curriculum changes are mentioned. Despite the desire to make traditional subjects "re quired" and the reluctance to give status to any new subject, changes in the curriculum do occur. rapid but attrition has been slow.
Addition has been fairly A "required" subject
appears to cling to the curriculum indefinitely. Municipal colleges and universities and junior colleges
Anderson and Davidson, op. cit., pp. 6 3 -6*+.
and technical institutions
have led in the curriculum
changes made by recognized schools. "Marginal" institutions, that is, private schools which offered post-high school training, have often pioneered cer tain subjects or areas, and adoption by recognized institu tions has followed.
Upgrading of institutions has offered an
other manner in which the curriculum was modified. The existence of marginal institutions and private education has appeared to aid the modification of the curri culum in response to the needs of our culture.
No objective
prediction was made as to the degree to which the curriculum will adapt itself to occupational needs in the future.
Edu
cators may cling to tradition as closely as the Chinese held to the memorization of certain classics as a standard of edu cational attainment.
It was the assumption in this study,
however, that occupational needs would be the major factor in curriculum changes, and that new schools would arise if the established institutions did not meet the need for training. ~~Economic changes and occupations.
Economic changes
are reflected in the size and character of the labor force.
17
R. H. Eckelberry, The History of the Municipal University in the United States« Office of Education, Bulletin, 1932, No. 2, Washington, D. C*: United States Government Printing Office, 1932, 213 PP»
76 Marcia Edwards*^ believed depressions were reflected by reductions in enrollment in higher education with a lag of about two years.
Edwards made her study in 1930 and found
her conclusions substantially verified by subsequent changes in enrollment during 1931-3^.
Probably no other factors men
tioned were so closely correlated as occupational changes and economic changes. Each depression is a unique historical event; but pre vious depressions and prosperity eras have been closely cor related with decreases and increases respectively in collegelevel enrollment, Educational opportunity and occupation.
Educational
opportunity is related to social trends, the median level of educational attainment in the community, the average income in the community, and other complex factors. Anderson and l6 Davidson suggested that it is closely correlated with family income.
Many factors, such as unionism or professional
organization and tradition, affect income.
No definite rel
ative weight in comparison with other factors could be assigned
^ Marcia Edwards, ’’The Relation of College Enrollment to Economic Depression in the United States, 1890 to 1930,“ (unpublished Master's thesis, University of Minnesota, Minneapolis, 193D 5 1 ^ PP*
16
Anderson and Davidson, loc. c i t .
77 to occupation as a measure of educational opportunity; but the level of occupation strongly influences the character of the community, community income, and the median level of schooling, and creates an "educational climate" which fosters educational opportunity. Despite an obvious relationship, changes in the economic structure, interstate migration, reluctance on the part of educators to change established patterns of education, and opposition on the part of some to support any type of educa tion, educational opportunity was found to differ so widely in the *+8 states that the occupational hierarchy was not advanced as a gauge of educational opportunity.
Certain
states and communities have at times maintained their level of occupational efficiency and culture by importing the educational product of other states or communities. EXTENT AND LIMITATIONS OF SOCIAL-ECONOMIC DATA The United States Census classification of occupations. Occupation has been suggested as a measure of all the factors except educational opportunity that certain investigators have believed influenced attendance.
No assumption was
made, however, that the relative weight of each factor was accurately reflected by occupational data.
In order to de
termine the extent to which occupational data does offer a common factor that would measure the complex forces which
78 contributed to college-level attendance, a substantial body of data, carefully collected, constantly revised, and appli cable to the entire population, was found indispensable# The United States Census has already been cited as the source of such a body of data. In 1933? Ur. Alba M. Edwards, Director of the Census of Occupations in the Census Bureau, constructed an occup ational scale that compared with the census classification of workers.
The need for such a scale had long been recognized,
and some similar classifications had been attempted, notably by Pearl. 20
The advantage of Edwardfs classification was its
comparability with census data.
The 1940 census enumerated
the population in terms of the classification he suggested, and Edwards subsequently (1943) issued a study of comparative occupational statistics, 1 8 70-1 9 4 0 .2 1
His description of the
classification was fundamental to this study and will be found in Appendix A.
The major occupational groups of the 1940 Census follows Professional workers Semiprofessional‘ workers Farmers and farm managers Proprietors, Managers and Officials except farm
20 Raymond Pearl, The Biology of Population Growth* Revised ed. (New Yorks A. A. Knofp, 1930), 2b0 pp. 21 Alba M. Edwards, log cit.
Clerical, Sales, and Kindred workers Domestic Service workers Craftsmen, Foremen, and Kindred workers Service workers except Domestic Farm Laborers (Wage Worker*s) and Farm Foremen Farm Laborers (Unpaid Farm workers) Laborers except Farm. A description of each class has also been included in Appendix A. Limitations of the census on occupation data are evident. Each individual defined his occupational status to the census enumerator.
Some upgrading undoubtedly occurred.
Smith criticized the professional classification on the basis that it contained anything from **chorus girls and healers**22 to scientists, and was **too heterogeneous to justify placing it at the top of any scale of social stat us. ”23
Attention has also been called to the fact that the /
classification did not correspond to income levels.
Notably,
skilled workers were better paid than clerical and kindred workers; and proprietors, managers, and officials probably earned more than the professional class.
Davidson and Ander
son24- questioned whether it was a measure of economic levels.
22 1. Lynn Smith, Population Analysis, First ed. (New York: McGraw-Hill Book Company, Inc., 1948), p. 169* 2 3 Anderson and Davidson, loc. cit. 2^ Percy E. Davidson and H. Dewey Anderson, 11Are Edwards* Social-Economic Levels Economic?** School and Society, Vol. 1231: 153-156, July 30, 1938.
80 Despite its limitations, all the critics cited believed that the classification offered new opportunity for research. Edwards cited its use, either directly or in a modified form, by many individuals and a g e n c i e s . S h e v k y and Williams utilized it extensively in Social Areas of Los Angeles (Analy sis and Typology), and the classification of data was utilized to a lesser degree by numerous" investigators. It was considered in this study as the only body of objective data, aside from past records of attendance in secondary and collegiate institutions, which reflected in some way all the factors that selected studies had noted as influential in determining college-level attendance. SUMMARY The relation between education and occupations. The purpose of this chapter was to examine the relationship between the social-economic classification of the labor force and college-level attendance. Abundant evidence was found to indicate that a close relationship exists between the occupational character of the population and education.
Education usually fixes income,
standard of living, place in society, place of residence, and the occupational status of the individual.
25 Alba M. Edwards* 0£. clt.% p. 182.
81 The extent to which occupation is a. common factor. Urban or rural residence was seen to influence, tion of the population.
the occupa
A significant difference was seen to
exist between the ratios of the sexes in the major occupation groups.
Race and nativity were also seen to be reflected by
membership in certain occupation groups.
A well-defined
relation was acknowledged between intelligence and choice of occupations.
The growth of new occupations was found
to have added an entirely new curriculum to higher education since 1900.
Economic changes had profoundly affected both
education and occupations.
The presence or absence of edu
cational opportunity was believed to expand or limit certain occupation groups.
Change in each factor considered was
therefore believed reflected in some way by a reciprocal change in the labor force.
A causal relation was not, however,
assumed. The extent and limitations of social-economic data. The United States census was considered as a source that might make possible an evaluation of the extent and degree to which social-economic data reflected objectively the various changes noted.
The major occupational grouping in
the 1940 census offered a body of concrete data.
Edward rs com
parative data for 1870 to 1940 offered a potential check on any assumptions made.
The limitations of existing data were
acknowledged and their use in the study defined. As a generalization, it was inferred that the distri/
/ bution of occupations was related to the level of education, the income (except inherited wealth) and differences in social status in a given population.
A reciprocal relationship was
thus assumed between the occupational hierarchy of a given area and college-level attendance.
The relationship might
operate through variations in the social and economic pressure on youth to attend school. A subsequent chapter was devoted to an objective test of the extent to which the major occupation groups of the United States Census could be of value in predicting atten dance.
CHAPTER V THE BASIS FOR THE PREDICTION OF COLLEGE-LEVEL ATTENDANCE FROM CHARACTERISTICS OF THE POPULATION SOURCES OF DATA The purpose of the chapter.
The purpose of this chap
ter was to enumerate and explain the problems incidental to the use of educational opportunity and the major occupational groups for the prediction of college-level attendance. Sources of statistical data and the definitions and assumptions used in the development of the problem were clari fied. It was stated in a previous chapter that college-level attendance was a product of social and economic forces and educational opportunity.
It was implied that the occupational
characteristics of the population, as measured by the major occupational groups defined and enumerated by the Census, of fers a composite index of the influence of social and economic forces. The United States Census.
The difficulty of comparing
the biennial reports of the United States Department of Education, Walter!s annual report, and the annual enrollment reports of the American Association of College Registrars was noted in Chapter Two.
To eliminate as much disparity as
81+ possible, the United States Census was adopted as the source of attendance data* Methods of enumeration*
In enumerating the population,
the Census Bureau used the number that had their usual place of residence in an area* lation*
This was defined as the dejure popu
If the number enrolled in school was accepted as the
student population a disparity appeared that reduced substan tially the accuracy of prediction.
For example:
in two ad
jacent counties with all educational facilities located in one county there would be a substantial college-level attendance in one county and none in the other county.
The same problem
appeared in degree in estimating college-level attendance in one state.
College-level attendance in this study refers,
therefore, to the attendance of students whose usual place of residence is in the area considered. College-age population.
The primary source of post-
high school attendance is a segment of the general population designated as the college-age population.
The importance of
defining this age group and the differences that exist in the proportion of this age group to the general population was best described by the following quotation by Kelly and Pattersont . . . The proportion of the population attending col lege in some states is more than four times that of other states. . . . This table (refers to Table *+) reveals wide
85 variations among the States. Whereas California holds 9 2 .5 percent of her young people for their higher educa tion, Delaware holds 27.4 percent.1 Defining college-age population.
Differences of
opinion were found to exist as to the range or age limits representative of college-level attendance.
Deutsch,
Douglass, and Strayer defined the college-age population as composed of 1 8 , 1 9 , 2 0 , and 21 year olds, giving as reasons: . . . The college population in the fall of 1947 was for the most part, excepting veterans, composed of 1 8 , 19, 20, and 21 year olds. These are the generations born in 1 9 2 6 , 1927j 1928, and 1 9 2 9 . Those in college in the fall of 1965 will largely be individuals born in 1944, 1 9 4 5 , 1 9 4 6 , and 1947. This is true because the tradition al American educational system provides for four years of college, beginning with the eighteenth year of age. In any semester the college population will include youth of other ages than 18 to 2 1 , particularly in professional and graduate schools. . . .2 In a study by the Pacific Coast Committee of the American Council on Education, an explanation of the selection of ages 18 to 21 was: College-age population, for the purposes of this study, was set at eighteen to twenty-one years inclusive. To develop separate statistical projections for the relative ly small number of students who will enter college before or after these ages would be laborious and unjustifiable.
1 Frederick J. Kelly and Betty A. Paterson, Residence and Migration of College Students. Office of Education, Pamphlet No. 48, pp. 3 and 10.
2
Monroe E. Deutsch, Aubrey A. Douglass, and George D. Strayer, A Report of a Survey of the Reeds of California in Higher Education. The Regents of the University, of California and the State Board of Education, p. 5 3 .
86 As has been stated, reasonable probabilities, rather than nose-counts, were being sought, and the eighteen to twenty one population was an adequate index.3 The United States census has tended to include higher ages in computing attendance data for the past twenty years. Table III illustrates the distribution of college-level en rollment according to age in 1940. It is apparent from Table III that the number of per sons between age 22 and 24 inclusive attending college is ap proximately equal to the number of students attending college between age 14 to 17 inclusive.
Table IV indicates the number
of persons age 18 to 24 inclusive enrolled in a regular school in 1940. Table IV indicates that 1,004,280 students, ages 18 to 24 inclusive, were enrolled in grades one to twelve; or grade level was not reported. Of the 2,210,317 students age 18 to 24 in school in 1940, nearly 41 per cent were not reported as in college. total number who were not in college number in college 18 to 21.
The
was nearly equal to the
The 41 per cent not in college
could not be ignored in defining long-range trends.
It seemed
probable that a substantial number of students over 25 also Alvin C. Eurich, Chairman, Pacific Coast Committee of the American Council on Education, College-Age Population Study. 1947-64. Arizona. California. Nevada, Oregon. Washing ton. Series 1— Reports of Committees and Conferences— No. 29, Vol. II, November, 1947, p. 2.
87
TABLE III POPULATION lH- TO 2b YEARS ATTENDING COLLEGE**
Age
Grades 13-16
Graduate
Total
1^-17
230,275
969
231,21+1+
18-21
1,01+3,967
3 0 ,5 2 3
1,071+,1+90
22-2>+
165,000
6 5 ,51+7
220,51+7
Total
1,1+39,21+2
9 7 ,0 3 7
1,536,281
^ Adopted from Table XVI, Sixteenth Census, 19^0, Population, Characteristics by Age, Part I* United States Summary, p. 5^-*
88
TABLE IV POPULATION 18 TO 2*+ YEARS OLD ATTENDING SCHOOL IN 19^0 , BY GRADE LEVEIS^
Age
No Grade Grades Reported 1 -8
Grades 9 -1 2
Grades 1 3 -1 6
Grade 17
Total
1 8 -2 1
9 ,8*+2
5 8 ,1 0 1
80*+,335
1,0V5,967
30,523
l,9“+6 ,7 6 8
22-2*+
l,5*+8
6 ,1 2 2
2V , 332
1 6 5 ,0 0 0
6 5,9*7
262,5^9
Total
11,390
6*+.,223
8 2 8 ,6 6 7
1,208,967
9 6 ,0 7 0
2,209,317
5 Loc. c i t •
89 attended college to offset the number of students under 18 years of age who qualified for college training. An analysis of school attendance as reported in the census for 1910 and 1940 revealed that 9.OS per cent of the age group 18 to 24 attended school in 1910 and 12.72 per cent attended in 1940.
The number of students who attended
colleges as compared with other types of schools increased much more rapidly.
Apparently the percentage of youth of a
given age in training for adult activities does not vary as much as the type of training.
It therefore appeared logical
that any long-range estimate should be made on the basis of the percentage of the 18 to 24 group who would attend school and that the type of school that they would attend should be redefined each census year.
Such a definition made possible
more extensive use of census data. FACTORS THAT REFLECT EDUCATIONAL OPPORTUNITY Educational opportunity.
It was consistent with the
complexity of the problem to include additional evidence that social and economic forces were closely related to educational opportunity. Anderson and Davidson stated; The standard of living of well over 90 per cent of all families is determined by the gainful employment of one or more of its members. A m a n fs occupation exerts a most powerful influence in assigning to him and to
90 his immediate family their place in society, in deciding their place of residence, and in determining the occupat ional status of the children when they enter employment. The work a man does to earn his livelihood stamps him with mental and physical traits characteristic of the form and level of his labor, defines his circle of friends and acquaintance, affects the use of his leisure, in fluences his political affiliations, limits his interests and the attainment of his aspirations, and tends to set the boundaries of his culture. In a word, except for those few persons whose way of life and future are secured and fixed by the inheritance of great wealth, occupation is the supreme determinant of human careers.6 A recent community study (19*4-8 ) by the Stockton Unified School District of Out-of-School youth and In-SchoolYouth ages 18 to 2b inclusive indicate that education .affected the occupational status of out-of-school youth and that the occupation of the parents affected the educational level attained by youth.7 The occupational status of the parents appears to be a rough measure of the educational opportunity of youth. However, another type of educational opportunity exists, which, although non-quantitive, should be measured - the influence of living near an educational institution.
The
contiguity of an educational institution offers economic advantage and creates what might well be termed a favorable
6 Dewey H. Anderson, and Percy E. Davidson, Occupational Trends in the United States (Palo Alto, California: Stanford University press, 19*K)), p. 1. 7 Community Survey, Out-of-School-Youth. Stockton Unified School District, Andrew P. Hill, Superintendent, p. 9 (mimeographed material, not printed).
91 •'educational climate*”
An increase in the number of types
of state educational institutions offers limited increase in educational opportunity for the entire state.
Local in
stitutions extend and increase this opportunity.
Many
students will attend a local institution who cannot or will not attend a more distant school or college. It must be recognized, however, that a small portion of college-age youth are independent of local or state educational opportunity and can secure training wherever it is available. The relative value of privately and publicly controlled colleges in determining attendance.
The extent to which
privately controlled institutions offer educational advan tages is another factor in defining the degree of educational opportunity that exists in a given state or community.
The
extent to which privately controlled institutions offer opportunity can only be decided in terms of each institution or similar institutions.
For example:
Many of the private
institutions in the South that offered education to non-whites charged less tuition in 1940 than the publicly supported state universities and colleges for the white race.
In Utah the
average tuition paid in the privately controlled institutions of the state in 1940 was less than the average tuition paid in state supported institutions.
92 Tuition costs and the extent of the curricula seened to be indexes of degrees of educational opportunity offered by individual colleges. The degree to which distant colleges affect attendance.
Educational opportunity was also defined in
terms of the presence of an educational institution within a community.
The term college-community was coined and
defined as a contiguous area with a population in excess of fifteen thousand and residing within fifty miles of the center of population.
The definition was arbitrary.
However,
it was based upon the premise that financial support depended upon a population of fifteen thousand or more, and that a large proportion of the student body of most colleges came from an area within fifty miles of the college. Institutions within the state offer one degree of opportunity and institutions more distant another degree. States that supported many types of educational institutions such as agricultural and mechanical schools, technical schools, and junior colleges that offered terminal curricula provided increased educational opportunity. For the purpose of this study the contiguity of educational opportunity in the nation was assumed to be universal in the sense that above average educational opportunity in one area compensated, so far as national
93 estimates were concerned} for lack of opportunity in another SIP63 •
No attempt was made to rate the states in terms of the relative opportunity offered students.
In a subsequent
chapter opportunity in the community was defined in terms of the type of community and the distance to an institution. Opportunity on the secondary level.
Collegiate
institutions accounted for a major portion of college en rollment as defined in this study.
Completion of the
secondary school is ordinarily a prerequisite to college enrollment.
Secondary school opportunity is widespread in
terms of the number of schools.
Wide differences apparently
exist? however 5 in the ability or degree to which states encourage or are able to retain students in secondary schools after they pass the age of fifteen when compulsory attend ance is no longer required or is easily evaded.
Opportunity
on the secondary level was measured in this study by the number of students of ages 16 and 17 in school.
The premise was that
the degree of opportunity present was best reflected by the attendance of students who were beyond the age when attend ance is usually required.
Opportunity on the college level. In addition to opportunity on the secondary level? another measure of the extent to which a state offered educational opportunity was
94 needed# The limit of educational attainment as represented by the number of persons in the population, who had attended one or more years of college, offered an index of past educational opportunity.
It probably also indicated to some
degree the limit of intelligence of the population and in fluenced the "educational climate.,,
By using three measures
of educational opportunity - attendance of the 16-1? age group, adult educational attainment on the college level and contiguity of a college - it was believed a measure of educational opportunity could be obtained. SUMMARY Sources of data.
The United States Census was adopted
as the source of data to eliminate disparity in comparison. The de jure population was the basis of enumeration used in the United States Census. ' The basis used by the United States Department of Education and other sources of data on school enrollment was the de facto population.
In an effort to
eliminate the discrepancy, the de jure school population was the population which was used in this study. The college-age population was defined as the pop ulation 18 to 24 years of age inclusive - college-level attendance included all attendance at a regular school (as defined in the census - Appendix A) by individuals in the
95 age group
18 to 2k inclusive.
for the definition of the term.
Substantial reasons were given School attendance was
attendance during the month of March to correspond to the census enumeration. Factors that reflected educational opportunity.
Edu
cational opportunity was defined in terms of the type and number of institutions in a state or community and the adult educational college-level of the population.
Opportunity to
secure the prerequisite training for college-level attend ance was considered in terms of the number of students in the age group An
17 and 18 inclusive in school. assumption was made that wars and depressions
short-term factors and could not be predicted.
were
Changing
concepts of government or education might make obsolete any prediction of attendance.
CHAPTER VI AH ESTIMATE OF COLLEGE-LEVEL ATTENDANCE BASED ON SELECTED CHARACTERISTICS OF THE POPULATION THE FACTORS SELECTED AND THEIR OBJECTIVE RELATIONSHIP TO COLLEGE-LEVEL ATTENDANCE The purpose of this chapter.
The purpose of this
chapter was to describe the method used in estimating r college-level attendance from selected characteristics of the population with appropriate explanations and applications to illustrate its degree of precision and validity. Characteristics of the population.
General population
characteristics were sex, race, age, marital status, employ ment status, residence, educational level, and attendance at school.
Other characteristics could have been listed.
Each
characteristic enumerated was considered of sufficient im portance to be included in census data thus giving a source of objective data. Sex and race were discussed in Chapter III and dis carded as factors that could be utilized in prediction, either because of uncertain and changing relationships or because of lack of data.
Residence (urban or rural) as
defined by the eensus was not considered a valid criteria
97 for every community because of the method of enumeration and changing methods of transportation. Characteristics of the population selected for use in prediction.
It would be very difficult to obtain ob
jective data on every phase of opportunity; since it con sists of previous training for many years, health factors, family influence, economic influence, availability of a suitable school, level of ability, degree of motivation, 11educational climate11 in the community and other influences too numerous to enumerate.
It was therefore, necessary to
attempt to determine the degree to which three major in fluences were predictive of college-level attendance (1 ) economic and social level of the population (2 ) extent to which preparation for college was encouraged in the commun ity by secondary school attendance, and (3 ) the extent to which the population had encouraged educational opportunity in the past. The characteristics chosen as representative of these influences affecting college-level attendance were the social-economic classification of the labor force and certain phases of educational opportunity represented by the per centage of the age-group 16-1? attending school in a popul ation and the percentage of the population 25 years of age or over who had attended one or more years of college.
98 The distribution of the labor force as represented by the number of individuals in each major occupational group was assumed to reflect the economic and to some degree the social level of the population. Reasons for choosing the percentage of the age-group 1 6 -1 7 attending school as indicative of the degree to which the community offered an opportunity to acquire the pre requisites for higher education were given in Chapter V. The opportunity to complete high school and thus enter higher schools, it was believed, constituted a def inite part of opportunity in terms of college-level attend ance.
The wide distribution of elementary schools and com
pulsory legislation results in high attendance at the elementary level.
At age 16, however, youth is able to enter
a limited labor market and compulsory attendance is not com pulsory or is easily evaded.
The youth of a community begin
to drop out of high school at that age unless social and economic pressures in the community favor high school attend ance and the state provides the type of high school that challenges youth.
For these seemingly logical reasons the
percent of the age group age 16 and 17 attending school in a state or college-community was adopted as a measure of the degree of educational opportunity offered at that level. Correlation analysis revealed an objective relationship (r equal 0 .8 0 1 ) between college-level attendance (age 18 to
99 24)
by
states and thepercentages of
ion
of each of the 48
persons in thepopulat
states ages 16 to 17 inclusive who were
attending school in 1940. A social influence that might well be called "educa tional climate11 could
not be ignored at the college level.
Approval of college training, interest in college activities, and the assumption by a large part of the population that college training is desirable undoubtedly affects attendance. It is reflected by the number of persons in a population that have attended one or more years of college. The number of persons 25 years of age or over who have attended college one or more years also indicates to some degree past opportunity to acquire education, and a measure of social force that influences attendance.
Correlation
analysis revealed a relationship (r equal 0 .8 1 1 ) between college-level attendance (18-24) and the number of persons in the population 25 years of age or over who had completed one or more years of college in 1940. Migration complicated the extent to which it was assumed that the relationship correctly measured past educational opportunity available in an area.
However,
McEntire in a study of California's migrant population said; Migrants to California have come largely from states with lower educational standards and less well-educated populations than California. However, the migrants have been, as a group, better educated than the populations from which they have been drawn consequently there has
100 been little difference between the educational levels of newly-arrived migrants in California and the rest of the state*s population. 1 McEntire indicates that the national pattern of migration parallels California*s migration.
His study
suggested the probability that areas tended to attract mi grants who were on an average of about the same educational level as present inhabitants.
Such an assumption might ex
plain in part the correlation that exists in a community be tween college-level attendance and the number who have attended college one or more years. One or more years attendance at college expressed as a percentage of the total population 25 years or more of age was used as an objective measure of opportunity and desig nated as adult college-level educational attainment. Correlation analysis revealed an objective relationship (r equal .8 1 1 ) between college-level attendance expressed as a percentage of the age group (18 to 24) in each of the 48 states and college-level educational attainment. Another feature of educational opportunity, contiguity to a college, was found to be influential in determining
Davis McEntire, "Characteristics of California*s Population"; p. 33, procedure of the Fifth Conference on the Institute of Economics and Finance, edited by Cecil L. Dunn, Occidental College Bulletin* Vol. XXVI, No. Los Angeles, C a l i f o r n i a . ( N N ) , November 18, 1945-
101 attendance in a community and was included in the method suggested for estimating college-level attendance in a limited area*
Objective consideration of contiguity to a
college was deferred to the next chapter, since differences in opportunity due to that factor averaged out in the nation and to some extent in a state. No assumption was made that the types of opportunity described did not over-lap, or that they included all degrees of educational opportunity.
The degree to which they measured
the same thing was analyzed by the Wherry-Doolittle Test Selection Method of multiple correlation. The relationship of the major occupation groups to college-level attendance.
The major occupation groups as
enumerated in the 19^0 census were* Professional workers Semiprofessional workers Farmers and Farm managers Proprietors, managers and officials, except farm Clerical and kindred workers Craftsmen, foremen and kindred workers
^ Sixteenth Census of the United States: 19^-0; Bureau of the Census, Reports on Population. Vol. IV, C h a r a c t e r istics of the Population,” Part I, Summary, Table XXIX, p. ^9. Washington, D. C.: United States Government Printing Office.
102 Operatives and kindred workers Domestic service workers Service workers except domestic Farm workers (wage workers) and farm foreman Farm laborers, unpaid family workers Laborers , except farm Occupation not reported The relation of the classifications of each occupation group when expressed as a percentage of the labor force in 194-0 to college-level attendance expressed as percentage of the age group 18-24 attending school in each of the 48 states is indicated by the following Pearson product-moment coefficients of correlation.
The criterion in each case was
college-level, attendance. Proprietors, managers, and officials except farm
.757
Professional and semiprofessional workers
.680
Serviee workers except domestic
.323
Clerical, sales, and kindred workers
.271
Occupation not reported
.216
Craftsmen and foremen
.090
Farmers and farm managers
.060
Farm laborers and foremen
-.005
Farm laborers, unpaid family workers
-.246
Laborers except farm
-.303
Operatives
-.319
103 Domestic service workers
-.602
The classifications were rearranged to form a hier archy with the groups with high positive correlation at the top of the hierarchy and the groups that showed high neg ative correlation at the bottom of the hierarchy. The original classification was arranged in a way that apparently emphasized decreasing training or skill.
A
complete description of the occupations included in each classification is included in Appendix A. the classes are pertinent.
Some comments on
A significant relationship
(r equal .7 5 7 ) existed between the proportion of "proprietors* managers* and officials except farm" in the labor force and college-level attendance as defined.
This relationship
appeared to be constant in the several states and a recip rocal relationship was indicated. The relationship between "professional and semiprofessional workers" and college-level attendance (r equaled .680) was relatively high.
Examination of the scattergram*
however* revealed evidence of possible curvilinearity. The use of this relationship would be rendered more difficult statistically if combined with other factors.
Too* the
curvilinearity might be spurious since data from states that supported two systems of education (for Caucasian and nonCaucasian) apparently accounted for the curvilinearity. "Service workers except domestic" showed a definite
positive relationship.
However, this classification contained
a wide range of vocations with a corresponding range of education, social, and economic levels included. "Clerical, sales, and kindred workers*1 showed a positive relationship to the criterion (college-level attend ance), was represented in every state, and was considered as a group that might offer a predictive value. 11Occupation not reported** was a small miscellaneous group which might be composed of the idle rich and the idle poor.
It was considered too small and indefinite for use%
fulness in prediction. d r a f t s m e n and foremen11 was found to have little correlation with college-level attendance. The relationship of each of the other major class ifications was explained by the zero order coefficients cited. The fact that many of the occupations that showed a negative correlation exhibited about the same degree of correlation was considered worthy of interest. Examination of the scattergrams revealed that each of the occupational groups listed as semiskilled or un skilled, excluding "service workers other than domestic," appeared to be closely related*
A scattergram was then made
for a class designated as "semiskilled and unskilled workers," which included "domestic service workers," "operatives," "laborers except farm," "farm laborers (unpaid family
105 workers),“ and “farm laborers and foremen. 11 A relationship with college-level attendance indicated by a negative correlation of -.756 was the result.
A possible
explanation of this increased relationship rested on the assumption that the real relationship was between unskilled and semiskilled labor and college-level attendance rather than between segments of classification and attendance. Correlation between a segment of the group and college-level attendance appeared to be very similar to correlations that existed in one quadrant of the scattergram showing the re lation of the combined groups and college-level attendance. Zero order correlations were computed to determine the objective relation of the classes to the criterion (collegelevel attendance) and to each other.
The “professional and
semiprofessional workers" classification had a high correlation (r equal .854) with “proprietors, managers and officials, except farm11 which indicated the probability that the two were interrelated and measured the same thing. Since “professional and semiprofessional“ in addition showed some indications of curvilinearity? it was omitted. The correlation of each factor with the criterion (college-level attendance expressed as a percentage of the age group 18 to 24) and with each other, designated as: (1 ) proprietors and managers except farm expressed as a percentage of the labor forces
(2 )
semiskilled and un—
106 skilled workers expressed as a percentage of the labor force; and (3 ) clerical sales and kindred workers expressed as a percentage of the labor force is given in Table V. Table V shows the correlation and intercorrelation of three classifications of the labor force with collegelevel attendance and Table VI shows the correlation and intercorrelation when one measure.of educational opportunity was added (attendance? 1 6 -1 7 ). Multiple correlation analysis indicated a relation ship between Factors #1? #2? #3, #4 in Table VI and the criterion expressed by an R of *9 0 0 (after chance errors had been removed by the Wherry-shrinkage formula). THE METHODS USED FOR PREDICTION Selection of factors.
The selection of a number of
factors that apparently reflected changes in college-level attendance was the purpose 'of Chapter III? IV? and V. The relationship of these factors? and many others? to college-level attendance in each of the 48 states was determined by scattergrams and the calculation of zero order Pearson product-moment coefficients of correlation. The Wherry-Doolittle Test Selection Method^ was used to
3 Henry E. Garrett? Statistics in Psychology and Education. Third ed. (New York: Longmans? Green and Co.? 1947)? p. 435.
107 TABLE V THE CORRELATION BETWEEN COLLEGE-LEVEL ATTENDANCE AND SELECTED FACTORS AND THE CORRELATION BETWEEN FACTORS
0 a College-level attendance 1 - Proprietors, managers, and officials, except farm 2 = Semiskilled and unskilled workers 3 s Clerical, sales, and kindred workers
1 0 1 2
.757192
2
3
-.756139
.270551
— 677993
.553865 -•332853
This table reads: the correlation of factor #1 with the criterion is *757192# Factor #1 has a correlation with factor #2 of .6 7 7 9 9 3 , etc.
108 TABLE VI THE INTERCORBELATION OF ATTENDANCE 18 TO 24 WITH ATTENDANCE 16 TO 17 AND THREE CLASSIFICATIONS OF THE MAJOR OCCUPATION GROUPS
List of Factors (N = 48)
0
s
Criterion— college level attendance
1 s Attendance, ages 16 to 17 2 - Proprietors and managers, except farm 3 = Semiskilled and unskilled workers 4
0 1 2 3
Clerical, sales, and kindred workers
1
2
3
.801849
.757192
-.756139
.270551
.761198
-.631297
.572127
-.677993
.553865
4
-.332853
This table reads t the correlation of factor # 1 with the criterion is .757192. Factor #1 has a correlation with factor #2 of .677993} etc.
109 select the tests which would yield a maximum multiple R, to discard factors which added nothing to prediction, and to compute a multiple regression equation from which the criterion could be predicted. The selection of factors included discovering the relationship between the various major occupation groups and combining those classes which alone had little relationship but which together offered value in prediction. Another consideration was the extent to which each factor was represented in every community.
A few factors
would predict accurately for the nation or even a state, but failed to predict in a single community.
Additional consider
ation was given this problem in a succeeding chapter devoted to the estimation of potential attendance in a single community. Statistical techniques used.
Pearson product-moment
coefficients of correlation were calculated to determine the relation of the factors selected to college-level attendance and to each other in the ^8 states in 19^0 (Table VIII). The Wherry-Doolittle Test Selection Method of multiple correlation analysis was used to determine the relative value of each factor (Beta weights) and the total value of the team of factors
(multiple R) in prediction.
Appendix C ) .
(Table XXVII
110 The Beta weights were used in linear regression equations to estimate the extent to which college-level attendance changed in relation to the factors used in pre diction.
^he formula used was included in Appendix C.
Ezekiel*s
4
method of determining the value of a non-
quantitative variable was used in Chapter VIII and explained in that chapter.
A discussion of the reliability of re
gression coefficients and the estimates made was included in Appendix C. APPLICATION OF THE TECHNIQUE TO DATA FOB 1910, 1920, 1930, 19^0, and 1948 That educational opportunity at the secondary level and the relation of the major occupation groups to collegelevel attendance in 1940 represented a fundamental and basic relationship was suggested by the following analysis of national attendance for 1910, 1920, 1930* 1940, and 1948. Comparison of the labor group— 1910 to 1948.
Alba
Edwards^ in a publication of the Bureau of the Census^ ^ Mordeeai Ezekiel, Methods of Correlation Analysis. Second Ed. (New York: John Wiley & Sons, Inc., 1941), p. 32 5* ^ Alba M. Edwards. Comparative Occupation Statistics for the United States. Io70 to 1940. Bureau of the Census, Sixteenth Census of the United States: 1940 (Washington, D.C.s United States Government Printing Office, 1943), 206 pp.
6
Sixteenth Census of the United States: 1940. Bureau of the Census, Reports on Population. 4 vols. and Special Reports, Washington, D. C.: United States Government Printing Office, 1943,
Ill compiled comparative occupation statistics for the period 1870 to 1940 and classified the various occupations into social-economic groups.
The basis of his classification was
explained in Chapter V and the complete description is in cluded in Appendix A.
Certain major occupation groups for
194-0 were comparable to his social-economic classifications particularly for the years 1910, 1920, and 1930,
E
17 who were attending school, and thus completing the pre requisites for post-high school training; and the percentage of the group age 25 and over who had completed one or more years of college.
Contiguity to a college was considered a -
separate and distinct factor, since it did not directly measure educational opportunity as such.
It merely in
creased or decreased the sum of educational opportunity by increasing or decreasing the intensity of the social and economic forces operating in a specific area.
A separate
measure was adopted to define this non-quantitative variable. Basic definitions and assumptions were developed to take in^consideration the age, distribution, and residence of the population and a formula to estimate attendance was evolved*
The development and application of the formula. National attendance for 194-0 was analyzed as a basis for determining the influence of variables.
The Wherry-DoolittleN
Test Selection Method of multiple correlation analysis re vealed a relationship between college-level attendance (ex pressed as percentage of the age-group 18 to 24) in the 48 states and a team of variables ("Attendance* ages 16 and 17*11 "Proprietors and Managers* except Farm*" "Semiskilled and Unskilled Workers*" "Clerical*Sales*and Kindred Workers") expressed by an R of .900.
The relative value of the several
factors in prediction was represented by Beta weights ob tained in the calculation of multiple R.
These Beta weights
were used in linear regression equations to predict the most probable values of the dependent variable. To determine if the relationship found for 1940 was constant for other census years national attendance was estimated for 1910* 1920* 1930* 1940* and 1948 from com parative data. Since no other sample could be drawn from the same "universe" except those included in the problem (for the universe was restricted to the 48 states in 1940) appli cation of the relationship to previous years was made to give a tentative measure of the extent to which it might* also* apply to subsequent years.
152 The standard deviation of the residuals (standard error of estimate) .991* indicated that 67 per cent of the estimates made with the formula could be expected to come within one per cent of the actual value expressed as the percentage of the age-group 18 to 24 attending school* The relationship between the dependent and independ ent variables was not interpreted as constant or necessarily a casual relationship.
It was suggested that the relation
ship was reciprocal and probably changed as our culture changed.
It was assumed that contiguity was eliminated as a
factor in national estimates by compensation (high degrees of opportunity in some states compensated for lack of oppor tunity in others). Application of the formula to state estimates.
The
formula used in estimating national attendance was refined to estimate attendance for each state. An additional factor, "Adult College-level Educational Attainment,11 was added to the team of independent factors and Proprietors, Managers, except Farm11 was eliminated be cause of a high correlation with the new factor.
A relation-*
ship expressed as an R of .922 was obtained. The new formula was then applied to census data for the 48 states for 1940/
It was recognized that attendance
was estimated for the 48 states on the basis of equal
153 educational opportunity as far as the contiguity of a college to each college-community was concerned*
The purpose of the
estimate was to compare the relative achievement of each state in 194*0 when the four characteristics of the population were accounted for by the factors used in prediction. National and state estimates compared.
The standard
deviations of the residual^ (differences between actual and estimated attendance) was 1 .2 3 as compared with .9 9 for the estimates of national attendance over a period of five decades.
The increase in the standard deviation of the
residuals (standard error of the estimate) despite a higher R, was ascribed to differences in educational opportunity in the several states not measured by the factors.
This
assumption was supported by the fact that states that were acknowledged to offer a high degree of educational oppor tunity were underestimated and states acknowledged to be below the national average were overestimated. Evaluating the influence of contiguity.
No objective
data were available to evaluate state differences in edu cational opportunity.
Therefore the formula was applied
to the counties of California to determine the value rep resented by contiguity to a college in that state.
Counties
of the state were divided into four groups in terms of the
degree of educational opportunity estimated present in each county.
By use of a technique based on the relationship of
the differences between estimated attendance and actual attendance (residuals) it was possible to give an objective value to four defined degrees of educational opportunity present in the state in 1940.
In view of the slow rate at
which the factors changed it was believed that the value for each group would not alter greatly in a single decade. The difference between maximum and minimum opportunity in terms of the presence of a college or colleges in a county in California in 1940 was approximately 8 per cent when attendance was computed as a percentage of the age group 18 to 24 inclusive attending school.
The value applied
only to California. Potential attendance. fined by comparison.
Potential attendance was de
It was estimated by adding the mean of
the residuals for the group of counties classified as offer ing maximum opportunity in the state (group I) to the attend ance estimated on the basis of the characteristics of the population.
The latter estimate assumed that the community
had educational opportunity equivalent to mean educational opportunity in the nation.
The mean of the residuals of
group I was assumed to represent the value of contiguity of a college.
155 CONCLUSIONS The relationships established,
A relation was
objectively established between the major occupation groups and college-level attendance, and between educational oppor tunity and attendance.
The relation of the major occupation
groups was represented by two factors in the formula used to estimate attendance. relation.
This relation was termed a reciprocal
It may be a casual relation; or both the composi
tion of the labor force and college-level attendance may change at approximately the same rate due to some basic force or change that controls them both.
An interesting specula
tion is that each may reflect urbanization. A method of estimating college-level attendance based on the relation of attendance
to the characteristics of
the population was formulated.
The formula when applied
to data for the nation, -gave a collective estimate of national college-level attendance.
When applied to data
for a state it approximated state college-level attendi/
ance; but reflects differences in educational opportunity in the states that were not compensated for by migration to other states.
When applied to data for a county or
a college-community the formula provided a comparison with other communities regardless of differences in the occupational
characteristics
and educational
level
156 of th© population of the two communities.
The estimate of
attendance was not based on mean educational attainment or opportunity; but on a changing quantity moving along a fitted line of relation as the independent variables (characteristics of the population)changed. k method of estimating the value of the contiguity of a college to a community in terms of college attendance was formulated.
The value was defined as a series of constants
that increased educational opportunity in areas that offered defined degrees of educational opportunity in terms of edu cational facilities.
The method suggested could be refined
by the use of census tracts to define each college-community used in comparison and the use of census data for 1950.
It
could be applied in any state by use of census data for a computation of values for that state.
The technique made it
possible to define the value of certain degrees of educational opportunity in a state to a college-community in terms of attendance. The value of the study.
The methods* formulas* and
techniques suggested in this study provides
(1 ) a method
by which national attendance may be estimated from certain characteristics of the population;
v
(2 ) a method by which a
forecast of national attendance can be made with the expect*
ation of a degree of precision not attained by previous
157 forecasts by projecting the growth of the factors used and use of the formula on the estimated values obtained. (This was not included in the study because of the imminence of a census year.); (3 ) a method by which communities may be equitably com pared in terms of the extent to which they are providing collegelevel opportunity commensurate with the characteristics of the population when compared with national norms; (4) a method by which the potential attendance of a community can be estimated as compared with attendance in other parts of the same state when the characteristics of the population are considered. The use of the formulas and techniques in a city where census tract data are available and where the effect of dis tance on attendance is known would provide (1) information as to the prospective attendance that could be expected if new junior colleges or senior colleges were established; (2 ) in formation regarding the best location for new institutions; (3 ) information regarding the potential enrollment that could be expected if educational opportunity comparable to the maximum in the state were provided. The use of the formulas and techniques in a state would provide equally valuable information regarding the establishment of regional senior or junior colleges. No single formula or technique, however, offers a ready-made survey of a community or state. Terrain or climate, for example, might make attendance
158
impossible for students living within a few miles of a college.
Special provisions for those students might still
not compensate for the influence which a college in a community would exert upon youth to attend.
A comprehensive
study of the individual community is necessary. SUGGESTIONS FOR ADDITIONAL RESEARCH Equality of educational opportunity.
The determina
tion of a comparative index by which comparisons may be fairly made considering the characteristics of the population raises the question of equality of educational opportunity for youth living in areas where estimated attendance is higher than ac tual attendance.
Many areas would benefit by the establishment
and maintenance of educational institutions found practical for similar communities.
Other communities because of
terrain* sparse population* and climate have to consider the enrollment that could be expected* the cost per pupil of education* and the special type of education that would pro vide maximum opportunity to their youth. Criteria to determine the characteristics of the adequacy of a college-community are apparently needed.
The
size of an institution determines to a degree the cost and the extent of the curriculum.
Is it more feasible to con
struct regional junior colleges or colleges and provide dormitories and sustenance for students from remote areas*
159 or is it more practical to develop colleges in remote areas and pay whatever additional cost is necessary to provide the curriculum needed?
There is no question of the value of
bringing youth to college.
To what extent will youth choose
to attend, however, if they are not encouraged to seek training by the part which the college plays in the social and economic life of a community?
At what point should the
state limit the ambition of a community to maintain a local college? Tvnes of educational institutions.
A comparison of
the number of persons 18 to 24 attending regular schools in „ California in March 1940, with the number attending colleges as defined by the California State Department of Education, revealed that approximately one third were attending schools not defined as colleges.
Additional data regarding the
number of students and the type of instruction in those schools where youth is willing to pay tuition to secure instruction would be of interestto educators. An age-grade study.
The median age of students in
Los Angeles City College in the fall semester of 1950 was two years higher than the median age of pre-war students. age-grade study of students enrolled
An
in California colleges
would clarify the extent to which attendance can be predicted in terms of a college—age group.
The influx of veterans does
160 not seem to offer a complete explanation. Bace and nativity.
The influence of race and
nativity on college-level attendance is not represented adequately by statistics on college-level attendance that merely indicate the proportions of each race that attend. Non-caucasian attendance in West Virginia> expressed as the percentage of the group 18 to 24 attending school was greater in 1940 than Caucasian attendance.
The proportion
in Oklahoma was approximately equal. In two California Junior Colleges * (Los Angeles City College and Erawley Junior College) over a period of five years Negro attendance exceeded the attendance of Mexican students ten to one despite the fact that the Negro pop ulation was exceeded by the Mexican population.
Some
national groups exceed the native population in collegelevel attendance. Attendance or non-attendance appears to be related more closely to cultural patterns than to race or nativity.
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162 A.
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PUBLICATIONS OF LEARNED ORGANIZATIONS
Badger, Henry G., The Economic Outlook in Higher Education for 123iiz3-5- Office of Education , Pamphlet No. 5 8 . Washington, D. C #: United States Government Printing Office, 193^• *+9 pp. Blose, David T., and Ambrose Caliver, Statistics of the Edu cation of Negroes. 19^-^*+ and 19^5-36l Office of Educa tion, Bulletin 1938, No.' 13. Washington, D. C.: United States Government Printing Office, 1939* 67 pp. Boardman, H. S., and 0. S. Lutes, Survey of Higher Education
169 in Maine. by the University of Maine. in Cooperation with Bates . Bowdoin. and Colby Colleges. Under the direction of Teachers u oliege, Columbia University, New York. Orono, Mains 1932. ^21 pp. Bunn, John W . , "Reappraisal of Enrollment Trends and Implica tions," Current Trends in Higher Education. 19^8. Part II. Department of Higher Education. Washington, D. National Education Association of the United States, June, 19^8. Pp. 39-^5. Capen, Samuel Paul, and Edwin B. Stevens, Report of a Survey of the University of Nevada. Bureau of Education, Bulle tin 1917, No. 19. Washington, D. C.s, United States Government Printing Office, 1917* 18*+ pp. Deutsch, Monroe E . , Aubrey A. Douglass, and George D. Strayer, A Report of a Survey of the Needs of California in Higher Education. The Regents of the University of California and the State Board of Education, n.p.s n.n., March 1, 19^8. 132 pp. Dunn, Cecil L., editor, "Proceedings of the Fifth Conference of the Institute of Economics and Finance," Occidental College Bulletin. Vol. XXVI, No. 1. Los Angeles, Cali fornia: n.n., November, 19*+8. 1^5 pp. Eckelberry, R. H., The History of the Municipal University in the United States. Office of Education, Bulletin, 1932, No. 2. Washington, D. C.: United States Government Printing Office, 1932. 213 PP. Edwards, Newton, "A Report to the American Youth Commission," Equal Educational Opportunity for Youth. Washington, D. C.: American Council on Education, 1939. 189 pp. Faulkner, Donald, conference director, Report of the Confe rence on Administration of the Church-Related School. Green Lake, Wisconsin: United Presbyterian College Asso ciation, Disciples of Christ Board of Education, Associa tion of Northern Baptist Educational Institutions, and National Protestant Council on Higher Education, June
2^-29 , 19^8 . 267
pp.
Grigsby, Rail I., Annual Report of the Federal Security Agency. 19*+o. Office of Education. Washington, D. C.: United States Government Printing Office, 19^ 8 . 530 pp. Hauser, Dr. Philip M., Sampling Staff, A Chapter in Population
170 Sampling. Bureau of the Census. Washington, D. C.s United States Government Printing Office, n.d., after 1944. 141 pp. Hollis, Ernest V., and Ralph C. M. Flynt, Higher Education Looks Ahead. Office of Education, Bulletin 1945, No. 8 . Washington, D. C.: United States Government Printing Office, 1945. 98 pp. Kefauver, G. N., W. H. Noll, and C. E. Drake, The Secondaryschool Population, National Survey of Secondary Education, Monograph 4, U. S. Office of Education Bulletin 1 7 . 19^2. 68 pp. Kelly, Fred J., Continuity of College Attendance. Office of Education, Bulletin, 1937, No. 24. Washington, D. C.: United States Government Printing'Office, 193724 pp. _______ , and Ruth E. Eckert, Residence and Migration of Col lege Students. Office of Education, Pamphlet No. 9 8 * Washington, D. C.: United States Government Printing Office, 1945. 19 pp. _________ and John H. McNeely, Federal Students Aid Program. Office of Education, Bulletin 1935, No. 14. Washington, D. C.: United States Government Printing Office, 1935* 39 PP. _______ , and Ella B.Ratcliffe, Privately Controlled Higher Education in the United States. Office of Education, Bulletin, 1934, No. 12. Washington, D. C.s United States Government Printing Office, 1934. 22 pp. _______ , and Betty A. Patterson, Residence and Migration of College Students. Office of Education, Pamphlet No. 4S. Washington, D. C.s United States Government Printing Office, 1934. 22 pp. McDonald, Ralph W., editor, Current Trends in Higher Education. Department of Higher Education. Washington, D. C.s National Education Association of the United States, 1947. 227 pp. _______ , editor, Current Trends in Higher Education, 1949. Department of Higher Education. Washington, D. C.s National Education Association of the United States, 1949202 pp. _______ , and James L. McCaskill, editors, Current Trends in
171 Higher Education, 19*+8. Department of Higher Education. Washington, D. C.: National Education Association of the United States, June, 19^8. 199 pp. McNeely, John H . , College Student Mortality. Office of Edu cation, Bulletin 1937, No. 11. Washington, D. C.: United States Government Printing Office, 1938. 112 pp.
______ , The Problem of Duplication as Attacked in Certain State Surveys of Higher Education. Office of Education, Bulletin- 193^, Ho. 19. Washington, D. C.s United States Government Printing Office, 1935* 50 pp. s/Miller, Ernest C., “Enrollment Trends,** Current Trends in Higher Education. Department of Higher Education, Washington, D. U . : National Education Association of the United States, 19^-7* Pp. 27-3^• Morrison, J. Cayce, chairman, Committee on Institute Curriculums, “A Guide to the Development of Programs for the Institutions of Applied Arts and Sciences,1' University of the State of New York Bulletin. No. 1332* n.p.s n.n., January 2, 19^7* 75 PP*
Partch, Clarence E., Analysis of the Need for Facilities to Provide Adequate Educational Opportunities for Veterans and for Graduates of Secondary Schools. New Brunswick, New Jersey: Rutgers University, July, 19^6. 71 PP* Population Association of America, “Intrinsic and Environ mental Factors in American Population Growth,” Proceed ings of the American Philosophical Society. Vol. XXC, No. Lh, February l5. 1939. Philadelphia: The American Philosophical society, 1939* 626 pp. Re v e s , Floyd W. , National Resources Planning Board, “Equal Access to Education,” Section 9? PP* 68-7^ of “Supporting Technical Material,” Part I of “Post-War Plan and Program,” 8l p p . , National Resources Development Report for 19*+3. House Document No"! 128, 78th Congress, 1st Session. Washington, D. C.: United States Government Printing Office, 19^3* _______ , Ernest C. Miller, and John Dale Russell, “The Univer sity of Chicago Survey,” Trends in University Growth. Vol. I. Chicago: University of Chicago Press, 1933• 2*+2 pp. Shevky, Eshref, “Character of the Resident Population,” pp. 10-19 of “Proceedings of the Fifth Conference of the In stitute of Economics and Finance,” edited by Cecil L.
172 Dunn, Occidental College Bulletin. Vol. XXVI, No. 1. Angeles, California: n.n., November, 19*+8. l*+5 PP. Strayer, George D . , in the State of t o n . Submitted 19%. Olympia,
Los
f,A Report of a Survey of Public Education Washington," Public Education in Washingto Governor Mon C. Wallgren September 5, Washington: n.n., 19*+6. 66*+ pp.
Studebaker, John W., U. S. Commissioner of Education, Annual Report of the Federal Security Agency. 19*4-7. Section 2, pp. 169-2^ 8 . Office of Education. Washington, D. C.: United States Government Printing Office, 19*+8. Tead, Ordway, "Equalizing Educational Opportunities Beyond the Secondary School," Inglis Lecture. 19*+7. Cambridge, Massachusetts, Harvard University Press, 19*+7. 53 PP* Th o m a s , Dorothy Swaine, Research Memorandum on Migration Differentials. Bulletin *+3 . New York: Social Science Research Council, 1938. *+23 pp. Varnum, Walter C., chairman, Four-Year College Survey Com mittee, A Study of the Needs of Higher Education in Los Angeles. Los Angeles, California: Los Angeles City College, February, 19*+9. 106 pp. Watson, Tom, Program of Education and Training for Young Persons Employed on Work Projects on the NYA • . • Final Report. Bulletin 19*+6, No. 12. Washington, D. C.: United States Government Printing Office, 19*4-6. 16 pp. West, Rodney M., and L. V. K o o s , "I. The Growth of the Uni versity in the Next Quarter Century," The Bulletin of the University of Minnesota. Vol. XXIII, 257^9-5*0, June 21, 1920. Mimneapolis, Minnesota: The University of Minne sota, 1920. 50 pp. Zook, George F., The Residence and Migration of University and College Students. Bureau of Education, Bulletin 1926, No. 11* Washington, D. C.j United States Government Printing Office, 1926. 127 pp. E.
UNPUBLISHED MATERIALS
Carpenter, Charles Clifford, "A Study of Criteria to Determine the Characteristics of the Adequacy of School Districts in California." Unpublished Doctor*s dissertation, The University of Southern California, Los Angeles, 19*+8. 1*4-5
173 Edwards, Marcia, f,The Relation of College Enrollment to Eco nomic Depression in the United States, 1890 to 1930. 11 Unpublished Master’s dissertation, University of Minnesota, Minneapolis, 1931* 144 pp. Hills, E. Justin, "The Determination of Need for Educational Provision at the Higher Secondary Level in the Los Angeles School District.11 Unpublished Doctor’s dissertation, University of Southern California, Los Angeles, 1941. 456 pp. Kozelka, Richard L., "Business Indicators for the Ninth Federal Reserve District with a Tentative Combined Index." Unpublished Doctor’s dissertation, University of Minnesota, Minneapolis, 1931* 253 PP« Marchus, Flo5^d Irvin, "Forecasting University Enrollment." Unpublished Doctor’s dissertation, The University of California, Berkeley, 1947* 142 pp. F.
NEWSPAPERS
Article in The Los Angeles Times. October 2, 1949. f,Colleges Facing Financial Straits," Part I, p. 30.
APPENDICES
APPENDIX A DEFINITIONS AND AN EXPLANATION OF THE CLASSIFICATION OF THE LABOR FORCE
176 The Sixteentli Census of the United States: 1940 used as a primary source of data.
1
was
The following excerpts
from the Census define the terms used: 2 School Attendance. — The school attendance tabulation for 1940 is based on the replies to the enumerators inquiry as to whether the person had attended, or been enrolled in, any regular school or college between March 1 and April 1, 1940. Night schools, extension schools, or vocational schools are not included unless they are part of the regular school system; and no correspondence schools are included. The corresponding question in the censuses from 1890 to 1930 applied to a somewhat longer period: In 1910, 1920, and 1930 to the period bet?/een the preceding September 1 and the census date (April 15 in 1910, January 1 in 1920, and April 1 in 1930), and in 1890 and x900 to the 12 months preceding the census date. Fur thermore, the question was not restricted as to the type of school or college in the earlier censuses'. The shorter period to which the question applied in 1940 undoubtedly accounts for many of the apparent de clines during the decade in the proportion attending school at given ages. Further, there were a number of areas in which the rural schools were closed for the entire month of March, 1940; "and, although the children in these areas were for the most part still enrolled in school, negative answers were generally given to the school attendance question, since the children were not actually in attendance. Moreover, in those urban areas where midyear graduates are important, the midyear graduates would have been returned in 1940 as not attend ing school— but at earlier censuses they would have been returned as attending.
Sixteenth Census of the United States: 1940. 4 Vol s . , Bureau of the Census (Washington, D. C. U. S. Government Printing Office).
2 Ibid., Vol. II, 11Characteristics of the Population,11 p. 11.
177 Table V summarizes the figures for the United States in 194-0 for persons 5 to 24 years of age by school attend ance, sex, and selected age groups. Highest grade of school completed.^ The 1940 census, for the first time, included a question on the formal educational attainment of each person. The question on \ the schedule referred to the last full grade that the person had completed in the regular school system— public, private, or parochial school, college, or university. This question replaces the inquiry on illiteracy included in previous censuses, and provides data on educational status, a characteristic which is significant for every population group, especially in combination with other characteristics. The tabulations on last year of school completed, which are presented here, are restricted to persons 2 5 years old and over, practically all of whom have completed their formal education. More dtailed statistics on education to be presented in later publications will include for younger persons data on last year of school completed, cross-classified with school attendance. All tables presenting data on education include the median year of school completed. The median year of school completed may be defined as that year which divides the population into two equal groups, one-half having completed less schooling and one-half having com pleted more schooling than the median. These medians are expressed in terms of a continuous series of numbers representing years completed. For example, the completion of the first year of high school is indicated by 9 and of the last year of college by 16. For the sake of com parability, the first year of high school uniformly rep resented by 9j although there are some areas with only 7 years of elementary school. Table VI summarizes the figures for the United States in 1940 for persons 25 years old and over by years of school completed and by sex. Data on median school years completed are also presented.
4
Occupations included in each major occupation group: 3 Ibid., p. 11 4 Ibid., p . 17
178 TABLE XVI (Designated Table V by Edwards) SCHOOL ATTENDANCE, BY AGE AND SEX, FOR THE UNITED STATES s 1940
Total
Male
4 6 ,3 5 1 ,9 1 5
2 3 ,2 4 3 ,6 9 7
23,108,218
Persons 5 and 6 No. attending Percent attending
4 ,1 9 6 ,7 9 2 1 ,8 0 5 ,2 1 1 4 3 .0
2,129,568 901,367 42.3
2,067,224 903,844 43.7
Persons 7 to 13 No. attending Percent attending
1 5 ,8 2 8 ,0 3 5 1 5 ,0 3 4 ,6 9 5 9 5 jo
8 ,0 2 3 ,4 6 8 7,607,080 94.8
7,804,567 7,427,615 95.2
Persons 14 and 15 No. attending Percent attending
4,828,248 4,347,665 9 0 .0
2,440,453 2,189,880 89-7
2,387,796 2,157,785 90.4
Persons 16 and 17 No. attending Percent attending
4,892,170 3,361,206 68.7
2,162,443 !,679,590
2,429,727 1,681,616 69.2
Persons 18 to 20 No. attending Percent attending
7,385,876 1,744,447 2 3 .6
3 ,6 4 6 ,0 3 6 935,854 25.7
3,739,840 808,593 21.6
Persons 21 to 24 No. attending Percent attending
9,220,793 465,875 5.1
4,541,729 300,814 6.6
4,679,064 165,061 3.5
School Attendance
Total, 5 to 24 yrs.
Female
179
Professional workers: Artists and art teachers; Authors, editors, and reporters; Chemists, assayers, and metallurgists; Clergymen; College presidents; Professors and instructors; Dentists; Engineers, technical; Lawyers and judges; Musicians and music teachers; Pharmacists; Physicians and surgeons; Teachers (n.e.c.)*; Trained nurses and student nurses; Actors and actresses; Archi tects; County agents and farm demonstrators; Librarians; Osteopaths; Social and welfare workers; Veterinarians; Professional workers (n.e.c.). Semiprofessional workers: Designers and draftsmen; Funeral directors and embalmers; Photographers; Religious workers; Technicians; Athletes; Aviators; Chiropractors; Dancers, dancing teachers, and chorus girls; Healers and medical service workers (n.e.c.); Optometrists; Radio and wireless operators; Showmen; Sports instructors and offi cials; Surveyors; Semiprofessional workers (n.e.c.). Farmers and farm managers: Farm managers.
Farmers (owners and tenants);
Proprietors, managers, and officials, except farm: Advertising agents; Conductors, railroad; fnspectors, government; Public officials (n.e.c.); Buyers and depart ment heads, store; Country buyers and shippers of live stock and other farm products; Credit men; Floormen and floormanagers, store; Managers and superintendents, building; Officers, pilots, pursers, and engineers, ship; Officials, lodge, society, union, etc.; Postmasters; Purchasing agents and buyers (n.e.c.); Proprietors, managers, and officials (n.e.c.). Clerical, sales, and kindred workers: Agents (n.e.c.); Bookkeepers, accountants, and cashiers; MClerks11 in stores; Mail carriers; Messengers, errand, and office boys and girls; Shipping and receiving clerks; Steno graphers, typists, and secretaries; Telegraph operators; Telephone operators; Ticket, station, and express agents; Attendants and assistants, library; Attendants, physicians1 and dentists* offices; Baggagemen, transportation; Col lectors, bill and account; Express messengers and railway mail clerks; Office machine operators; Telegraph sje
N.e.c. is used as an abbreviation for "not else where classified."
180 messengers; Clerical and kindred workers (n.e.c.); Canvassers and solicitors; Hucksters and peddlers; Insurance agents and brokers; Real estate agents and brokers; Traveling salesmen and sales agents; Auctioneers; Demonstrators; Newsboys; Salesmen, finance, brokerage, and commission firms; Salesmen and saleswomen (n.e.c.). Craftsmen, foremen, and kindred workers: Bakers; Blacksmiths, forgemen, and hammermen; Boilermakers; Brickmasons, stonemasons, and tile setters; Carpenters; Compositors and type-setters; Decorators and window dres sers; Electricians; Foremen (n.e.c.); Inspectors (n.e.c.); Jewelers, watchmakers, goldsmiths, and silversmiths; Loco motive engineers; Locomotive firemen; Machinists, mill wrights , and tool makers; Mechanics and repairmen; Holders, metal; Painters, construction and maintenance; Paperhangers; Pattern and model makers, except paper; Plasterers; Plumbers and gas and steam'fitters; Roofers and salters; Sawyers; Shoemakers and repairers (not in factory); Stationary engineers, cranemen, hoistmen, etc.; Tailors and tailoresses; Tinsmiths, coppersmiths, and sheet metal workers; Upholsterers; Cabinetmakers; Cement and concrete finishers; Electrotypers and stereotypers; Engravers (except photoen gravers); Furriers; Glaziers; Heat treaters, annealers, and temperers; Inspectors, scalers, and graders, log and lumber; Loom fixers; Millers, grain, flour, feed, etc.; Opticians and lens"grinders and polishers; Photoengravers and lithographers; Piano and organ tuners; Pressmen and plate printers, printing; Rollers and roll hands, metal; Stone cutters and stone carvers; Structural and ornamental metal workers. Operatives and kindred workers: Apprentices; Attendants, filling station, parking lot, garage, and airport; Brakemen, railroad; Chauffeurs and drivers, bus, taxi, truck, and tractor; Conductors, bus and street railway; Deliverymen; Dressmakers and seamstresses (not in factory); Filers, grinders, buffers, and polishers, metal; Firemen, except locomotive and fire department; Furnacemen, smeltermen, and pourers; Heaters, metal; Laundry operatives and laundresses, except private family; Linemen and servicemen, telegraph, telephone, and power; Meat cutters, except slaughter and packing house; Mine operatives ana laborers; Motormeii, street, subway, and elevated railway; Painters, except contracting, construetion and maintenance; Sailors and deck hands, except U. S. Navy; Switchmen, railroad; Welders and flamecutters; Asbestos and insulation workers; Blasters and powdermen; Boatmen, canalmen, and lock keep ers ; Chainmen, rodmen, and axmen, surveying; Dyers; Fruit
181 and vegetable graders and packers, except in cannery; Milliners (not in factory); Motion picture projectionists; Motormen (vehicle), mine, factory, logging camp, etc,; Oilers, machinery; Photographic process workers; Power station operators; Operators and kindred workers (n.e.c.). Domestic service workers: Housekeepers, private family; Laundresses, private family; Servants, private family. Service workers, except domestic: Firemen, Fire department; Guards, watchmen^ and doorkeepers; Policemen and detectives; Soldiers, sailors, marines, and coast guards; Marshals and constables; Sheriffs and bailiffs; Watchmen (crossing) and bridge tenders; Barbers, beauti cians , and manicurists; Bartenders; Boarding house and lodginghouse keepers; Charwomen and cleaners; Cooks; Elevator operators; Housekeepers, stewards, and hostesses, except private family; Janitors and sextons; Porters; Practical nurses and midwives; Servants, except private family; Waiters and waitresses, except private family; Attendants, hospital and other institution; Attendants, recreation and amusement; Bootblacks; Ushers, amusement place or assembly. Farm laborers (wage workers) and farm foremen: laborers (wage workers); Farm foremen.
Farm
Laborers„ except farm: Fishermen and oystermen; Garage laborers and car washers and greasers; Gardeners (except farm) and groundskeepers; Longshoremen and steve dores; Lumbermen, raftsmen, and woodchoppers; Teamsters; Laborers (n.e.c.). Table XI summarizes the number of persons in each major occupation group by sex, for the United States: 1940. Significance of the social-economic groups:
Taken
from “Comparative Occupation Statistics for the United States, I8 7 O to 1940“ by Dr. Alba M. Edwards: J Alba M. Edwards. "Comparative Occupation Statistics for the United States, 1870 to 1940." Bureau of the Census, Sixteenth Census of the United States: 1940. (Washington, D. C.: United States Government Printing Office, 1943)*
182 TABLE XVII (Designated Table XI by Edwards) EMPLOYED WORKERS, BY MAJOR OCCUPATION GROUP AND SEX, FOR THE UNITED STATES: 19*+0
Ma^jor Occupation Group
Employed Workers, lb Years Old and Over Total
Male
Female
Total
Employed (Except 3^,2 0 7 ,9 0 5 1 1 ,1 3 8 ,1 7 8 on emergency 1 0 0 .0 wo r k . .......... ^ 5 ,1 6 6 ,0 8 3 Total Pr of es s iona1 2 ,8 8 1,592 Workers Semiprofessional *+63 ,*+56 Workers Farmers and 5>lLK3?6l*+ Farm managers Proprietors, 3,7^9,287 managers, and officials, except farm Clerical, sales 7,517,630 and kindred workers Craftsmen, foremen, and kindred 5,055,722 workers Operatives and 8,252,277 kindred workers Domestic service 2,111,31*+ workers Service workers 3,*+ 58,33*+ except domestic Farm laborers l,92*+,890 (wage workers) and Farm foremen Farm laborers, 1,165,120 unpaid family workers Laborers, except 3,06*+,128 farm Occupational not 378,719 reported
Ma le Female 1 ,5 1 1 ,1 1 8 1,370,1+7*4
Per Cent Dis tribution Male
1 0 0 .0
Female
1 0 0 .0
F Total M 6 .*+ *+.*+ 1 2 .3
36V , 269
99,187
1 .0
1 .1
0.9
*+,9 9 1 ,7 1 5
151,899
11.*+
i*+.7
l.b
3 ,3 2 5 ,7 6 7
*+23,520
8 .3
9.8
3.8
^,3 6 0 ,6*4-8 3,156,982
16.6
12.8 2 8 .3
106,590
11.2
1^.5
6 ,2 0 5 ,8 9 8 2,0*4-6,379
18.3
18.2 18.*+
1*+2 ,2 3 1 1,969,083
b.7
0.*+ 17.l*
2 ,1 9 6 ,6 9 5 1,261,639
7.7
6.5 11.3
1,828,16*+
96,726
b.3
5.b
0.9
9*+l,8*+l
223,279
2.6
2.8
2.0
2,965,693
98,*+35
6.8
8.7
0.9
133,985
0.8
0.7
1.2
*+,9*+9,132
2*+*+, 73*4-
1.0
183 The preceding section defines and describes the dif ferent social-economic groups. The present section dis cusses their significance. The social-economic groups are something more than large subdivisions of the Nation1s labor force; and they are something more than mere summary groups con structed to facilitate the discussion of the broader aspects of the labor force. Each of them represents a distinctive part of the labor force— a part with its own peculiar characteristics and having its own peculiar significance. In forming these groups, industry lines were crossed and all of the workers who were doing pro ductive work requiring similar qualifications or who were performing services requiring similar qualifications were brought together into one large,-homogeneous group, without particular reference to the different occupations the workers were pursuing. So constituted, it is evident that each of these groups represents not only a ma^or segment of the nation's labor force, but, also, a large population group with a somewhat distinct standard of life, economically, and, to a considerable extent, in tellectually and socially. In some measure, also, each group has characteristic interests and convictions as to the numerous public questions— social, economic, and po litical. Each of them is thus a really distinct and highly significant social-economic group. The first of the social-economic groups— professional persons— is composed of the professionally trained workers. These, more than most other workers, are engaged in purely intellectual pursuits, as contrasted with other service pursuits and pursuits directly related to the production, exchange, or distribution of material goods. Professional persons, perhaps more than the workers in any other socialeconomic group, are pursuing their occupations primarily because of true professional interest in their chosen fields of work, rather than because of monetary or other considerations. Artists, authors, teachers, preachers, physicians, musicians, together with the other professional workers, plainly form a distinct social-economic class. Proprietors, managers, and officials form a very im portant and in many respects a very distinct socialeconomic group. They do most of the hiring and the "firing,11 they pay a relatively large proportion of the taxes, they largely control capital, they largely determine (in normal times) what the lines and the extent of production shall be,
184 and, with their assistants, they direct the work of a large portion of the other workers. It is evident that the standard of living of the proprietors, and their views on social and economic questions, frequently will be quite different from those of their employees. Clerks and kindred workers, frequently referred to as "white-collar workers,” form a large and rapidly growing class— a class between the usually better-educated and better-paid professional workers and the less welleducated but better-paid skilled workers. The skilled workers often belong to unions, and many of the professional persons belong to professional societies, but only a small proportion of the clerical workers are organized. As a class, they are not yet fully group conscious. Until recent years, and in many cases until the present, the relation of clerical workers to their employers has been largely a personal relation. But the clerical class is becoming group conscious, it is beginning to organize. When it becomes thoroughly group conscious and completely organized, it can exert a great influence on social and economic questions. The clerical worker, like many other workers, is dependent on others for his job— for the chance to earn a living. The average salary is only enough to meet the demands of a very moderate standard of living. Little is left for savings. He lives, all tod frequently— as do many other workers— face to face with the hazard of unemployment and with the risk of dependency in his old age. It is quite evident that his outlook on life and his stand on many of the social and economic problems of the day will be quite different from that of the proprie tor and may be considerably different from that of the professional man. The next group— "Skilled workers and foremen11— is composed of the most highly skilled of the manual workers— of craftsmen who have undergone an apprenticeship or who have become proficient in their trades, through extensive training on the job. They, perhaps, are more fully group conscious and are more fully organized than are the workers in any other social-economic group. Their work calls for higher qualifications, and they are more highly paid than are the persons in the next lower group of manual workers— the semiskilled— and, as a group, they are better paid, though less well educated than are the clerical workers. They constitute a very important social-economic group.
185 The "Unskilled workers" form a particularly significant social-economic group. Although the group has been chang ing in size more rapidly than any other group, and fortunately, has been decreasing, it nevertheless was considerably the largest of the social-economic groups in 194-0, when it included more than 1 in 4 of all workers. The group, though largest in size, ranks lowest, both in the social and in the economic status of the workers in cluded. The workers in this group are less well educated and more poorly paid than are the workers in any other group; and being lower in economic status than the workers in any other group, they most frequently suffer from un employment and become the subjects of relief. Inevitably, their vie?\rs on social and economic questions are in fluenced by their form of life and labor. Sufficiency of the social-economic groups as a scale. We need, we have, and we use a scale for measuring the " I.Q1* of individuals. We need a scale for measuring, if not the "I.Q.,11 at least the social-economic status of a group of workers, or of the workers of a community, or of a city or' of a state, or even of a country. And we need a scale for measuring the social-economic status of the large segments of a labor force, as, for example the workers of the different races of nationalities. Do the social-economic groups here presented constitute such" a scale? May they be used as a convenient yardstick for measuring and comparing groups of workers, or the workers of communities, of cities, of states, of races, etc? If not, then the work of those who have sought to develop these groups and to bring them into general use has been largely "love*s labor lost." Before proceeding with the presentation and analysis of the statistics, therefore, it is well that we examine the sufficiency of the social-economic groups as a scale of measurement. As the name states, there are social-economic groups. The workers in each group have been included partly be cause of their social and partly because of their economic status. The standard— if it be a standard— is thus a hybrid— partly social and partly economic. And the weight of the social factor varies from one group to another, and from one occupation to another, as does, also, the weight of the economic factor. Thus, the social factor is greater in the clerical group than in the skilled group, but the
186 reverse is true as to the economic factor, “Stenographers, typists, and secretaries,11 as a group, outrank plumbers socially, but not economically. Education is a very large factor in the social status of workers, and wage or salary income is a very large factor in their economic status. Unfortunately, data showing the education and the wage or salary income of the persons in each social-economic group are not available. These data are available, however, for the experienced workers (except public emergency workers) in each 1940 census major occupation group; and, with the exception of the three service groups, the major occupation groups correspond quite closely with the social-economic groups presented in this study. There fore, the 1940 figures for the major occupation forces, showing wage or salary income and years of school com pleted, are presented in Tables XXIV and XXV, insofar as these figures are available. The major occupation groups included in Table XXIV are confined to those which are rather closely comparable in content with the social-economic groups, of similar titles, and in which a large proportion of the workers receive wage or salary income. In the case of each major occupation group, there is a wide range in wage or salary income, and the model wage or salary group varies greatly from one major occupation group to another. Perhaps the groups can be compared most accurately through differences in median salary or wages received, as shown at the bottom of the table. In using the figures of Table XXIV, it must be recognized that some professional persons and a considerable proportion of farm laborers receive board, or board and lodging, as part of their pay. The figures presented in Tables XXIV and XXV, when considered together, indicate that the social-economic groups are arranged in this report in the descending order of the social-economic status of the workers, comprising them and that they do constitute a scale. A good test of whether or not the groups here pre sented constitute a practicable scale for measuring the social-economic status of groups of workers is the degree of success with which they have been so used. Although the grouping has been used quite extensively by Federal and other agencies and by individuals, only a few samples of its use will be referred to here.
TABLE m i l (Designated Table XXIV by Edwards)
TABLE XXIV.— WAGE CR SALARY INCOME RECEIVED IN 1939 BY EXPERIENCED WORKERS IN THE LABOR FORCE (EXCEPT THOSE ON P1BLIC EMERGENCY WCEK), IN SELECTED MAJOR OCCUPATION (BOUPS IN 1940, WHO WORKED 12 MONTHS IN 1939, FOR THE UNITED STATES _ _ _ _____________
WAGE CR SALARY
(Per cent not shown where less than 0.1)
CRAFTSMEN PROFESSIONAL & CLERICAL,SALES FOREMEN, & SEMIPROFESSION- & KINDRED KINDRED WGRKAL WORKERS WORKERS ERS Number
Per Number cent
Per Number cent
OPERATIVES & KINDRED WORK ERS
Per Number cent
FARM LABORERS AND FOREMEN
Per cent
Number ...
LABORERS, EX* CEPT FARM & MINE
Per Number cent
Per cent
Total reporting $100 or more.... 1,389,273 100.0 5,312,785 100.0 2,683,509 100.0 3,900,343 100.0 802,102 100.0 1,352,326 100.0 $100 $100 to $199...... $200 to $399...... $400 to $599...... $600 to $799...... $800 to $999...... $1,000 to $1,199.... $1,200 to $1,399.... $1,400 to $1,599.... $1,600 to $1,999.... $2,000 to $2,400.... $2,500 to $2,999.... $3,000 to $4,999.... $5,000 and over...
9,424 29,944 37,677 68,515 85,560 95,538 129,738 117,366 188,867 196,376 105,682 193,083 81,503
Median wage or salary income.......
$lJ803.05
0.7 2.2 2.8 5.1 6.4 7.1 9.7 8.8 14.1 14.7 7.9 14.4 6.1
24,513 99,354 228,570 621,563 701,151 709,246 723,662 551,352 637,128 553,025 187,021 209,986 66,214 $1,275.17
0.5 1.9 4.3 11.7 13.2 13.3 13.6 10.4 12.0 10.4 3.5 4.0 1.2
6,156 29,034 59,856 141,275 173,783 272,435 363,119 390,405 551,915 420,633 153,838 112,789 8,271
$1,551.69
0.2 1.1 2.2 5.3 6.5 10.2 13.5 14.5 20.6 15.7 5.7 4.2 0.3
20,436 109,457 269,292 657,315 508,691 5a,692 523,973 434,731 473,787 253,896 69,728 33,547 3,798
0.5 129,209 2.8 333,686 6.9 164,000 16.9 89,264 13.0 37,448 20,252 13.9 13.4 14,827 11.1 6,474 3,976 12.1 1,772 6.5 510 1.8 528 0.9 156 0.1
$1,142.14
$362.93 (
16.1 a.6 20.4 11.1 4.7 2.5 1.8 0.8 0.5 0.2 0.1 0.1 • ••••
18,375 89,609 144,984 243,410 200,022 223,675 205,502 119,239 80,096 20,584 4,218 2,105 507 $979.76
1.4 6.6 10.7 18.0 14.8 16.5 15.2 8.8 5.9 1.5 0.3 0.2 • ••••
TABLE XIX (Designated Table XXV by Edwards)
,
i TABLE XXV.— YEARS OF SCHOOL COMPLETED BY EXPERIENCED WORKERS IN THE LABOR FORCE (EXCEPT THOSE ON PUBLIC EMERGENCY WCEK), BY MAJOR OCCUPATION GROUP, FCR THE UNITED STATESs 194,0 (Figures based on a 5-percent cross-section sample)
YEARS OF SCHOOL COMPLETED7
PROFESSIONAL AND SEMIPROFESSIUNAL WORKERS Number
Total reporting... Grade school8....... Under 5 years8... 5 and 6 years...... 7 and 8 years....
Per cent 100.0
1
PROPRIETORS, MANAGERS, AND OFFI CLERICAL, SALES CRAFTSMEN, FORE FARMERS AND FARM CIALS, EXCEPT AND KINDRED MEN, AND KIND WORKERS MANAGERS FARM RED WORKERS Number Per Number Per Number Per Number Per cent cent cent cent 5,139,260 100.0 3,799,340 100.0 8,061,800 100.0 5,627,920 100.0
7.1 4,030,520
78.4 1,481,060
39.0 1,678},920
20.8 3,368,860
59.9
0.7 1,114,280 0,8 816,760 5.6 2,099,480
21.7 219,140 211,220 15.9 40.9 1,050,700
12rjo80 5.8 5.6 165!,680 27.7 l,392i,160
455,040 1.5 2.1 568,240 17.3 2,345,580
8.1 10.1 41.7
40.7 4,897,M O
60.7 1,997,720
35.5
High School.........
24.8
933,040
18.2 1,546,240
1 to 3 years..... 4 years..... .
6.3 18.4
587,200 345,840
11.4 6.7
650,680 895,560
17.1 l,6O3j,220 23.6 3,294,220
19.9 1,142,360 855,360 40.9
20.3 15.2
College............
68.1
175,700
3.4
772,040
20.3 1,485’,440
18.4
261,340
4.6
1 to 3 years....... 4 or more years,... Median school years completed...... ••••
loved to estimate attendance in counties ♦ The method employed to establish an objective value for the non-quantitative independent variable, contiguity, is ex haustively described by Ezekiel.^
Briefly: criteria were
established and a scale evolved to rate the counties in terms of the number of junior and senior colleges present in designated distances) in each count (Appendix B ) . counties were then sorted into four groups.
(or with The
The use of four
groups resulted from logical descriptive differences that ^ Mordecai Ezekiel, Methods of Correlation Analysis « Second Ed. (New York: John Wiley and Sons, Inc., 19bl) , pp. 3 0 2 - 1 1 .
218 appeared when the counties were sorted on the basis of con tiguity to a college.
Values were then estimated for college-
level attendance for each county for 194-0 by the same method used to estimate attendance for the states.
Each county
estimate was subtracted from actual attendance for 1940 and residuals (z1 , Tables X, XI, XII, and XIII) obtained.
The
net influence for the new variable (contiguity) was obtained by determination of the average of the residuals for each group.
These results were not accepted as the final effect
of contiguity on attendance until the problem of whether there was any correlation between the new factor and the factors previously used? or whether they were independent of each other? was considered.
This was done by sorting the
other factors according to the values used in sorting the counties (the same groups) and obtaining averages for each group,
A comparison of the averages of each of the other in
dependent factors used in prediction (Table XV) with the averages obtained for the four groups indicated no significant correlation.
(An index of correlation could be computed by
this method to indicate the degree of correlation if corre lation appeared at all probable by inspection.) Values obtained for contiguity (the average of the residuals for each group) were added to the original estimates made for the counties and new values obtained.
These final
estimates were again compared with actual attendance and a
219 2 new set of differences (residuals) obtained (z , Tables X, XI, XII, XIII)• 'values was
The standard error of estimate for the final .879 which compares favorably with the standard
error of estimate found for the estimates of attendance for 1910 to 19*+8.
(The mean for the estimate of college-level
attendance for all the counties without considering contiguity was 16,01 and the standard deviation was 3.068.) multiple correlation,
An index of
.956 (index of total determination,.91*0
was obtained to indicate the improvement in accuracy with which the dependent variable (college-level attendance) could be estimated.
TABLE XXIII THE INTERCORRELATION OF ATTENDANCE 18 TO 2b WITH ATTENDANCE 16 TO 17 AND THREE CLASSIFICATIONS OF THE MAJOR OCCUPATION GROUPS
List of Factors
(N - L8)
0 r Criterion— college level attendance 1 r Attendance, ages 16 to 17 2 = Proprietors and Managers, except Farm 3 = Semiskilled and Unskilled Workers *+ = Clerical sales, and Kindred Workers
1 0 1 2 3
.80181+9
2
3
1+
.757192
-.756139
.2 7 0 5 5 1
.761198
-.631297
.572127
-.677993
.553865 -.332853
This table reads: the correlation of factor #1 with the criterion is .757192. Factor #1 has a correlation with factor #2 of .677993? etc.
TABLE XXIV DETERMINATION OF THE BETA COEFFICIENTS FOR ESTIMATE, 1910-19^8
l
a1
2
3
1+
_„ M
mm» «■»
,_ M
-c
Check
mm
mmmmmm
*1 C1
1.000000 -1.000000
.761198 -.7 6 1 1 9 8
-.6 3 1 2 9 7 .631297
.572127 -.572127
-.8018^9 ,80l8*+9
.900179 -.9 0 0 1 7 9
a2
-*6 3 1 2 9 7
-.6 7 7 9 9 3 -.197^51 .32828*+
1.000000 .6oi*+6*+
-.332853 .028329 - .0*+7100
.756139 .2*+993*+
.113996 .682276
-.*+1551+3
-1.13*+359
1.000000 .671337 -1.000000
-.270551 .176^36 -.262813
1.522588 .975^36 -1 .1+52975
.553865
-.757192 -.0 9 8 3 2 8 .296632
.879878
b2 c2 a3 b3 c3 aif Cl^ a5 b5 c5
--—
.572127 ---
-.1 9 0 1 6 2 .761198 .331^81 ---
.553865 .127663
-1.000000 -.3 3 2 8 5 3 ...
---
1.000000 -1.000000
-.677993 ...
—
---
...
.233153 .703368
---
ro ro
H
222
TABLE XXV V VALUES FOR ESTIMATES, 1910-19^8
V1 V2 v3 % V-
-.80l81+9
.757192 •
1^6826
.06b?77 .098328
.756139 .21+9931+
-.270551
.188208 .176^36
223
TABLE XXVI Z VALUES FOR ESTIMATES 1910-19^8
1
Z -l
Z2
1 .0 0 0 0 0 0
.
2
3
1 .0 0 0 0 0 0
.>+20578
Z3
.355758
Z^.
.331^81
1 .0 0 0 0 0 0
.601>+6>+
b
1 .0 0 0 0 0 0
.672671 .671337
TABLE XXVII ABSOLUTE VALUES FOR ESTIMATES: 1910-1958
a
b
c
3 5
.10.3858 .056370
.357038 .253180 .206810
.029166
.1776M*
.652962
f
e
N-l N-m
Vm2 Km 1 2
d
R2
R
Test #
.357038 .25868*+
.65-2962 .75-1316
.801859
1
.216001
.783999 .810255
.860997 .885537
3 5
.900135
2
K2
1.000000 1.021739 l.oW+Mt 1.068182
g
.189756
5
BETA VALUES, Bi =
.567325
B2 = b3 =
.296632 .303128
B^ =
.319221
Multiple R = .90013? Coefficient of determination -
.810255 ro ro ■r
225
CHARACTERISTICS OF THE POPULATION USED IN PREDICTION OF ATTENDANCE FOR THE STATES AND FOR COUNTIES IN CALIFORNIA I.
Percentage of the age group 2 5 years and over who have attended one or more years of college*
2*
Percentage of the age group 16 and school*
17 attending
3*
Percentage of proprietorsi managers and officials in the employed labor force*
N-.
Percentage of semiskilled and unskilled workers in the employed labor force (including service workers other than domestic)*
5*
Percentage of clerical and kindred workers in the employed labor force*
226
TABLE XXVIII THE CORRELATION OF EACH FACTOR WITH COLLEGE-LEVEL ATTENDANCE (0) AND WITH EACH OTHER*
List of Factors
•V* 0
(N s **8)
College-level attendance
1 — Adult college-level attainment 2 - Attendance age 16 and 17 3 = Prop. Managers and Officials, except Farm b r Semiskilled and Unskilled Workers, including Service Workers 5 .. Clerical and Kindred Workers
0 1 2 3 b
1 .810851 ---
2. . .801866
3 .757192
-.687151
5 .2 7 0 5 5 1
.668^35
.792919
-.^558^5
.193116
.761198
-.501670
.572127
-.51659*+
.553865
---
---
---
-.182889
* The criterion (0) was the per cent of the age-group 18 to 2b inclusive attending school (college-level attendance)* Adult college-level attainment was expressed as a per cent of the population 25 years or older who had attended one or more years of college. Attendance age 16 and 17 was expressed as a percentage of the age-group 16 and 17. All other factors were expressed as per cent of the labor force.
TABLE XXIX DETERMINATION OF THE BETA COEFFICIENTS FOR STATE AND COUNTY ESTIMATE
l al t>l C1 a2 b2 c2 a3 b3 c3 ai+ c*+ a *> °5
2
1+
3
5
-c
Check
1 .38777*+ -1.38777*+
1.000000 -1.000000
.668*+35 - ,668*+35
.792919 -.7 9 2 9 1 9
-.*+558*+5 .*+558*+5
.193116 -.193116
-.8 1 0 8 5 1 .810851
-.i+558*+5
-.5 0 1 6 7 0
1.000000
-.1 9 6 9 6 7 .2V8631
-.51659*+ -.1551*+6 .1958*+1
-.1 8 2 8 8 9 -.09*+858
.687151 .317529 -.*+008i7
1.000000 .50*+223 -1.000000
.761198 .192609 -.3 8 1 9 9 2
-.5 0 1 6 7 0
.572127
—
— .668*+35 — —
—
---
—
---
.553865 .22193*+ -.368^17
•792919
.761198
1.000000
— -
--
—
---
.193116
-.185557 -1.000000
.792205 -1.000000
.119739
.030153 .662763 -.8 3 6 6 0 5 1.69822*+ .93 5372 -1.855076
-.801866
---
.572127 .*+19*+57 - .831888
-.182889
1.000000
-.270551 .07*+561 -.123772
1.86 5668 .898902
-.51659*+
-.757192 .O10*+28
1.83*+196
—
—
0 - Criterion (college attendance 18-2*+) 1 r Persons with 1 or more years of college (25 or more) 2 s Attendance age 16 and 17 5 r Clerical workers
.602*+07 -1.000000 .553865 --—
-.180917 •35880*+
—
.056198
3 = Prop. Managers and Offi cials *+ - Semiskilled and unskilled workers i\> ro -