70- 13,969
ALBAUM, Melvin, 19 36- AN ANALYSIS OF HUMAN FERTILITY BEHAVIOR IN SPATIAL SUB-SYSTEMS OF TURKEY.
The Ohio State University, Ph.D., 1969 Geography
University Microfilms, Inc., Ann Arbor, Michigan
•V Copyright by
Melvin Albaua
1970
THIS DISSERTATION HAS BEEN MICROFILMED EXACTLY AS RECEIVED AN ANALYSIS OF HUMAN FERTILITY BEHAVIOR
IN SPATIAL SUB-SYSTEMS OF TURKEY
DISSERTATION
Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University
By
Melvin Albaum, B.A., M.S.
The Ohio State University 1969
Approved b
AduAser Department of Geography ACKNOWLEDGEMENTS
There are many people who have, in one way or another, given valuable assistance to my graduate training and to this study. My sincere appreciation is extended to: Professor John
R. Randall, for his constant advice and willingness to assist me, in so many ways, during the past several years; Professor Emilio
Casetti, for his patience and ability to share his knowledge in such a meaningful manner; and, to Professor Edward J. Taaffe, who made much of this study possible by arranging a leave of absence
from teaching duties at The Ohio State University, in order to participate as CIC Scholar at the Population Studies Center of the
University of Michigan.
There are no words which can adequately express my grati
tude and sincere appreciation to Professor George J. Demko. He was
more than an adviser and teacher; he was a true friend when it
really counted. To George and Jeanette, what can I say?
I also wish to extend my appreciation to: Professor David
Goldberg, University of Michigan Population Studies Center, and to
Professor Brian W. Beeley, Department of Geography, Kent State
University. Both individuals provided some of the data sources and
Professor Beeley freely discussed some of the problems which I
ii encountered.
I would further like to thank, sincerely, Richard W.
Buxbaura, who put up with me and gave me a place to stay during my frequent consulting trips to Columbus.
My deepest gratitude goes to my family, who encouraged me to appreciate the value of learning and gave me constant moral support during some difficult periods.
Computer facilities were made available through grants at The Ohio State University and at the University of Kentucky, which are gratefully acknowledged.
ill VITA
July 13, 1936 ...... Born - New York, New York
I960 ...... B.A., Hunter College, City University of New York
1961-1964 ...... National Defense Graduate Fellow, Departi ment of Geography, University of Wisconsin, Madison, Wisconsin
1964 M.S., University of Wisconsin, Madison, Wisconsin
1964-1968 ...... Teaching Associate, Department of Geography, The Ohio State University, Columbus, Ohio
Fall Quarter, 1967 . . CIC Scholar to the Population Studies Center, University of Michigan, Ann Arbor, Michigan
1968-1969 ...... Assistant Professor, Department of Geography, University of Kentucky, Lexington, Kentucky
PUBLICATIONS
"Cooperative Agricultural Settlement in Egypt and Israel," Land Economics, Vol. XLII, May, 1966, pp. 221-226.
FIELDS OF STUDY
Major Field: Geography
Studies in Population Geography and Demography. Professors George J. Demko, Kent Schwirian, David Goldberg (University of Michigan).
Studies in Middle East. Professors John R. Randall, Sydney N. Fisher, Saad Nagi.
iv TABLE OF CONTENTS
Page acknowledgements ......
VITA ...... lv
LIST OF TABLES ...... vll
LIST OF MAPS ...... lx
LIST OF FIGURES ...... x
Chapter I. THE PROBLEM AND ITS BACKGROUND ...... 1
The Problem: Fertility Behavior In Turkey The Study Area Fertility Behavior and Regional Systems Overview of Chapters
II. DELINEATION OF A REGIONAL SYSTEM IN T U R K E Y ...... 27
Data and Variables Summary of Analytic Procedures Interpretation of Principal Axis Factor Analysis Grouping Analysis of Provincial Factor Scores Resulting Regional Sub-Systems Summary
III. HUMAN FERTILITY AND ITS CORRELATES IN TURKISH SUB-SYSTEMS...... 85
Introductory Statement Spatial Variations of Turkish Fertility Behavior Spatial Analysis of Fertility Correlates Summary
v IV. CONCLUDING STATEMENTS ...... 132
Results and Interpretations Implications Recommendations for Future Research Concluding Statement
APPENDIX ...... 151
BIBLIOGRAPHY ...... 153
vi LIST OF TABLES
Table Page
1. Variables Employed in Principal Axis Factor Analysis ...... * ...... 32
2. Results of the Principal Axis Factor Analysis of 69 Variables ...... 3 7 *
3. Factor I Loadings ...... 33
4. Factor II Loadings ...... 4 4
3. Factor III Loadings ...... 47
6 . Factor IV L o a d i n g s ...... 52
7* Factor V Loadings ...... 5 5
8 . Factor VI Loadings ...... 55
9. Factor VII Loadings ...... 5 6
10. Factor VIII Loadings ...... 57
11. Factor Scores by Province ...... 6 1
12. Regional Type Sub-Systems in Turkey: Provincial M e mbers ...... 79
13. Turkish Fertility Ratios for Entire Province (EP) and for Places With Less Than 10,000 Persons (PLT): 1955 and 1960 98
14. Means, Standard Deviations, and Ranges of 1960 Regional Fertility Ratios ...... 102
15. Correlation Analysis Results: Turkey ...... 106
16. Correlation Analysis Results; Region 1 * 1 0 9
17. Correlation Analysis Results: Region 2 ......
vii 18. Correlation Analysis Results: Region 3 112
19. Correlation Analysis Results: Region 4 ...... H 2
20. Correlation Analysis Results: Region 5 116
21. Correlation Analysis Results: Region 6 116
22. Correlation Analysis Results: Region 7 1 1 9
23. Correlation Analysis Results: Region 8 . 1 1 9
24. Multiple Correlation Analysis Results ...... 122
25. Correlation Coefficients of Fertility Ratios With Delineating Factors by Regions ...... 126
viii LIST OF MAPS
Maps Page
1. Turkey and Neighboring States ...... 5
2. Provinces of T u r k e y ...... 29
3. Distribution of Positive and Negative Scores: Factor I ...... 41
4. Location of Factors I and II P l o t s ...... 65
5. Location of Factors II and III P l o t s ...... 68
6 . Location of Factors II and IV P l o t s ...... 72
7. Location of Factors II and VIII Pl o t s ...... 75
8 . Delineated Regional Type Sub-Systems ...... 80
9. Turkish Fertility Ratios by Province - Contours of Linear+Quadratic+Cubic Trend Surfaces..... 92
10. Distribution of Positive and Negative Scores: Factor I I ...... 95
11. Turkish Fertility Ratios - Entire Province (1960) . . 96
12. Turkish Fertility Ratios - Places With Less Than 10.000 Persons ...... 97
ix LIST OF FIGURES
Figure Page
1. Plot of Factors I and 11 S c o r e s ...... 64
2. Plot of Factors XI and III S c o r e s ...... 67
3. Plot of Factors II and IV S c o r e s ...... 70
4. Plot of Factors II and VIII S c o r e s ...... 74
x CHAPTER I
THE PROBLEM AND ITS BACKGROUND
The Problem: Fertility Behavior In Turkey
Introduction
This study Is a spatial analysis of the correlates of human fertility behavior within a system of regional types in the Republic of Turkey. Two basic objectives motivate this study: the first, to Identify spatial variation of fertility behavior and primarily, the spatial variation of Its correlates; the second, to systematic ally delineate, on the basis of a multivariate approach, regional type sub-systems in which such behavior takes place and can be analyzed.
The problem, therefore, is partially related to the conceptu alization and investigation of a basic component of demographic behavior - human fertility - and partially related to the concept of regionalization. The delineation of regions and the taxonomlcal clustering of areal units in a regionalization scheme may be valid in itself; however, regionalization for the sake of regionalizing leaves little accomplished but a set of neatly drawn boundaries.
It is the purpose here to take the regionalization framework a step
1 2 further in order to Integrate demographic behavior correlates with sub-systems of regional types.
Objectives of the Study
This study Is Intended to provide some insight related to the spatial variation of fertility and its most significant correlates.
It is concerned with the uneven spatial distribution of fertility ratios in a developing Middle Eastern country - the Republic of Turkey - utilizing a firm basis for the placement of boundaries delineating
"regional types". With the development of electronic computers cap able of handling more sophisticated statistical models, it has become possible to carry out the classification of areas by means of a sim ultaneous analysis of a large number of variables, resulting In a set of possible regions or regional types.
Human fertility may be regarded as a product of behavior motivated in some measure by the ideas, interests, desires, and at
titudes which people acquire through collective living. Decisions are made with respect to having a family and the size of the family
one is to have. The effort here is to measure, with some precision,
the extent to which behavioral diversity among people in regional
type sub-systems is associated with specific features of regional
organization and structure.
In accordance with the basic purposes and objectives set 3 forth for this study, the following questions are posed. These questions form the Investigative core of this study and the basis for the formulation of several hypotheses; their answers fora the basis of the study's results and the acceptance or rejection of the hypotheses*
(1) On the basis of Interrelated and Interdependent social,
economic, and demographic characteristics of areal
units within the larger system of Turkey, what are the
regional types or sub-systems which emerge?
(2) What spatial patterns and variations In human fertility
behavior exist in Turkey? Do these spatial patterns
and variations relate to tie delineated system of re
gional types?
(3) What are the major correlates of this fertility behavior
in the larger system and in each of the sub-systems? Are
these correlates similar within all sub-systems?
(4) What is the explanatory strength of these correlates?
Do they explain fertility behavior in a similar way in
all regions, or are there significant regional variations
in their explanatory strength?
Proposition: The Republic of Turkey, treated as a spatial system, is
composed of sub-systems which can be identified as "re— 4
glonal types” on the basis of specific features of
organization and structure within the larger system.
Hypotheses: Reproductive behavior is a response influenced by and
derived from certain inherent characteristics of a
sub-system (region) within a larger system. The spatial
variations of this behavior can be associated with the
spatial variations of these characteristics.
Spatial variations of fertility correlates cocist from
one sub-system to another, both in the variables them
selves and in their explanatory power.
The Study Area
The Republic of Turkey, with a population of over 34 million people, represents a rather appropriate study area for the problems associated with regionalization, as well as fertility behavior. Within
the span of a few decades, Turkey has attempted to move from the “tradi
tional" to the "modern” form of society, resulting in rapid change 1 economically, socially, and even politically. These changes, associ-
1 Several studies which treat this subject are: B. Lewis, The Emergence of Modern Turkey (London: Oxford University, 1961); Z. Y. Hershlag, Turkey: The Challenge of Growth (Leiden: E.J. Brill, 1968); M.D. Rivkin, Area Development for National Growth: The Turkish Precedent (New York: Frederick A. Praeger, 1965); R.D. Robinson, The First Turk ish Republic: A Case Study in National Development (Harvard University, 28 34 40
40
Iran
m m Iraq Ada MILES too Syria
MEDITERRANEAN SEA REPUBLIC of TURKEY
HAT 1: TtiSKET AMD HEIGHEOMHG STATES 6 ated with development, have had a profound effect on numerous parts of the country and have created a whole new structure of spatial patterns and spatial organization. Unfortunately, due to the lack of adequate data, spatio-temporal changes which have occurred in the past are difficult to analyze, except for the most recent period when data collection and policy formulation became systematized.
The changes which have occurred and which are occurring in Turkey have had an Impact on the entire country. Nevertheless, much of Turkey still remains unaltered by the progress of develop ment and the vast majority (almost 70 per cent) of the Turks live in farm communities of less than 5,000 persons. A sizeable portion of the Turkish population still live on the marginally productive agricultural lands of the eastern provinces. Low Income levels, poor sanitary facilities, illiteracy, inadequate communications links, and other facets of an undeveloped environment still is a way of life for millions of Turks.
For centuries, Istanbul (Constantinople) represented the dominant center of Ottoman and Turkish culture and development.
1963); N. Eren, Turkey Today and Tomorrow (New York: Frederick A. Prae- ger, 1963); A.M. Kazanlas, Education and the Quest for Modernity in Turkey (Chicago: University of Chicago, 1966); J. Kolars, Tradition, Season, and Change in a Turkish Village, Research Paper No. 82, Depart ment of Geography, University of Chicago, 1963; F. Shorter (ed.), Four Studies on Economic Development in Turkey (London: Frank Cass, 1967V". It was, and to a large degree still remains, the pivotal point from which much of socio-cultural and economic phenomena had dif fused. In addition to its function as the political center of the empire, its strategic location on the Bosphorus Straits and its proximity to European influence afforded it with the accessibility
to ideas and Innovations few Turkish centers have been able to achieve in Turkish history. As a result, spatial patterns which would emerge from an analysis of selected data might reflect a
rather strong east-west orientation or dip. However, this may no
longer be the complete case. Although Istanbul has been a dominant
primate city, the role of Izmir has been of great importance In
the provincial areas of southwestern Turkey. Ankara, since its
role of national capital was bestowed in the 1920's, has emerged
as one of the fastest growing urban areas in Turkey, both in popula
tion size and in national Influence. The greatest impact of this
growth and development of Ankara has been, obviously, in the central
Anatolian hinterland of the city. The rapidly urbanizing and in
dustrializing areas along the Black Sea and Mediterranean coasts
have, likewise, had their regional Impacts.
Because Turkey is a developing country, it represents a
classic example of an economic system with many dualisms in its
structure. Each province, or group of provinces are at different
stages of development, in addition to being differentially endowed 2 with varying resource bases. Economic growth and capital expendi tures have not been uniformly distributed throughout Turkey. Changing patterns in agriculture and in mineral exploitation have occurred as 3 a related factor of development.
As a result of recognized internal variations In economic structure, social organization, and developmental levels, the need for a systematic regionalization scheme for Turkey appears to be great. Few attempts have been made in delineating Turkish sub
systems of regional types or uniform regions, and only with partial
success with the utilization of either a single selected variable 4 or a very small number of selected variables. The delineation of
these regional boundaries and the classification of Turkish provinces,
as expected, has varied in each case. The first Turkish Geographical
Congress, in 1941, for example, divided the country into seven "natural* 5 regions. The Turkish government uses an arbitrarily derived system
2 See, R.Y. Keleg, Regional Disparities in Turkey (Ankara: Ankara University Faculty of Political Science, 1964).
% . Ol^en, "The Geographical Distribution of Public Invest ments," Planning in Turkey, ed. S. Ilkin and E. Inan^ (Ankara: Mid dle East Technical University, 1967), pp. 274-78.
^See, for example: S. Erin^ and N. Tun^dilek, "The Agri cultural Regions of Turkey," GR, Vol. 42, 1952, pp. 179-203; E.C. Semple, "The Regional Geography of Turkey: A Review of Banse's Work," GR, Vol. 11, 1921, pp. 338-50; B. Helling and G. Helling, Rural Turkey: A New Socio-Statistical Appraisal (Istanbul: Istanbul University, In stitute of Economics and Sociology Pub. No. 102, 1958).
^Turk Cografya Kongresi Kltabi (Book of the Turkish Geographical Congress) (Ankara: Turkish Geographical Congress, 1941). 6 made up of eight "geographic" regions, and the recently created
Turkish Demographic Survey project utilizes a system delineating 7 five "administrative" regions. There has not yet been any attempt made to delineate regional types, based on multiple variables, in a systematic way, for the Republic.
One of the most Important applications of a regionalization system for Turkey Is in its use for the study of spatial patterns; and, there are several important reasons for looking at spatial patterns in Turkey within the regional context. One, is that regional comparisons can be made, especially within the framework 8 of a general theory of spatial behavior. Another important reason is that it permits comparisons between regional and national spatial systems. Agricultural wealth, for example, varies so greatly from one area to another in Turkey, comparisons on a national basis are extremely distorting if not almost completely meaningless. Another example is population density, which can have quite a different in
fluence and meaning in different spatial contexts.
^Genel Nufus Saylmi (Census of Population) (Ankara: State Institute of Statistics, 1964).
^N.H. Fi^ek, Y. Heperkan, and J. Rumford, The Evolution of the Turkish Demographic Survey (Ankara: Turkish Ministry of Health and Social Welfare, 1960). (Mimeographed).
®See, B.J.L. Berry, "A Synthesis of Formal and Functional Regions Using a General Field Theory of Spatial Behavior," Spatial Analysis, ed. B.J.L. Berry and D. Marble (Englewood Cliffs: Prentice Hall, 1968), pp. 419-28. 10
It has been argued by some scholars that the region Is 9 the context of a considerable proportion of spatial behavior.
This appears to be a justifiable argument when made applicable 10 to the Republic of Turkey* Weiker has noted this with regard to population movement. In addition, he further supports the
Importance of the notion of functional regions by illustrating such factors as the growing importance of the provincial press and the growing network of feeder roads from villages to towns and cities. These roads enable large numbers of villagers to travel, but not too far. He argues that despite strong influences
from a more national level, a local or regional view remains an
important one for many Turks, resulting in varying regional spatial behavior. This argument would tend to support the general notion
that sub-systems of spatial networks result in sub-systems of
spatial behavior patterns.
With progress made in economic and social development,
the crucial problems within the Republic lie with the growth of
its population - a fact which bears heavy consequence on any
^B.J.L. Berry, "Interdependency of Spatial Structure and Spatial Behavior: A General Field Theory Formulation," FRSA, Vol. 21, 1968, pp. 205-6; B.J.L. Berry, Essays on Commodity Flows and the Spatial Structure of the Indian Economy, Research Paper No. Ill, Department of Ceography, University of Chicago, 1966; G. Olsson and S. Gale, "Spatial Theory and Human Behavior," PRSA, Vol. 21, 1968, pp. 229-42.
^W.F, Weiker, "Growth Patterns of Some Turkish Provincial Capitals," Paper presented to American Political Science Association Meeting, 1968. attempted planning process. An analysis of the fertility behavior in Turkey may provide adequate information for planners, government social and educational agencies, and for optimum resource utilization.
The Turkish government’s concern with the impact of rapid population growth on the environment, economic development, social and family affairs, and migration at the regional and national levels, is aptly reflected by the recent surveys, population planning programs, and other related actions taken by the national legislature. Thus, the practical applications of information gained in this type study are numerous. On the theoretical side, variables identified as influ encing or explaining fertility behavior within the sub-systems of
Turkey can facilitate, perhaps, the building and construction of potential models of spatial behavior under given constraints. This too, may have practical applications in the area of population plan ning strategy.
Shorter**1 has observed that fertility patterns within
Turkey are such that it would be expected that European fertility norms and practices were in the process of being diffused. However, he further states that this is probably not the case, suggesting that differentials which exist between the sub-systems in Turkey might be part of a "permanent" rather than transitional spatial pattern. Therefore, given the situation of a "static" spatial pattern,
H f .C. Shorter, Information on Fertility, Mortality, and Pop ulation Growth in Turkey (Ankara: Hacettepe University Institute of Population Studies, 1968), pp. 25-26. (Mimeographed). 12 the sub-systems within Turkey afford this study and its objectives with an ample setting for Investigation.
Fertility Behavior and Regional Systems
Too often, investigations of human fertility have been attempted on either the macro-level, involving vast generalizations of entire countries or major world regions; or, on the micro-level, emphasizing demographic behavior in an isolated case study of certain villages or cultural groups. In either approach, the shortcomings appear to be more numerous than the threshold of validity might
permit. At the macro-level, we often must take Into account the regional variations of such factors as economic development (or the
lack of such), the advancement of social institutions, accessibility
of information and innovation, etc. At the micro-level, what may
be applicable in one or two isolated villages may well be the “unique"
case and may be inappropriate or inapplicable to neighboring areas.
Hence, the isolated case study often falls short of being an appro
priate model for other areas, even in the same cultural group.
One method of alleviating some of these problems is through
the utilization of a regional system, in which areal units are
grouped together with respect to a set of characteristics, maximizing
similarities. The resultant clusters of areal units may produce a
system of either uniform regions or regional types, depending on 13
spatial contiguity. Obviously there are several shortcomings which may arise from utilizing this type of system for analyzing behavior, e.g., urban-rural differences. Nevertheless, it is a
sound, objective attempt to formulate what may be termed a geo
graphic compromise*
The concept of a system of regions - be they uniform regions
or regional types - may well be analogous to the whole notion and 12 theory of general systems. On the other hand, human fertility may be approached through this same notion of general systems analysis*
It is becoming more and more apparent from recent work that human
fertility is a likely response to the action - inputs and outputs - 13 to and from the system, which exists within and between social systems.
Reproductive Behavior - The Study of Human Fertility
The study and interest in human fertility has received wide
spread attention in recent times. The interest In human fertility,
however, was displayed long before the contemporary trend. The concern
with population numbers and optimum population size can be found in
^See, J.R. Borchert, "Geography and Systems Theory," Problems and Trends in American Geography, ed . S.B. Cohen (New York: Basic Books, 1967), pp. 264-72. For a general discussion of systems analysis, see: V.F. Buckley, Modern Systems Research for the Behavioral Scientist (Chicago: Aldine, 1968); and, F.K. Berrien, General and Social Systems (New Brunswick: Rutgers University, 1968).
provocative treatment of this is given in J.M. Beshers, Population Processes In Social Systems (New York: The Free Press, 1967). 14
14 the writings of Plato, Aristotle, and other ancient scholars.
Even the contemporary theories which are currently being put to test can be often traced to the early writings of Confucius and 15 his school, which gave much attention to checks on population growth. Ibn Khaldun, a fourteenth-century Muslim author, expounded
In detail a theory of cyclical variations of population and its 16 relation to economic, political, and socio-psychological conditions.
Human fertility, as a behavioristic response to a given socio-economic, psychological, and political environment, has its theoretical founda tions in many of these early commentaries. It is only in the recent period that this behavioristic response has been put to test with renewed vigor in a theoretical framework.
It must be recognized that much of the work concerned with human fertility has been in response to the classic work of Malthus, whose provocative essays stimulated a renewed dedication and commit- 17 ment to the analysis and examination of fertility. In his early
^For an interesting discussion of the views of Plato and Aristotle on this subject, see, United Nations, Population Division Studies No. 17, The Determinants and Consequences of Population Trends (New York, 1953), p. 22.
15C. lluang-Chang, The Economic Principles of Confucius and His School (New York: Hafner, 1911), Vol. I.
^**See, N.A. Quadir, "The Economic Ideas of Ibn Khaldun," Indian Journal of Economics, Vol. 22, 1942, pp. 898-907; and, C. Issawi, An Arab Philosophy of History (London: Cambridge University, 1950).
■^T.R. Malthus. An Essay on the Principle of Population (London: Reeves and Turner, 1798). A total of seven revised editions were Issued between 1803 and 1834. 13 essay, one might have considered Malthus to have been somewhat radical in his strong environmental deterministic approach. How ever, in later editions, Malthus appeared to modify his original thinking and incorporated such notions cs contraception and fertility control.* , 18
It was not until recently that himan fertility analysis was subjected to analogous models and population growth fitted to logistic 19 curves. It has only been a few years since human fertility has become a problematic component in population dynamics - for it Is only in the last several decades that human mortality rates have declined substantially - resulting In growth rates at an unprecedented 20 level in human history. What has become the critical aspect of
18 There are various commentaries on the Malthusian essays. See, for example, G.F. McCleary, The Malthusian Population Theory (London: Faber and Faber, 1953); and, D.V. Glass, ed,, Introduction to Malthus (New York: John Wiley and Sons, 1953). 19 Some of the pioneer studies are: R. Pearl and L.J. Reed, "On the Rate of Growth of the Population of the United States Since 1790 and Its Mathematical Representation," Proceedings, National Academy of Sciences, Vol. 6 , 1920, pp. 275-88; R. Pearl, Studies in Human Biology (Baltimore: William and Wilkins, 1924); R. Pearl, L.J. Reed, and J.F. Kish,"The Logistic Curve and the Census of 1940," Science, Vol. 92, 1940, pp. 486-88; D.G. Kendall, "Stochastic Processes and Population Growth," Journal, Royal Statistical Society, Vol. 11, 1949, pp. 230-64; E.B. Wilson and R.R. Puffer, "Least Squares and Pop ulation Growth," Proceedings. American Academy of Arts and Sciences, Vol. 6 8, 1933, pp. 287-382; and, S. Vianelli, "A General Dynamic Demographic Scheme and Its Application to Italy and the United States," Econometrlca, Vol. 4, 1936, pp. 269-83. 20 See, K. Davis, "The Amazing Decline in Mortality in Under developed Areas," American Economic Review, Vol. 46, 1956, pp. 305-18. See also, M. Spiegelman, "Longevity and Mortality in the American Pop- 16 fertility studies is not the detremental effect of over-population itself, but the factors which are directly related to differential fertility rates. The interest of scholars has been directed toward identifying, describing, and analyzing the effect of various econ omic, social, and cultural variables which relate to the reproductive 21 behavior of human belnga.
Much of what is known today is derived from the data and 22 experience of the Western culture groups. There is much which remains unknown or unclarified with regard to the variables which
ulation," Population: The Vital Revolution, ed. R. Freedman (Chicago: Aldine, 1964).
21 The recent investigations in this area are extensive in number and scope. A continuous bibliographic listing is given in the volumes of Population Index, published by the Office of Popula tion Research, Princeton University. An example of some of thia literature is: S. Friedlander and M. Silver, "A Quantitative Study of the Determinants of Fertility Behavior," Demography, Vol. 4, 1967, pp. 30-70; R.A. Easterlin, "Towards A Socio-Economic Theory of Fertil ity: Survey of Recent Research on Economic Factors in American Fertil ity," Fertility and Family Planning (Ann Arbor: University of Michigan, 1967). Some of the classic studies on this subject are: P.K. Whelpton and C.V. Kiser, eds., Social and Psychological Factors Affecting Fer tility, Vols. I - V (New York: Milbank Memorial Fund, 1946-1958); F. Lorimer, Culture and Human Fertility (Paris: UNESCO, 1954); and, K. Davis and J . Blake, "Social Structure and Fertility: An Analytical Framework," Economic Development and Cultural Change, Vol. 4, 1956, pp. 211-35. 22 The most formidable body of literature has been in the treatment of the theory of the demographic transition. An excellent summary of this theory and bibliographic references can be found in W.C. Robinson, "The Development of Modern Population Theory," American Journal of Economics and Sociology, Vol. 23, 1964, pp. 375-92. 17
effect the non-Western groups. It Is highly feasible that similar behavioristic responses may be found among all cultural groups, al- 23 though there is much doubt cast on this view. What is of interest,
nevertheless, is how various factors cause or Influence various
responses in a spatial context. It is apparent that the spatial variation of fertility behavior is related to the spatial varia
tion of certain variables, resulting in a significant areal associa
tion with high, declining, or low fertility rates. For example,
recent KAP (knowledge, attitude, and practice) studies of contra
ceptive device utilization, carried out in various parts of the 24 world, support this.
Studies which have been devoted to analyzing fertility
differentials and fertility correlates have, for the most part,
been carried out by sociologists. Although many of these studies
have identified significant differences between urban and rural
groups, religious, and socio-economic groups, their emphasis has
23 Some provocative empirical results may be found in: I.B. Taeuber, "Japan’s Demographic Transition Re-examined," Population Studies, Vol. 14, 1960, pp. 28-39; J. Abu-Lughod, "Urban-Rural Differences as a Function of the Demographic Transition: Egyptian Data and an Analytical Model," American Journal of Sociology, Vol. 39, 1964, pp. 476-90; A.O. Zarate, "Fertility in Urban Areas of Mexico: Implications for the Theory of the Demographic Transition,” Demography, Vol. 4, 1967, pp. 363-73. 24 See, W.P. Mauldin, "Fertility Studies: Knowledge, Atti tude, and Practice,” Studios on Family Planning, No. 7, The Popula tion Council, 1965. 18 been primarily societal in scope. Those studies which have given attention to the spatial variations have been relatively few In number, especially in the empirical testing of spatial models.
Recently, several geographers have treated the spatial aspect of declining fertility as a diffusion process and have presented some 25 empirical support for their mathematical models.
The Regional Concept and Regionalization
The concern with spatial structure and spatial organization,
together with their interrelationships, has been at the core of geo
graphy since the discipline evolved. Geographers of the past and
those of the present have attempted to classify segments of the 26 earth’s surface into regional types and regional systems. Now,
with the advances in the social and behavioral sciences, geographers
have started to develop mathematical models of spatial patterns,
Some recent examples of this research are: E. Casettl and G.J. Demko, "A Diffusion Model of Fertility Decline: An Application to Selected Soviet Data - 1940-1965," Discussion Paper, Department of Geography, The Ohio State University, No. 5, 1969; R. Chung, "Space- Time Diffusion of the Transition Model: The Twentieth Century Patterns," Paper presented to the Population Association of America Meeting, 1966; and, M. Albaura, "A Spatial Analysis of the Demographic Transition Model," Paper presented to the Southeast Division Meeting, Association of Amer ican Geographers, 1968. For a conflicting point of view regarding the diffusion process and fertility, see, G. Carlson, "The Decline of Fertility: Innovation or Adjustment Process," Population Studies, Vol. 20, 1966, pp. 177-93.
2 fk See, D. Whittlesey, "The Regional Concept and the Regional Method," American Geography-Inventory and Prospect, ed. P.E. James and C.F. Jones (Syracuse: Syracuse University, 1954), pp. 21-68. 19 resulting in new trends and innovations within the discipline, 27 which have long been absent. Over the past decade and a half,
a directed interest in the parameters of spatial Interaction has
elicited a broad range of research. Innovative works, such as
those of Garrison, Berry, Hagerstrand, and others, have been
amplified and extended, developing a new body of substantive lit- 28 erature, complimenting work in other disciplines.
The importance of aggregating areal units into regions for the study of spatial structure involving both patterns and 29 linkages, has been clearly acknowledged in the literature.
There is abundant evidence which attests to the significance of regions as distinctive subdivisions of the larger whole. This
27 See, for example, Berry and Marble, Spatial Analysis, op. c i t .; R.J. Chorley and P.J. Haggett, Models in Geography (London: Methuen, 1968); R.J. Chorley and P.J. Haggett, Locational Analysis in Human Geography (New York: St. Martin's, 1966); and, W. Bunge, Theoretical Geography (Lund: Gleerup, 1960). 28 An excellent bibliography of the major innovative works can be found in the works cited in the preceding footnote. See also, the recent text of L.J. King, Statistical Analysis in Geography (Engle' wood Cliffs: Prentice Hall, 1969); and, The Science of Geography: Report of the Ad-Hoc Committee on Geography (Washington: National Academy of Sciences - National Research Council, 1965). 29 D. Whittlesey, op. cit.; R. Hartshorne, Perspective on the Nature of Geography (Chicago: Rand McNally, 1959); and, for an interesting treatment of the regional concept and its role in geo graphy, see, R. Minshull, Regional Geography - Theory and Practice (Chicago: Aldine, 1967). 20 demonstration of heterogeneity among regions represents only partial verification of the significance of regionalization* Of equal importance is the need to demonstrate homogeneity within the spatial structure of the region. Although this latter problem had been somewhat neglected in the past, recent research has given 30 new insight to this taxonomical problem.
There appears to be some neglect in current geographic research, toward identifying certain regional features which appear to be most significantly related to behavioral differences among the inhabitants of the various regions. The whole notion of the interaction of groups of individuals, as reflected by aggregate behavioral patterns, and its interdependency on the structure of areas, as defined by a given set of selected characteristics of 31 these areas, has been clearly stated by Berry. Tn an earlier study, Berry carried forth this notion and utilized the basic ideas of general field theory in order to integrate formal and functional 32 regions.
^®B.J.L, Berry, "A Method for Deriving Multi-Factor Uniform Regions," Frzeglad Geograflczy, Vol. 33, 1961, pp. 262-82; B.J.L. Berry, "Approaches to Regional Analysis: A Synthesis," AAAG, Vol. 54, 1964, pp. 2-11.
■^B.J.L. Berry, "Interdependency of Spatial Structure and Spatial Behavior," op. cit., pp. 205-6.
^B.J.L. Berry, "A Synthesis of Formal and Functional Regions," op. cit* 21
The question of regions per se, their delineation and
characteristlcs, and methodological procedures has been researched by a number of scholars in geography and in related disciplines,
utilizing various statistical procedures and techniques. One of
the first examples of experimentation with statistical procedures
for delineating regions, was Kendall's pioneering work on the 33 distribution of crop productivity in Great Britain. This was
followed shortly by the innovative studies of agricultural regions 34 35 of the United States done by Hagood. The work of Odum, that 36 37 of Mangus, and Bogue's investigations, all added to the growing
literature on regionalization. One of the classic statements to 38 be found is in the work of the National Resources Planning Committee,
33 M.G. Kendall, "The Geographical Distribution of Crop Pro ductivity in England," Journal, Royal Statistical Society, Vol. 102, 1939, pp. 21-62.
^M.J. Hagood, N. Danilevsky, and C.O. Beuni, "An Examination of the Use of Factor Analysis in the Problem of Sub-Regional Delinea tion," Rural Sociology, Vol. 6, 1941, pp. 216-33; and, M.J. Hagood, "Statistical Methods for Delineation of Regions Applied to Data on Agriculture and Population," Social Forces, Vol. 21, 1943, pp. 287-97.
Odum, Southern Regions of the United States (Chapel Hill: University of North Carolina, 1936). 36 A.R. Mangus, Rural Regions of the United States (Washington: U.S. Government Printing Office, 1940).
J D.J. Bogue, "An Outline of a Complete System of Economic Areas," American Journal of Sociology, Vol. 60, 1954, pp. 136-39.
3®United States National Resources Committee, Regional Factors in National Planning and Development (Washington: U.S. Government Printing Office, 1935), Chapter 12. 22 which regarded regions as areas exhibiting homogeneity in one or more aspects. They interpreted regional homogeneity not as an
abstract, or artificial construct imposed arbitrarily by roan, but
rather as:
...a spontaneous expression of physical and psychological differences. Regions are genuine entities, each of which expresses both natural and cultural differeni-iation from its neighbors. 39
It should be noted that this interpretation of regional homogeneity
contrasts with the contemporary prevailing notion among geographers.
There appears to be a substantial number of studies which
deal with '’regionalism1', especially as a concept applied to various 40 aspects of American culture. Unfortunately, those scholars who
have contributed to this body of literature appear to have given
little in the form of a clear and concise statement of their 41 theoretical position.
In the post World War II period, attempts to develop simpler
3 9Ibid., p. 141.
^®See, for example, M. Jensen (ed.), Regionalism in America (Madison: University of Wisconsin, 1951), which is a volume of published papers which were delivered at a symposium on American regionalism in 1949, at The University of Wisconsin, Madison.
*lRor some interesting critical comments on this subject, see, D.W. Varley, A Quantitative Analysis of Regionalism in the United States, 1940 (unpublished Ph.D. dissertation, Department of Sociology, University of Michigan, 1956), Chapter I. 23 statistical procedures defining and delineating regions were 42 43 made by such geographers as Weaver and Zobler. With the development of modern high-speed electronic computers, computa- 44 tlonally demanding methods proposed by Kendall began to be used and extended. Berry first Introduced the application of factor 45 analysis and discriminatory analysis to regionalization, and later added such techniques as dimensional analysis and grouping methods - including a technique of grouping in which contiguity could be added 46 as an additional constraint - for delineating regions. These 47 48 methods were later used by such geographers as King, Thompson,
^J.C. Weaver, "Crop Combination Regions in the Middle West," GR, Vol. 44, 1954, pp. 175-200.
« L . Zobler, "Statistical Testing of Regional Boundaries," AAAG, Vol. 47, 1957, pp. 83-95.
^ M . G . Kendall, A Course in Multivariate Analysis (London: Charles Griffin, 1937).
Berry, "An Inductive Approach to the Regionalization of Economic Development," Essays on Geography and Economic Develop ment , Research Paper No. 6 8, Department of Geography, University of Chicago, 1961, Part VIII.
^Berry, "A Method for Deriving Multi-Factor Uniform Regions," op. cit.; and, Berry, "A Synthesis of Formal and Functional Regions," op. c i t .
^L.J. King, "Cross-Sectional Analysis of Canadian Urban Di mensions: 1951-1961," Canadian Geographer, Vol. 10, 1966, pp. 205-24; and. L.J. King, "Discriminatory Analysis of Urban Growth Patterns in Ontario and Quebec, 1951-1961," AAAG, Vol. 57, 1967, pp. 566-78.
A Q J.H. Thompson, S.C. Sufrin, P.R. Gould, and M.A. Black, "Toward a Geography of Economic Health: The Case of New York State," AAAG, Vol. 52, 1962, pp. 1-20. 24
49 Ahmad, and several others, and extended methodologically by 50 such geographers as Casettl. In other disciplines, scholars 51 52 53 such as Russett, Moser and Scott, Hadden and Boigatta, 54 and Adelman and Morris, used similar analytic techniques In dealing with their respective classlficatory problems. Recently,
King has brought together much of the work which has been done In this research area, citing numerous works and giving mathematical 55 derivations for the procedures used.
49 Q . Ahmad, Indian Cities: Characteristics and Correlates, Research Paper No. 102, Department of Geography, University of Chicago, 1965.
^E. Casetti, Multiple Discriminant Functions, Technical Re port Ho. 11, and Classificatory and Regional Analysis by Discriminant Iterations, Technical Report No. 12, Department of Geography, North western University, 1964. (Mimeographed).
Russett, International Regions and the International System: A Study in Political Ecology (Chicago: Rand McNally, 1967). 52 C.A. Moser and W. Scott, British Towns: A Statistical Study of Their Social and Economic Differences (London: Oliver and Boyd, 1961). 53 J.K. Haddan and E.F. Borgatta, American Cities: Their Social Characteristics (Chicago: Rand McNally, 1965).
5^1. Adelman and C.T. Morris, "A Quantitative Study of Social and Political Determinants of Fertility," Economic Development and Cultural Change, Vol. 24, 1966, pp. 129-57.
^Se e , L.J. King, Statistical Analysis in Geography, op. cit. especially Chapter 8, which deals with classification and regional ization problems. For a review of some of the classificatory tech niques, see Chapter 7, which deals with principal components and factor analysis in geographic research. 25
Overview of Chapters
In this chapter, the Introduction to the study has been presented. A discussion of the regional concept and recent method ological development, regional systems and fertility behavior, has been given, integrating the relevant literature. The objectives of the study are explained and the background of the study area and its suitability for this study are also stated.
Chapter II is concerned with the delineation of regional
type sub-systems for the Republic of Turkey. After a short dis cussion of the data and variables used, an explanation of the multivariate statistical procedures used to delineate the sub
systems, is given. The results of the principle axis factor
analysis Is presented, followed by an interpretation of the di mensions created by the factor loadings. Plots of factor scores
on selected dimensions are made and interpretations discussed.
The grouping algorithm is explained briefly, and the results and
interpretations - delineating a system of regional types - is
presented.
Chapter III examines human fertility behavior and its
correlates within the Turkish sub-systems, as well as for the
larger system of Turkey. In the introductory statement, a dis
cussion of previous research findings is presented, and the "fertility 26
ratio" measurement Is explained. An analysis of the spatial variations of Turkish fertility behavior is presented, followed
by comments concerning temporal change in this behavior. The
section of this chapter concerned with the spatial analysis of
fertility correlates, identifies the most significantly related
variables and analyzes their explanatory power in relation to
fertility, for each sub-system and for the larger system. The
chapter is concluded by a summary.
The concluding section, Chapter IV, serves to summarize
the pertinent findings of the study through a discussion within
the framework of the questions posed in the opening section of
the first chapter. The final chapter also makes note of some of
the implications of the study, and suggestions for future research
are made. The chapter Is completed with a concluding statement. CHAPTER II
DELINEATION OF A REGIONAL SYSTEM IN TURKEY
The Republic of Turkey represents a complex system of in ternal spatial variation in which, at the same time, a general homogeneity of spatial phenomena can be identified. It is the purpose of this chapter to identify and delineate "regional types" or sub-systems, on the basis of specific features of spatial organ ization and structure within the larger Turkish system. The delinea
tion of this regional system is carried out through a principal axis factor analysis and the utilization of a grouping algorithm.
Data and Variables
The basic data which have been utilized in the various
statistical procedures of this study consist of material extracted
from various census reports, statistical documents, and unpublished materials Issued by various agencies of the Government of the Republic 1 of Turkey. These data are primarily for the year 1960, the time
period of this study, with the exception of several cases where data
from one or two years preceding or following 1960 were used because
of the unavailability of 1960 information.
*A list of the data sources is given in the Appendix.
27 28
Areal units of measurement, which form the basis of the
67 observations, are the Turkish provinces (vllayetler or lller, in Turkish). These provinces are the administrative units of
Turkey and their choice for this study was dictated primarily by the data; these were the collection categories for most of the original statistics used in this study. Map 2 presents the location of the 67 provinces in the Republic of Turkey.
The 69 variables which were selected for use in this study, as raw data, are both absolute numerical quantities and derived numerical quantities, e.g., percentages, ratios. These
69 variables were selected to indicate the internal structure and organization of the Turkish provinces within a framework of several attributes. These attributes are; Demographic - population size, population structure, population change, residence status, ethnic group affiliation; Economic - agricultural land use, labor force characteristics, energy consumption; and, Social, Educational and
General Development - educational levels, literacy rates, indicators of village development, indicators of information flow, medical facilities, road densities and quality.
Although other variables might have been preferable for use
in conjunction with those selected, the unavailability or the sheer
lack of basic raw data prevented the optimal choice of variables to be used. Table 1 lists the variables which were employed in the MARMAM
T 1 MILES 30 100
MEDITERRANEAN SEA REPUBLIC of TURKEY
ro M5 30
(Key to Map 2)
Provinces of Turkey
1 Adana 36 Kars 2 Adiyaman 37 Kastamonu 3 Afyonkarahisar 38 Kayseri Kirklareli 4T Agrl o 39 5 Amasya 40 Kir§ehir
6 Ankara 41 Kocaell 7 Antalya 42 Konya 8 Artvin 43 Kutahya b Aydin 44 Malatya 10 Balikesir 45 Manlsa
11 Blleclk 46 Maraf 12 Bingol 47 Mard in 13 Bltlis 48 Mugla 14 Bolu 49 Mu 5 15 Burdur 50 Nev§ehir
16 Bursa 51 Nigde 17 £anakkale 52 Ordu 18 fankiri 53 Rize 19 ^orum 54 Sakarya 20 Denlzll 55 Samsun
21 Dlyarbaklr 56 Slirt 22 Edlrne 57 Slnop 23 Elazlg 58 Sivaa 24 Erzlncan 59 Teklrdag 25 Erzurum 60 Tokat
26 Eskl^ehlr 61 Trabzon 27 Gazlantep 62 Tuncell 28 Glresun 63 Ur fa 29 Gutnu$hane 64 U^ak 30 Hakkarl 65 Van
31 Hatay 66 Yozgat 32 Isparta 67 Zonguldak 33 I5el 34 Istanbul 35 Izmir 31 principal axis factor analysis, together with their abbreviated code names.
Summary of the Analytic Procedures
The data are subjected to several steps In multivariate analytic procedures. A preliminary step is the preparation of a data matrix, 67 x 69 (67 observations of 69 variables), which con sists of subsets dealing with the various attributes of each place.
The first major step is a principal axis factor analysis of the m x m correlation martrix R, which contains the correlations of each of the m variables with every other variable. This was executed utilizing a computer program PAPA. Output from the factor analysis includes an ra x r matrix of rotated factor loadings.
This to x r matrix is then subjected to computational procedures contained in the ESTFAC computer program, together with the raw data and their means and standard deviations, to produce an n x r matrix of factor scores, F. The matrix P shows the location of the original n observations on each of the new dimensions developed by the factor 2 analysis.
The PAFA and ESTFAC computer programs and their subroutines were written at the University of Kentucky Computing Center.
Principal axis factor analysis is a form of "Factor Analysis" and has been used as a methodological procedure in many of the social and behavioral sciences. Its application to spatial research has been 32
TABLE X
VARIABLES EMPLOYED IN PRINCIPAL AXIS FACTOR ANALYSIS
Variable Coded irober Name Variable
01 TOTPOP Total population 02 P0PDEN Population Density 03 PCURBN Per cent population urban 0A PCVILL Per cent population living In villages 05 SEXRTO Sex ratio 06 PCBSPR Per cent population born In same province 07 PCEURO Per cent population of European origin 08 PCSKUR Per cent population speaking Kurdish 09 PCNTTK Per cent population whose native tongue Is Turkish 10 PCSINW Per cent females 15 years and older who are single 11 NIRATE Rate of natural Increase 12 FERRTO Fertility ratio: entire province 13 FRTOLT Fertility ratio: places with less than 10,000 persons 1A PCO-25 Per cent population age 0 to 25 years 15 PC2565 Per cent population age 25 to 65 years 16 SCHAGE Number of school age children 6 to 16 years per 100 adults 17 PCPLT5 Per cent population less than 5 years old 18 PCPINC Per cent population increase 1955-1960 19 PCCROP Per cent village population living in places with crops as main source of income 20 PCLSTK Per cent village population living In places with livestock as main source of Income 21 DSHEEP Number of sheep per unit area (km.2) 22 DGOATS Number of goats per unit area (km.2) 23 CATTLE Number of cattle per unit area (km.2) 2A CEREAL Per cent area sown in cereals 25 PULSES *Per cent area sown in pulses 26 INDCRO Per cent area sown in Industrial crops 27 FRTNUT Per cent area sown in fruits and nuts 28 FOREST Per cent area in forests 29 MPTRAR Number of males in agricultural employment per tractor 30 WCOOPS Per cent village population living In places with cooperatives
*Pulses are plants which produce edible seeds, as peas, beans, len tils, etc. 33
TABLE 1 - Continued
Coded Name Variable
UWIK.TS Per cent village population living in places with weekly markets MWTCLR Per cent economically active males 15 years and older in white collar employment 33 PPRMRY Per cent economically active population 15 years and older in primary activities 34 MPRMRY Per cent economically active males 15 years and older in primary activities 35 MSCNDY Per cent economically active males 15 years and older in secondary activities 36 MTRTRY Per cent economically active males 15 years and older in tertiary activities 37 PCPENY Per capita energy consumption 33 ENYIND KWH energy consumed for industry in entire province 39 ENYINC KWH energy consumed for industry in places other than provincial center 40 PCSACL Per cent sown area in cereals 41 PCSAPS Per cent sown area in pulses 42 PCSAIC Per cent sown area in industrial crops 43 PCSAFN Per cent sown area in fruits and nuts 44 POPRAD Population per radio 45 POPPTT Population per PTT (postal, telephone, telegraph) establishment 46 ARAPTT Area per PTT (postal, telephone, telegraph) estab lishment 47 PCPIML Per capita ordinary internal mail originating in province 48 PCPFML Per capita ordinary foreign nail originating in province 49 POPHOS Population per hospital bed 50 POPDOC Population per doctor 51 POPCAR Population per automobile 52 PCCARP Per cent automobiles privately owned 53 ASRFWR Ratio: all season roads/fair weather roads 54 RDSPUA Km. roads per unit area (km.^) 55 PCRDSA Per cent roads which are all season 56 ELECTY Per cent villages with electricity 57 SEWRGE Per cent villages with sewerage 34
TABLE 1 - Continued
Coded Name Variable
58 TILERF Per cent village population living In homes having tile roof 59 COFHSE Per cent village population living in places having coffee house 60 GSTHSE Per cent village population living In places having guest house 61 PIPOLY Per cent villages having piped water supply only 62 PIPPWS Per cent villages having piped water supply as part of water source 63 PRGHSE Number of printing houses per 100,000 persons 64 PCMILL Per cent males illiterate: entire province 65 PCFILL Per cent females illiterate: entire province 66 PCMILP Per cent males illiterate: places with less than 1 0 .0 0 0persons 67 PCFILP Per cent females illiterate: places with less than 1 0 .0 0 0persons 68 PCPGPS Per cent population 10 years and older having more than primary schooling 69 PCGPEM Per cent population having more than primary schooling who are male 35
At the next step, the CONGROUP computer program is used and the n observations are arranged as points in the orthogonal
r-space, based upon distances between pairs of points. Computa
tion of pairwise distances changes the n x r matrix of factor
scores, F, into an n x n matrix D, which contains all possible
pairwise distances. The grouping of the observations then
occurs, on the basis of the computed distances. In a stepwise
manner such that at every step of the aggregation process the
vithin-group distance is minimized. This process, through suc
cessive stages, transforms the n x n matrix D into a single row
and column vector containing all the observations. That is, the
n one-member groups are successively reduced to n-1, n-2,...t 1
groups. The resulting groups are approximations of the multi-
factor regional types - sub-systems - which are desired.
exemplified by Berry and others. (See discussion in the previous chapter.)
The primary purpose of the technique is to reduce the original number of explanatory variables into a small number of independent factors in terms of which the whole set of variables may be understood. It thus provides us a simpler, more compact explanation of the regularities apparent in the empirical results. Principal axis factor analysis decomposes the original variance of a variable into variance components associated with the variation of a set of other quantities. The final explanatory variables are not observable magnitudes; they are, rather groupings of the original variables into a number of clusters - known as FACTORS. Each cluster consists of a linear combination of the initial variables included in the analysis. Those variables which are most closely Inter correlated are combined within a single factor.
For further discussion and a more detailed treatment of 36
Interpretation of Principal Axis Factor Analysis
The principal axis factor analysis identifies the basic components that the 69 variables have in common. Each component gathers together statistically Independent clusters of character istics on the basis of their intercorrelations* As illustrated in Table 2, eight basic dimensions or FACTORS account for over
75 per cent, or three-fourths, of the total variance. The first two factors account for almost 50 per cent of the total variance.
It should be noted that more than the eight Indicated factors were identified in the analysis, but the remaining factors offered neither meaningful interpretation, nor accounted for a significant percentage of the total variance.
The interpretation of each of the basic components or factors, is achieved through examination of the correlation between each of the 69 variables and each factor - the factor
"loadings," and by the values scored on the respective factors
by each of the 67 provinces (observations) - the factor "scores."
Factor I (See Table 3)
The first dimension, Factor 1, accounts for 36 per cent
the technique, see: H.H. Harman, Modern Factor Analysis (Chicago: University of Chicago, 1967); D.N. Lawley and A.E. Maxwell, Factor Analysis As A Statistical Method (London: Butterworths, 1963); and, L.J. King, Statistical Analysis in Geography, op. cit.. Chapters 7 and 8. 37
TABLE 2
RESULTS OF THE PRINCIPAL AXIS FACTOR ANALYSIS OF 69 VARIABLES
Per Cent Total Variance Cumulative Proportion Factor Eigenvalue Accounted For of Total Variance
I 24.69 35.79 35.79
II 8.05 1 1 .6 6 47.45
III 5.16 7.47 54.92
IV 3.65 5.28 60.20
V 2.99 4.34 64.54
VI 2.80 4.05 68.59
VII 2.70 3.91 72.50
VIII 2 .1 1 3.06 75.56
* Eigenvalues are the latent roots of the correlation matrix. There are as many eigenvalues as variables in the matrix. The eigen values determine the values of the factors; they may be thought of roughly as the length of the vector which passes through a scatter of points In multidimensional space in such a way as to reduce to a minimum the distance between the points and the vector. 38
TABLE 3
FACTOR I LOADINGS
Factor Loading Variable
.93 Per cent population 10 years and older having more than primary schooling .92 Per cent economically active males 15 years and older In white collar employment .92 Per capita ordinary foreign mail originating in province -.92 Per cent active population 15 years and older in primary activities .91 Per cent economically active males 15 years and older in tertiary activities .91 Number of printing houses per 100,000 persons .8 8 Per cent population urban .87 Per capita ordinary internal mail originating in province -.87 Per cent population living in villages -.85 Per cent economically active males 15 years and older in primary activities .83 Total population .80 Per cent population of European origin -.80 Per cent population born In same province .79 Population density .78 KWH energy consumed for industry in entire province -.65 Per cent population having more than primary schooling who are male .59 Sex ratio .58 Per cent economically active males 15 years and older in secondary activities ,54 Per cent automobiles privately owned -.53 Per cent females illiterate: entire province -.48 Population per doctor -.44 Population per automobile -.42 Per cent males Illiterate: entire province 39 of the total variance and Is Interpreted as a high level of socio economic development vlth an urban emphasis. This Is observed by considering the high positive loadings of such variables as "per cent population 10 years and older having more than primary school ing," "per cent economically active males 15 years and older in white collar and in tertiary activities," "per cent population urban," and the like. This factor actually consists of two interrelated parts: first, a social development element composed of school years completed, number of printing houses, per capita mall originating in the province, per cent automobiles privately owned; and, second, an urban-high economic level element composed of labor force in secondary, tertiary, and white collar activities, kilowatt-hours energy consumed for industry, population density, and per cent urban.
An examination of the high negative loadings supports the interpretation given for Factor I, in that these loadings are for such variables as per cent labor force in primary activities, illit eracy, population per doctor and per automobile. These negative loadings indicate low social, educational, and economic situations with a rural aspect inserted by the presence of the high negatively loaded variable, "per cent population living in villages." These negative loading variables portray the opposite situation' described by the positive loading variables.
The high negative loading for the variable "per cent 40
population born in the same province*' further supports the thesis
that this factor characterizes a situation of economic and social
development or, in terms of migration, variables of "opportunity" 3 or "forces of attraction." These are the very variables which, when aggregated, tend to create a situation which would draw migrants
from less developed, less prosperous areas. It is a known fact that
in Turkey, the greatest out-migration is from economically depressed 4 areas having low level village and urban development. It seems
logical, therefore, that areas of rather high level development and
containing urban centers, would have a high percentage of its pop
ulation who were from other provinces.
A cartographic portrayal of the factor scores (see Map 3)
clearly indicates a distinct spatial pattern for the first factor.
Most of the provinces in the extreme western portion of Turkey
(except for those located in Thrace) are characterized by high-to-
moderate positive scores. The industrialized south-central provinces
are characteristically, highly positive score areas. The adjacent
E.S. Lee, "A Theory of Migration," Demography, Vol. 3, 1966, p. 52.
^See, R.D. Robinson, "Turkey's Agrarian Revolution and the Problem of Urbanization," Public Opinion Quarterly, Vol. 22, 1958, pp. 307-405; and, G.H. Sewell, Squatter Settlements in Turkey: Analysis of a Social, Political and Economic Problem (unpublished Ph.D. disserta tion, Department of Economics and Social Science, M.I.T., 1964), 28 34 40
m co m
~1 MILES 100 36
mediterranean SEA REPUBLIC TURKEY
Negative Score Positive Score (Relatively Low Level Urban Development) (Relatively High Level Urban Development) MAP DISTRIBUTION OF POSITIVE AND NEGATIVE SCORES: FACTOR I 42 provinces portray -moderately positive scores, to the vest, and negative scores, eastward. Obviously, the highest positive scores
are found in the provinces of Istanbul, Ankara, and Izmir.
The eastern and central provinces of Turkey are repre
sented by negative scores on Factor I. The high negative scores
of the southwestern provincial areas and the western Black Sea
coastal areas also stand out clearly. Although some of these
provinces are fairly well developed, their population is not
primarily of an urban type (see Map 4 in the latter part of the
chapter). The appearance of several northeastern Black Sea
provinces - Artvin, Rize, and Gum^hane - as having moderate and
high negative scores on Factor I is rather interesting. Although
this area is among Turkey's most densely populated, most of the
inhabitants are non-urban, living in self-sufficient villages like
their kinsmen In the interior, rather than In cities as on the
western coast of Turkey.
Factor I and the spatial array of Its scores describes a
situation which has been a major problem in Turkey: regional
disparities with regard to social and economic development. This 5 problem has been stated and re-stated by several scholars, and
practical solutions appear to be coming from the Turkish State
^See, for example, Helling and Helling, op. c i t ., pp. 8-11; and Kele^, op. cit. 43
6 Planning Office. The Turkish government has distributed its in vestments In Industrial and service sectors into areas of the east as a partial solution for reducing these disparities.
Turkey has an economic structure in which both public and private enterprises function side by side in many branches of the economy. Private enterprise appears to be most active in such sectors as textiles, food, chemical products, stone and earth enware industries. Iron and steel, printing and rubber industries are of lesser importance to private industrial Income. The public enterprises occupy an important place in the production of alco holic beverages, in transportation, coal, petroleum, iron and steel industries. Except for some very small enterprises, private invest ments are concentrated in Istanbul province, followed by Izmir,
Adana, Bursa, Ankara, Aydin, Eskifehir and I^el - all having rela tively high positive factor scores on the first factor. State enterprises are relatively spread out over the country, but recently, data suggest emphasis in the southeastern provinces, the Mediterranean 7 coastal provinces, and to some degree, in the northwestern provinces.
Factor II (See Table 4)
Accounting for 12 per cent of the total variance of the
^State Planning Organization, First Five Year Development Plan 1963-1967 (Ankara: Central Bank of Turkey, 1964).
^N. Ol^en, op. cit., pp. 274-78. See also, B.W. Beeley, "Spatial Aspects of Development in Turkey," Paper presented to Associa tion of American Geographers Meeting, 1968. 44
TABLE 4
FACTOR II LOADINGS
Factor Loading Varlable
-.87 Fertility ratio: places having less than 10,000 persons -.83 Fertility ratio: entire province -.83 Per cent population speaking Kurdish -.81 Per cent males illiterate: places having less than 10,000 persons .81 Per cent population whose native tongue is Turkish -.76 Per cent population less than 5 years old -.75 Per cent females Illiterate: places having less than 10,000 persons -.75 Per cent males illiterate: entire province -.71 Per cent females illiterate: entire province .69 Per cent village population living in places having guest house -.69 Per cent village population living in places with livestock as main source of Income -.65 Population per radio .64 Per cent village population living in places with coffee house -.63 Number of school age children 6 to 16 years per 100 adults -.61 Rate of natural increase .59 Per cent roads which are all season -.57 Per cent population increase 1955-1960 .56 Per cent village population living in hones having tile roof .54 Per cent village population living in places with cooperatives -.49 Area per PTT establishment .49 Per cent villages with electricity -.47 Per cent population age 0 to 25 years .45 Ratio: all season roads/fair weather roads .44 Per cent population age 25 to 65 years .44 Per cent villages having piped water supply as part of water source .40 Per cent villages with sewerage 45
standardized variables, the second basic dimension - Factor II - reveals a second way in which the variables are interrelated. High
positive factor loadings are registered by several variables which
indicate a rural component with a high level of village development,
as well as some ethnic identification. The highest positive loading
variable - "per cent population whose native tongue is Turkish" - and
one of the highest negative loading variables - "per cent population
who speak Kurdish" - may be interpreted as an ethnic characteristic
of this factor, as well as adding some support to the fact that there
exists a low level of development among the Kurdish speaking minority
in Turkey. High positive loadings characterize villages having
guest houses, coffee houses, cooperatives, homes with tile roofs -
indicative of a high level of village development and economic pros
perity. The appearance of other related variables which load on the
positive side of this factor, further support the interpretation.
The combination of variables having negative factor loadings
further clarifies the interpretation given for Factor II. These var
iables, which indicate high fertility rates, a rather young population
in age, high rates of illiteracy, support the notion of underdevelop
ment. It is rather interesting to note that the high negative loading
which is of an agricultural nature, is that indicating livestock aa
a main source of income. This variable goes well with the Kurdish
ethnic aspect of this factor, since the major economic activity of 8 the Kurdish group is that of grazing and nomadic herding.
Turkey's southeastern territories clearly stand out as being negatively identified with Factor II. The southeastern-most provinces are those containing the largest Kurdish concentrations.
Interesting, are the high negative scores registered by the provinces of southcentral Turkey; although industrialized, and with a moderate level of development in their urban centers, these provinces do not appear to have a similarly high level of development in their village 9 sector. The southeastern and southcentral portions of Turkey have strong traditional ties with their less developed neighbors of Syria and Iran, while western Turkey has become vitally involved in the 10 diffusion process of socio-economic phenomena from Europe. The strong influence of the largest urban centers of western Turkey, the rich agricultural areas of the coastal regions, and the proximity to Europe, each add to the significance of the high level of village development where the factor scores are high and positive.
Factor III (See Table 5)
The third basic component, accounting for almost 8 per cent
®U.B. Fisher, The Middle Fast (London: Methuen, 1963), pp. 180-82.
^This was brought out in discussions with Professor Brian W Beeley, Department of Geography, Kent State University, during the summer, 1963. Professor Eeeley has travelled throughout this area in connection with his own research. 10 N.H. Fi?ek and F.C. Shorter, "Fertility Control in Turkey, 47
TABLE 5
FACTOR III LOADINGS
Factor Loading Variable
.91 Per cent area sown in fruits and nuts -.85 Per cent area sown In cereals .84 Per cent sown area In fruits and nuts -.72 Per cent sown area In cereals .71 Number of males in agricultural employment per tractor -.47 Per cent population living in places with crops as main source of income -.45 Area per PTT establishment -.40 Sex ratio .32 Km. roads per unit area (km.2) ,27 Number of cattle per unit area (lan.^) .26 Per cent sown area in Industrial crops .25 Per cent villages with electricity .25 Population density -.25 Number of sheep per unit area (km.^) -.25 Per cent village population living in places having guest house .23 Per cent villages with sewerage .2 1 Per cent females 15 years and older single 48 of the total variance, appears to bring together several inter related variables which describe an agricultural land use type, supported by a labor characteristic. "Per cent area sown in fruits and nuts" and "per cent sjwn area in fruits and nuts" are, by far, the highest positively loaded of the variables in this component. "Per cent sown area in industrial crops," although not having a significantly high loading, does appear as a positive moderately loaded variable, and probably indicates cotton and tobacco.
Labor intensity, associated with the type of agriculture described by these variables, can be implied by the positive load ings of such variables as "number of males in agricultural employ ment per tractor" and "population density". It is reasonable to assume that areas having a very strong emphasis on fruit and nut production and cotton and tobacco crops, would likely have little need for and use of tractors, since these types of crops are not suited for tractor use. Likewise, area3 of grain production would have a much lower farraer/tractor ratio. This partly explains the negative factor scores in the western Anatolian provinces (Ankara,
Konya, Eski^ehir, Kersehir, Sivas, Qorum, etc.), where cereals are extremely important crops. The high negative loading of the variable
"per cent area sown in cereals," adds to the negative scores gener ated by the central Anatolian provinces.
Demography, Vol. 5, 1968, p. 583. This is also implied by R. Kele$, op. cit. 49
The appearance of such variables as cattle and sheep density tend to support the agricultural structure of this factor.
The commercialized orientation of the agricultural type suggested by this factor is supported by the high positive loading of the
road density variable. Rural areas have a high degree of network
connectivity where this type of agriculture is found; much of the produce involved is exported to foreign markets, as well as to other 11 parts of the Republic. The cattle density variable, while loading
only moderately positive, may suggest dairying activities - another
agricultural specialization closely associated with high road density.
The factor score pattern which emerges, however, does take
on some complexity, in that Factor III contains several variables
which might be considered as irrelevant to the interpretation of
the factor, given. The provinces of the Republic which are most
widely known for their production of fruits and nuts obviously appear
as having moderate to high factor scores. The Black Sea, Aegean,
and Mediterranean coastal regions are promient In this respect.
Mev^ehir, one of the central Anatolian provinces known for its grape
growing, is clearly portrayed by a high positive score. Some of the
eastern and southeastern provinces appear to have low positive scores.
It is possible that these may partly reflect a relationship with cer
tain variables not included in the interpretation of the factor. On
11S. Erin^ and N. Tun^dilek, op. cit., p. 203. so the other hand, It is In some of these provinces that the area sown is relatively small, compared to the total land area; and, of the area sown, fruits and nuts may be significant. Some of these provinces contain isolated oasis type settlements which are 12 dependent on an intensive irrigated agriculture of fruits and nuts. 13 These are also areas where some tobacco is grown.
The provinces which rank high in positive factor scores on Factor III are those provinces which have fairly high population
densities (for the most part), contain some pockets of manufacturing
activity, and are primarily located in coastal areas. Villages
having sewerage and electricity, as suggested by the lower positive
loadings of these variables on this factor, are likely to be found
In most of these provinces, except perhaps in the southcentral coastal
area.
The appearance of a fairly high positive score for Hakkari
province, the southeastern-most province of Turkey, is rather mis
leading. The only interpretation which one might give to this anomoly
Is the extremely high number of males employed in agriculture and the
rather low figure for tractors in this province. This would result
in a positive score because of the influence of the tractor/males
employed in agriculture ratio variable, which has a high positive
12 Discussion with Professor Beeley, op. cit.
Thornburg, Turkey: An Economic Appraisal (New York: Twentieth Century Fund, 1949), p. 70. 51 loading on this factor.
The low, but negative, scores which are registered by some of the provinces along the Marmara coast (Istanbul, £anakkale, and Balikesir) are probably influenced by the negatively loaded variables "area per PTT establishment" and "per cent population living in places with crops as the main source of income". Since these provinces are relatively highly developed, many PTT estab lishments cover small trade areas and much of the income is derived from non-agricultural activities.
Factor IV (See Table 6)
The higher loadings associated with this factor suggest emphasis in cereal crop agriculture and little emphasis on raising industrial crops (such as tobacco, cotton, and sugar-beets). There are also variables which appear in this component which suggest that the level of village life and village development are rather low: emphasis on education higher than the primary level tends to be among males; high number of males in agriculture per tractor; per cent villages with coffee houses and cooperative and those with weekly markets Is low; low sex ratio (indicating perhaps the out migration of males to other areas more prosperous); high population per automobile and per doctor.
Slightly over 6 per cent of the variance is explained by 52
TABLE 6
FACTOR IV LOADINGS
Factor Loading Variable
-.85 Per cent area sown in industrial crops -.84 Per cent sown area in industrial crops .60 Per cent sown area in cereals -.46 Per cent village population living in places having coffee house -.45 Sex ratio .43 Per cent area sown in cereals -.42 Per cent area in forests -.41 Number of goats per unit area (km.2) -.40 Per cent village population living in places with cooperatives ,35 Per cent population having more than primary schooling who are male .32 Number of males in agricultural employment per tractor .30 Population per automobile -.30 Per cent automobiles privately owned .29 Per cent population born in same province -.28 Per cent females 15 years and older single .26 Population per doctor -.26 Per cent village population living in homes having tile roof .26 Per cent population less than 5 years old .22 Per cent females illiterate: entire province - .2 1 Per cent village population living in places with weekly markets .21 Per cent population living in villages .21 Per cent population living in places with crops as main source of income .21 Per cent females Illiterate: places having less than 10,000 persons - .2 0 Per cent population urban 53
Factor IV. The significance of this factor, however, can be readily seen by the fact that, of the accumulated percentage of the total variance accounted for by the first four factors (60 per cent),
Factor IV accounts for approximately 12 per cent).
An examination of the factor scores reveals the expected high positive scores for central Anatolia, known for Its cultivation of hard winter wheat, and moderate positive scores for other wheat producing areas of Anatolia. The moderate-to-high positive scores registered by most of the Black Sea coastal provinces indicate areas where maize production is of considerable importance to local agriculture. Those areas where industrial crops are raised, stand
out as having negative component scores - the highest negative load
ings are for the two variables associated with industrial crop agri
culture.
Remaining Factors: V, VI, VII, VIII
The decision of how many factors should be interpreted is 1A one which has received some comment in recent geographic work. Al
though statisticians have coped with this problem and several have
established criteria for making this decision, the common practice 15 appears to be that of Individual preference and Judgment.
^ L . J . King, op. cit., 1969, p. 17A.
. Horst, Personality: Measurement of Dimensions (San Fran cisco: Jossey-Basa, 1968), p. 1A2. 54
Factors V, VI, VII, and VIII, together account for 15 per cent of the variance. The cumulative total variance which is
accounted for by all eight factors is approximately 76 per cent.
An attempt is made to give some interpretation to the remaining
four factors, in light of the conflicting questions one may en
counter which may result from the presence of "random noise" in
each of these dimensions.
Factor V (see Table 7), accounting for over 4 per cent
of the variance, tends to indicate the absence of pulses as an
agricultural commodity. The factor scores on this dimension do
Indicate high negative allocations to the pulse-growing provinces.
Factor VI (see Table 8) , adding an additional 4 per cent
to the total variance accounted for, appears to bring together vari
ables which indicate a high level of population concentration: pop
ulation per doctor, automobile, hospital bed, radio; population density.
The variables clustered, also tend to give this factor a village
attribute, rather than an urban, and a European ethnic identification.
Factor VII (see Table 9), which also adds an additional 4
per cent of the total variance to the cumulative amount, clearly in
dicates an Industrial component. The prevalence of energy consump
tion variables, males employed in the secondary sector, support this
Interpretation. 55
TABLE 7
FACTOR V LOADINGS
Fac tor LoadIng Variable
-.90 Per cent area sown In pulses - .8 8 Per cent sown area In pulses .36 Per cent females 15 years and older single .34 Per cent villages having piped water supply as part of water source -.29 Fer cent village population living in places with cooperatives .28 Number of males in agricultural employment per tractor -.27 Number of goats per unit area (km.2) -.24 Per cent villages with sewerage .24 Rate of natural increase
TABLE 8
FACTOR VI LOADINGS
Factor Loading Variable
.63 Population per doctor .60 Population per automobile .54 Population per hospital bed .45 Population per radio -.36 Per cent population living in places with crops as main source of Income .33 Per cent population living in villages .32 Population density .32 Per cent population of European origin -.32 Per cent population urban .31 Per cent economically active males 15 years and older in primary activities .30 Per cent males illiterate: entire province -.28 Per cent economically active males 15 years and older in secondary activities 56
TABLE 9
FACTOR VII LOADINGS
Factor Loading Variable
.82 KWH energy consumed for Industry in places other than the provincial center .76 Per capita energy consumption .64 Per cent area in forests .56 Per cent economically active males 15 years and older in secondary activities .54 KWH energy consumed for industry in entire province -.38 Number of sheep per unit area (km.*) .33 Per cent village population living in homes having tile roof .29 Per cent village population living in places with weekly markets -.26 Area per PTT establishment -.25 Population per automobile -.24 Per cent economically active males 15 years and older in primary activities -.24 Per cent village population living in places with livestock as main source of Income 57
TABLE 10
FACTOR VIII LOADINGS
Factor Loading Variable
-.82 Population per PTT establishment .42 Per cent villages with sewerage .42 Per cent villages having piped water supply only .36 Per cent villages with electricity .35 Per cent population speaking Kurdish -.35 Per cent females illiterate: places having less than 10,000 persons .33 Per cent village population living In places with livestock as main source of income -.33 Per cent population whose native tongue is Turkish .32 Per cent village population living in places having coffee house .31 Km. roads per unit area (km. ) .27 Per cent village population living in places having guest house 58
Factor VIII (sae Table 10), accounts for 3 per cent of the total variance. It appears that this factor has two distinct parts: first, a high level of village development (resulting in high positive scores in western Turkey); and, second, a Kurdish element with livestock as the major source of income (resulting in high positive scores in southeastern Turkey).
It is apparent that for factors V, VI, VII, and VIII, no clear-cut Interpretations are easily attained. An attempt has been made, however, to offer some interpretations, bearing In mind that the "other” loadings tend to weaken these.
Factorial Structure of Turkish Provinces
The interpretations given, clearly indicate that the original data matrix, consisting of the 69 variables, can and does have Internal interrelationships. The original 69 variables tend to be interrelated within the factorial dimensions, summarized as follows:
FACTOR I: relatively high level of socio-economic development with an urban emphasis
FACTOR II: relatively high level of village development - Turkish group relatively low level of village development - Kurdish group
FACTOR III: agricultural land use in fruits and nuts with slight emphasis on industrial crops and high population density
FACTOR IV: agricultural land use in cereals with low level village development 59
FACTOR V: absence of agricultural land use in pulses
FACTOR VI: relatively high degree of population concentration (in village setting)
FACTOR VII: industrial activity
FACTOR VIII relatively high level of village development (western Turkey) Kurdish ethnic identification with livestock raising activity (eastern Turkey)
Analysis of Factor Score Plots
A word of caution is appropriate concerning the factor scores, since careful examination of these values might lead to questions regarding the interpretation of the factor. Several variables always appear in the factors as "random noise," and in fluence the values of the factor scores on each observation. There fore, an examination of the original data matrix is often necessary, 16 since it frequently facilitates a clearer interpretation. For
each of the factors discussed, this has been carried out.
The plotting of the factor scores of each province on Factors
"The interpretation of the principal components...is done mainly with reference to the loadings, the philosophy being that vari ables having high correlations or loadings on a component will serve to identify that component.... On any component, some variables will have low loadings and consequently will be ignored in the process of giving an 'interpretation' to the component. On these particular variables, some observations almost certainly will have high values in the original data matrix and their scores on the component will be weighted accordingly by these 'unimportant' variables....the interpre tation of the component scores may have to be qualified by an examin ation of the original data matrix." L.J. King, op. cit., 1969, p. 174. 60
I and II, simultaneously, reveals some rather interesting results for a spatial analysis. Figure 1 illustrates the fact that a province having a relatively high level of socio-economic development in its urban structure (Factor I), does not necessarily have a similar level of development in its rural or village structure (Factor II), and vice versa. Map 4 portrays the relationship of each province with the position of its location on the plot.
The westernmost provinces clearly stand out as being highly developed in both an urban and a rural sense; these provinces plot positive scores on both factors. The south-central provinces and the provinces of Ankara, Elazig, and Diyarbakir, plot positive scores on the first factor, but negative scores on the second. One can justifiably assume, therefore, that these are provinces which have a high level of development within an urban context, but rather
low developmental levels in their village structure.
The southeastern provincial areas stand out clearly as
having low developmental levels in both the village and the urban
sense; they plot negative scores on both Factor I and Factor II.
A high level of village development, but a low level of urban de
velopment appears to be the pattern for most of the non-urbanized
half of western Turkey. These provinces, together with Gumu^hane,
Artvin, and Rize, plot negative scores on the first factor, but
positive scores on the second. There appear to be several provinces TABLE 11
FACTOR SCORES BY PROVINCE
Province Factor
I II III IV V VI VII VIII
Adana .83 - .67 .33 -2,74 1.43 -1.21 .24 -1.93 Adiyaman - .52 - .39 .10 - .52 - .93 2.99 .25 -1.13 Afyonkarahlsar - .42 .73 - .99 .31 .01 - .21 - .87 .03 Agri - .25 -1.58 - .97 .42 1.23 .31 - .60 .53 Ainasya - .30 .44 - .51 - .11 .49 - .42 .51 - .31 Ankara 2.94 - .26 - .59 1.98 .45 -1.96 .63 - .86 Antalya - .36 .05 .04 -1.11 .08 - .56 .64 - .71 Artvin - .67 1.22 2.14 1.68 1.44 - .46 .40 .95 Aydin - .06 .39 1.01 -1.76 .22 .01 .35 1.04 Ballkesir .13 1.14 - .22 - .47 -1.44 .08 - .52 1,00 Bilecik - .81 1.48 - .32 - .07 .01 .22 - .18 1.66 Bingol - .56 -1.76 - .73 .13 .34 2.18 .05 1.48 Bitlis - .18 -2.06 - .83 - .01 .44 - .15 - .01 .88 Bolu - .58 .76 .48 .36 - .27 - .01 .41 .28 Burdur - .57 .52 - .76 .35 .45 -1.24 - .50 .18 Bursa .45 .88 .14 - .86 - .99 - .24 ,16 .69 Qanakkale - .29 1.44 - .11 - .53 -1.20 - .08 - .61 1.73 £ankiri - .29 .87 - .18 1.37 -2.30 .89 - .57 .01 £orura - .55 .40 -1.07 .57 - .06 .83 - .08 -1.44 Denizli - .37 .67 .27 - .24 -1.28 - .34 .07 1.36 Diyarbakir .14 -1.50 - ,15 .34 - .88 -1.30 - .14 .27 Edirne - .11 1.34 - .76 -1.01 .94 - .38 -1.14 .49 Elazig .19 - .40 - .19 .43 -1.36 - .96 .20 - .88 Erzincan - .11 - .28 ,04 1.03 .45 - .39 - .63 .44 Erzurum - .15 - .92 -1.02 .17 - .24 - .55 -1.22 - .39 TABLE 11 - Continued
Province Factor
I II III IV V VI VII VIII
Eski^ehir .77 ,99 - .93 .57 1.21 -1.95 .04 .31 Gaziantep .74 - .76 1.61 - .16 -3.19 -1.05 - .29 -1.80 Giresun - .48 - .07 3.26 .97 .47 .70 - .37 - .63 Gumu^hane - .70 .25 - .37 .77 1.05 1.29 - .23 - .83 Ilakkari - .32 -3.12 .68 - ,63 .61 .39 - .14 2.49 Hatay .50 -1.12 .67 -1.56 .17 - .84 - .10 - .69 Xsparta .27 .83 .54 .92 -1.74 - .87 - .32 1.79 I^el .34 - .24 .03 -1.73 .84 -1.07 .18 -1.79 Istanbul 6.47 .54 - .12 .97 .39 2.83 - .44 .65 Izmir 2.00 .45 .97 -2.11 - .66 .09 - .12 .90 Kars - .21 - .55 - .36 .16 ,79 .97 -1.31 .15 Kastamonu - .89 .54 - .34 .83 .31 .20 .50 - .30 Kayseri .28 .04 - .11 1.03 .25 -1.42 - .40 - .42 Klrklarell - .30 1.79 -1.08 -1.36 .86 - .04 - .13 .63 Kir$ehir - .41 .46 - .53 .82 .01 - .53 - ,66 -1.32 Kocaeli .58 .62 - .25 -1.06 .91 .02 2.86 .80 Konya .11 .29 - .87 .56 .47 - .91 - .26 - .98 Kutahya - ,32 ,37 - .83 .14 -1.08 1.41 2.22 .37 Malatya - .05 - .26 - .05 .74 .22 - .74 - .04 - .77 Manisa .04 .26 .20 -2.13 - .68 - .30 - .02 .15 Mara§ - .24 - .62 - .34 - .25 - .93 .42 - .04 -1.76 Mardin - .32 -1.80 .47 - .10 -1.73 - .36 .26 .21 Mugla - .61 .59 .88 -1.44 .25 - .07 .06 .71 Mu? - .32 -1.69 - .91 .30 .78 .04 .02 .86 Nev?ehir .27 .62 .79 .91 .41 - .32 -1.15 .47 TABLE 11 - Continued
Province Factor
I II III IV V VI VII VIII
Nigde - .13 .67 - .40 .59 .62 .79 -1.12 - .76 Ordu - .59 .02 1.79 -1.07 .66 2.75 - .15 -1.40 Rize - .28 .34 3.39 1.95 1.64 - .86 - .19 .33 Sakarya .16 .54 .34 -1.17 .83 - .38 .33 - .10 Samsun .15 - .11 - .26 - .76 .33 .31 .29 -1.94 Siirt - .06 -2.07 .01 .20 - .61 - .53 .41 1.19 Sinop - .87 .63 - .55 .44 .59 1.35 .42 - .50 Sivas - .24 .02 - .87 1.05 .33 .02 - ,19 -1.21 Tekirdag - .17 1.35 - .91 -1.29 1.23 - .40 -1.04 .54 Tokat - .32 .11 - .26 - ,15 -1.22 .76 .02 - .78 Trab zon - .08 - .47 3.20 .27 .24 .24 - .27 - .43 Tuncell - .54 - .44 .01 .78 .76 .27 .05 .24 Urfa - .06 - .92 - .56 .11 -1.63 - .71 - .45 - .47 U§ak - .36 .77 - .53 .30 -1.99 - .12 .11 .62 Van - .02 -2.06 -1.22 .04 1.02 .26 -1.00 1.06 Yozgat - .63 .77 - .95 .76 - .13 1.44 - .23 -1.07 Zonguldak - .16 - .07 - .38 1.11 .29 - .20 6.05 .10
O' u> • |J put’ I *111] II'J J*‘ I'Mtl 1
--O'z-
O ’l
o - S-
oo
O'Z o g -
01
* r 9 REPUBLIC of TURKEY
MAP 4: LOCATION OF FACTORS 1 AND II PLOTS W77/// High Level Urban Development/ Low Level Urban Development/ High Level Village Development High Level Village Development
High Level Urban Development/ Low Level Urban Development/ Low Level Village Development Low Level Village Development i 66 which might be characterized as having low level urban development with perhaps a moderate level of development in the village sector.
These provinces tend to be those which are located on the periphery between the less developed east and the more developed central and western parts of the country.
A plot of Factors II and III scores indicate, to some extent, the relationship between level of village development and agricultural land use. (See Figure 2.) Four relationships emerge:
(1) relatively high level of village development in areas of fruits and nuts are important; (2) relatively high level of village develop ment where fruit and nut cultivation is of little importance; (3) re latively low level of village development in areas of fruit and nut cultivation; and, (4) relatively low level of village development where agriculture does not stress fruit and nut cultivation.
Mapping the location of the plots (see Map 5) reveals a striking contrast between the eastern and western halves of Turkey.
The western half appears to have the higher level of village develop ment, with the Mediterranean coast being especially prominent in fruits, nuts, and some industrial crops (especially tobacco and cotton).
Several of the Black Sea provinces are similarly portrayed. The level of village development, in the western half of Turkey, also appears to be high in areas where Factor III type agriculture is not prevalent. 67
II
- - 2.0
1.0
-L0 o o
-5
-1.0
-20
tf Figure 2: Plot of Factors It and III Scores r
• * * * * • A' / ^ W T i r ^ V r « » i *1 p ^ l'ji |i^i i'I'TX'- *% * C ^ R b */■/,'»
* :*:i: v> : * r i L * : j
I MILES _ _ , _. * 47 * * « • A. . _ 'T* t*jr• uri 1 • ■ • *T *t*,1 100 _•'_•*_• - • ■_V • /iM m «• «» * «>t t f iT ~------^C* *
MEDITERRANEAN REPUBLIC of TURKEY MAP 5: LOCATION OF FACTORS II AND III PLOTS High Level Village Development Low Level Village Development With Fruit & Nut Crops With Fruit & Nut Crops
High Level Village Development Low Level Village Development With Absence of Fruit & Nut Crops With Absence of Fruit & Nut Crops
O' co 69
The eastern half of the country indicates a relationship between low level village development and the lack of fruits and nuts (and even Industrial crops). This Is true especially for the non-coastal provinces of the northeast, although the southeastern provinces are plotted in such a marginal position that they should be grouped together with those of the northeast. The south-central provinces (especially Hatay and Gaziantep), on the other hand, plot especially strong in the agricultural component, but weak in their level of village development. It is in this area that development has been uneven; the production of cash crops and the growth of industries has brought in poor seasonal laborers and other laborers from the barren mountain regions to the north. Many of these new comers have joined the local agricultural peasantry in forming a depressed proletariat. In 1957, for example, over AO per cent of the population of Adana province lived in what might be termed 17 "shanties
In plotting the scores on Factors II and IV, again one Is able to approach the interrelationship between level of village development and an agricultural land-use type: cereals. (See Figure
3.) As in the previous discussion, four interrelationships emerge:
(1) relatively high level of village development with cereals a pre dominant crop; (2) relatively low level of village development in
Mango, Turkey (New York: Walker, 1968), p. 143. 70
rr -2.5 o o ° * o o 5* o o
-1.0 o o O o o o O o o o o o - .5 ° °
o o o ° o O o o o o
o o 1 < o ° © © o o o o o o °o --to o r>0 <"0 o o o ° o o ° o -----2A o Figure 3: Plot of Factors II and IV Scores 71 areas where cereals are important; (3) relatively high level of village development where cereals are not significant in land use; and, (4) a relatively low level of village development where cereals are insignificant crops. In examining Map 6, which cartographically displays the location of each province on Lhe plotted axes, the emerging spatial distribution of the above four categories is quite similar to that of Map 5 (showing level of village development and fruit and nut agriculture), except that agricultural land-use emphasis is just the opposite. The levels of village development, obviously remain the same on both maps, but on Map 6, those provinces ‘known for their cereals production clearly reveal themselves. Except for Ankara province, western and central Anatolia is characterized as having a high level of village development with empahsis on cereals. Ankara province, which is characterized as having a low level of village development (its factor score on Factor II is fairly low: -.26) but agricultural emphasis in cereals, may re quire further analysis. In a re-examination of the original data matrix, one finds that only A3 per cent of the provincial population resides in villages. It should be realized, therefore, that in a discussion of the level of village development, in reality, reference is being made to only two-fifth's of the provincial population. According to the original data matrix, Ankara province ranks rather - s1*1 1 MILES MEDITERRANEAN REPUBLIC of TURKEY MAP 6: LOCATION OF FACTORS II AND IV PLOTS High Level Village Development High Level Village Development With Cereals Dominant Crop With Cereals Not Dominant Crop Low Level Village Development Low Level Village Development m . With Cereals Dominant Crop With Cereals Not Dominant Crop I ______'-i to 73 low on certain level of village development Indicators: per cent villages having coffee house - 15 per cent; per cent village pop ulation living in homes having tile roof - 5.3 per cent. It is also possible that the original data include the areas immediately sur rounding the city of Ankara, the gecekondular (squatter settlements), 18 inhabited by newly arrived villagers and small town Immigrants. It appears, thus, that there are several striking differences in the level of development between Ankara province and Ankara city. The eastern third of the country appears to be an area of cereals, predominantly, but with a low level of village development, except for the provinces of Bitlis, Mardin, and Hakkari, where cereals do not appear as important crops. A two-dimensional axes plot of the factor scores of Factors II and VIII reveals distinct locational patterns. The western provinces, having positive scores on both factors, appear in the upper-right quad rant of the plot. In this case, both factors emphasize high level village development and reinforce each other. The southeastern pro vinces, which score high negative on Factor II, score moderate-to- high positive on Factor VIII, which also consisted of a Kurdish ethnic group with livestock, element. Figure A and Map 7 clearly display distinct locational patterns of the provincial points on the axes. 1 A An excellent study and account of these settlements, and an analysis of the problems related to then, is given in Sewell, op. clt. 74 W«*t«rn Province* 2.0 1.0 - 1.0 -5 liO VIII -.5 - 1.0 S.E. ProvincM o Western Provinces x tastc-rn Provinces • Other Provinces Flfture 4: Plot of Fsctors II and VIII Scores r 28 34 40 I M11. E S mediterranean REPUBLIC of TURKEY MAP 7 : LOCATION OF FACTORS II AND VIII PLOTS High Level Village Development Low Level Village Development 4 Strong Kurdish Ethnic Group vt 76 Grouping Analysis of Provincial Factor Scores If one conceptualizes the Republic of Turkey as being a larger system composed of smaller sub-systems, the provinces of the Republic may be differentiated into groups, each group being a sub-system. These provinces, when grouped together into their re spective sub-system clusters, do not necessarily form contiguous regions. Rather, they form "regional types," with contiguity being a constraint of secondary importance. As would be expected, there are cases where contiguous provinces are members of the same group (sub-system or regional type); but, this is not a necessary attribute for membership in any sub-system. In the preceding analysis of the factor score plots, it became apparent that distinct groupings of provinces emerged as a result of plotting the factor scores on Factors I and II, II and III, II and IV, and II and VIII. However, there is still need for greater precision in the regionalization process delineating regional types, since all of the attributes of the provinces should be considered simultaneously. There attributes are, on the basis of their sig nificant interrelationships, represented by the eight identified factors, thus giving eight orthogonal dimensions. In order to locate the groupings of provinces in the 19 orthogonal multi-dimenslonal space, the CONGROUP grouping algorithm 20 was utilized. The program begins with 67 individual groups, each province being a group unto itself, since each province does display some degree of uniqueness in its attributes. The first step in the group ing selects the two provinces which are most alike in their internal organization and spatial structure, and hence, creates a single group of two members. This group of two, together with the remaining 65 provinces result in 66 separate groups. This step-like procedure continues, with individual provinces or existing groups linked on the basis of similarities or, in other words, or the basis of mini mizing the increment of the within group distance. The final step consists of one group of 67 provincial members, with total generaliza tion. Although there have been several criteria used in selecting 19 Programmed by Peter M. Neely, University of Chicago. See, D.F. Marble, Some Computer Programs for Geographic Research, Department of Geography, Northwestern University, Special Publication No. 1, 1967. 20 The algorithm analyzes the factor scores of each province on each of the eight factors (thus, on the basis of the original 69 variables), applying the principle of the discriminant function. Within an eight-dimensional space, the algorithm proceeds to mathematica iiy. maximize the ratio of the between groups to the within groups variance. In this case, tha ratio concerns distances, computed as Mahalanobia* statistics. For further discussion on the statistical aspects, see, J.H. Ward, "Hierarchical Grouping to Optimize an Objective Function," Journal of the American Statistical Association, Vol. 58, 1963, pp. 236- 44. For further discussion of this methodological procedure in geo graphic application, see, Ahmad, op. c i t ., Chapter III. 78 the optimal number of groups once grouping has been achieved, this grouping procedure has no single analytic solution. In this study, the number of groups was selected at that step In which a single 21 member no longer existed. Resulting Regional Sub-Systems The grouping of the 67 Turkish provinces resulted in essentially eight regional type sub-systems, presented in Table 12. As was stated previously, although contiguity Is not a requisite for group membership, the resultant grouping displays, for the most part, several sub-systems composed of contiguous member provinces. The sub-systems do take on distinct locational patterns, with member provinces tending to be clustered in distinct spatial locations within the overall larger system (see Map 8). The first group Includes the Aegean coastal provinces and the provinces in Thrace, In addition to Istanbul and the two provinces immediately east of Istanbul province. Its membership is made up of ten provinces, which are characterized by extremely high to moderate positive scores on Factor II, indicating a sub system of relatively high level of village development. This is For other studies in which decisions of a similar nature were made, see, Ahmad, op. cit.; and, L..T. King, "A Cross Sectional Analysis of Canadian Urban Dimensions,*' op. cit. 79 TABLE 12 REGIONAL TYPE SUB-SYSTEMS IN TURKEY: PROVINCIAL MEMBERS Region 1 (10) Region A (18) Region 6 (A) Edirne Burdur Glresun Kirklareli Afyonkarahisar Trabzon Tekirdag Eski?ehlr Rize Izmir Bolu Artvin Manisa Zonguldak Ayd in Kastamonu Mugla Ankara Region 7 (6) Istanbul Konya Kocaell Kir§ehir Agri Sakarya Nev?ehir Van Amasya Hakkarl Kayseri Bitlis Region 2 (9) Sivas Mu? Malatya Bingol fanakkale Erzincan Balikesir Tunceli Bursa Erzurum Region 8 (5) Bileeik Kars £ankiri Elazig Kutabya Diyarbakir U?ak Region 5 (10) Siirt Denizll Mardin Isparta Sinop Ur fa Samsun Ordu Region 3 (5) Tokat Yozgat Antalya Nigde l9el Mara? Adana Ad iyaman Natay Gumu?hane Gaziantep £orum St* MARMARA 1 ' 1!1;; 1 w : 111! i!! i; I!!1'1'1'1 1 MILES 0 MEDITERRANEAN REPUBLIC of TURKEY MAP 8: DELINEATED REGIONAL TYPE SUB-SYSTEMS I* * * M« • 4 < * • * « Sub-System U Sub-System 1 left* Sub-System 2 Sub-System 3 i • 1 • 1 'I't'i Sub-System 7 Sub-System 8 Sub-System 5 Sub-System 6 1III 1 1 .LIIIlLuL l 03 O 81 further supported by the generally high positive scores these provinces rank on Factor VIII. High negative scores on Factor IV, indicate the importance of industrial crops (which has a high negative loading on this factor); vineyard type fruits are also an important aspect of the agricultural production in this sub-system. Group two, is composed of nine provincial members: the three provinces on the Asiatic shore of the Sea of Marmara, with the re maining provinces concentrated in western Turkey. These provinces share high positive scores on the level of village development factor, low scores on the industrial factor, high positive scores on Factor VIII (supporting the relatively high level of village development characteristic) and high negative scores on Factor V, indicating the importance of pulses as agricultural crop commodities. The third sub-system group is made up of the five southern most provinces, four of which are located on the coast of the Mediter ranean Sea. These provinces rank moderately high on the level of urban development and quite low on the level of village development. These provinces are, agriculturally, important for fruits and nuts, industrial crops, and are of little importance in pulses. These are provinces in which industrialization has taken place and urban centers have grown in importance, but, where little improvement has been made in the agrarian sector of the region. 82 The largest regional type group is made up of the Ana tolian provinces with the additional membership of one or two peripherally located provinces, resulting in 18 members. In this fourth sub-system, cereals dominate the agrarian economy; fruits, nuts, and pulses appear to have little importance. Concentrations of population are low, characteristically, and the level of develop ment with an urban emphasis and industrial activities appear to be low (except in Ankara and Eskl^ehir provinces which are somewhat unique in this respect). In addition to three Black Sea coastal provinces, the fifth group is made up of provinces mainly located in the central- eastern portion of the country. The sub-system's ten member pro vinces appear to be located on the northern and southern edges of the Anatolian group (Region 4). This sub-system is characterized by a lack of urban type development but, low to moderate level of village development. The agrarian economy lacks fruits, nuts, and pulses, but has some industrial crops. It is further characterized by high concentrations of population In the village sector, resulting frequently in high local population densities. The four provinces in the northeastern Black Sea coastal area, clearly make up the membership of the sixth group. Low level urban development and an overwhelming concentration of population in 83 villages where fruits, nuts, and cereals are Important crops, distinguish this sub-system from the others. It represents an area of mixed farming and one of the densest regions of population in the Republic. The far southeastern provinces, which make up the six member seventh group, are characterized by their extremely low level of development in both a village and urban sense. The most common attribute of this regional type is its Kurdish population, engaged in livestock herding, primarily. The absence of pulses, fruits and nuts, industrial crops, and only some marginal production of wheat, are other common features of the member provinces. There also appears to be some degree of high population concentrations in villages, where they exist. The eighth regional type, which is made up of five near southeastern provinces, also has a low level of village develop ment and a strong Kurdish minority group. This is a marginal area for cereal crops, but ranks high negative scores on the absence-of- pulses dimension, indicating agricultural orientation may be in pulses. The high negative scores on the population concentration factor is another common attribute of this regional type. What has been accomplished here, in essence, is the de lineation of eight regional type sub-systems which together form the 84 complex larger system of the Turkish Republic. As would be expected in a country such as Turkey, which is primarily agricultural and rural, level of village development and agrarian economic structure seem to be delimiting criteria for regional differentiation. Each of the eight sub-systems contains a high degree of internal homo geneity with regard to the factors and thus, the original data. These regional types, according to the set purposes of this study, now form the basis of further analytic inquiry, as they relate to human fertility and in the context of the previously stated questions and hypotheses. In this chapter, an explanation was given regarding the original data, the variables which were selected, and the choice of areal units used. The purpose here was to utilize, via a multi variate approach, the original data in order to delineate regional type sub-systems within the Turkish Republic. The original data were reduced from 69 variables, to eight factors, each consisting of a number of interrelated variables. The resultant eight factors were used as the basis for grouping provinces Into regional type sub-systens, utilizing factor score rankings of each province on each factor. This procedure resulted In eight regional type sub-systems which are to be utilized for further analysis dealing with human fertility behavior in Turkey. CHAPTER til HUMAN FERTILITY AND ITS CORRELATES IN TURKISH SUB-SYSTEMS Introductory Statement The purpose of this chapter is to study variations of human fertility behavior and the correlates of this behavior, within the sub-systems, or regional types, which have been identified and discussed in the previous chapter. This type of approach is not only important for the test ing of theory, but also because it has significant practical application. A major undertaking in Turkey, at present, is the Turkish Demographic Survey (TDS) , which was started by the Ministry of Health in 1965. This monthly survey of vital events has a national sample of 235,000 persons, and is used to make basic demo graphic estimates for several categories of the Turkish population.^" Unfortunately, much of what is being analyzed from the survey, In the form of "regional" data, may be open to some degree of criticism. The five main regions used by the TDS were created by assembling the 16 regions of the Ministry of Health and arbitrarily delineating these into five. These regions are not well designed to maximize *N.H. Fi^ek, Y. Ucpcrkan, and J.C. Mumford, op. cit. 85 86 inter-regional variation in such variables as fertility, mortality, socio-economic measurements, and developmental levels, etc. This creates some difficulty when one desires to study a-d analyze the factors which affect demographic events, such as fertility corre- 2 lates. The approach which is taken in this study then, may con tribute in the long run, toward a more effective analysis of fertility behavior because of the utilization of more meaningful and rigorously delineated regional type sub-systems, which in effect, have minimized within group variances and maximized between group variances among Turkish provinces. The regional type sub-systems which have been delineated in the previous section, indicate a strong emphasis on develop mental levels and agrarian structure. This may be highly relevant to fertility behavior, both directly and/or indirectly. It has been noted that the motivation to limit family size is probably connected, to a great extent, with the trend of early childhood 3 mortality declines. Environmental hazards, protein deficiencies. ^This criticism of the Turkish Demographic Survey's five regions was also brought out In, N. Fi§ek and F.C, Shorter, op. cit., p. 578. See, D.M. Heer, "Economic Development and Fertility," Demography, Vol. 3, 1966, pp. 423-44; A.J. Coale, "Factors Associ ated With the Development of how Fertility: An Historic Summary," Paper presented to United Nations World Population Conference, 1965; N. B. Ryder, "The Influence of Declining Mortality on Swedish Reproductivity," Current Research in Human Fertility (New York: Mil- bank Memorial Fund, 1955), pp. 65-81; K.G. Basavarajappa, "Effects 87 and Inadequate health of children in turn, have a direct bearing on mortality rates among the very young. As the proportion sur viving beyond early childhood grows, increased demographic pres sure is often felt by families, and the motivation for family planning is strengthened. Therefore, the reproductive behavior of the Turkish population, assuming their response to be similar to that of other cultural groups, may very well be a factor highly related to levels of development and agrarian economic structure. A little over a decade ago, Taeuber’s study of fertility 4 in Turkey made note of several correlations between fertility and agrarian structure. Her findings indicate that there was a significant correlation between fertility ratios and the per cent males in agriculture (r ■ +.55), and between fertility ratios and the per cent population living in villages (r « +.64). Her find ings also Included a "developmental variable" - per cent males age seven and older who are literate - which had a significantly high negative correlation with fertility ratios (r a -.84). One of Declines in Mortality on the Birth Rate and Related Measures," Population Studies, Vol. 16, 1963, pp. 237-56; T.P. Schultz, "An Economic Model of Family Planning and Some Empirical Evidence From Puerto Rico,” Memorandum, RM-5405-RC/AID, The Rand Corp., 1967. For an interesting approach in testing this relationship, using a Monte Carlo simulation model, see J.C. Ridley, M.C. Sheps, J.W. Lingner, and J.A. Menken, "The Effects of Changing Mortality on Natality: Some Estimates From A Simulation Model," Milbank Mem orial Fund Quarterly, Vol. 55, 1967, pp. 77-97. ^I.B. Taeuber, "Population and Modernization in Turkey," Population Index, Vol. 24, 1958, pp. 101-22, 88 of her major conclusions was that variations In the fertility ratios among the Turkish provinces were related to the predomlance of the agricultural occupations and agrarian structure.^ More recently, Fi§ek and Shorter analyzed fertility rates in Turkey and noted that fertility differences between regions (using the regional system of the TDS) correlated well with liter acy indices.** In their analysis, they found that the correlation between birth rates and literacy rates were almost the same for both sexes (males: r « -.87; females: r - -.90). They also cor related fertility rates with an index of socio-economic development and with the per cent population which is urban. The calculated correlation coefficients obtained were -.87 for the former, and -.46 for the latter. They find that the relationship between birth rates and literacy rates is a particularly reliable association - this was confirmed by their use of the 1960 census data and their use of the Turkish Demographic Survey data. Although they conclude that fertility differences correlate well with literacy indices, they further conclude that in rural areas, factors other than those indexed by literacy may be more important influences on fertility behavior. 7 3Ibld., p. 117. ^Fi^ek and Shorter, op. cit., pp. 578-88. 7Ibld. , p . 585. 89 It is apparent that attempts have been made by several investigators to analyze the most meaningful and significant cor relates of human fertility in the Turkish Republic. With the trend having been set, through the use of recent data and a system atically delineated regional scheme, this study should add some additional insight into the relationships between fertility behavior and its most significant correlates. 8 Fertility Ratios The measurement of precise fertility variations in the Republic of Turkey is extremely difficult. As previously stated, it has only been in the last four years or so, that the Turkish government has embarked upon a major effort to collect adequate data concerning births, deaths, and related information. In the absence of accurate fertility measures, the data which were avail able in census publications were analyzed and adjusted, to give fertility indicators through the use of the fertility ratio. This ratio is a device which indicates the ratio of child ren In the age group, usually 0 to 5 years, to the number of women (often only married women are used in the calculation) in the child-bearing ages, usually 14 to 44 years old, although several investigators prefer the use of the 15 to 49 years category. A This is sometimes referred to as the "child-woman ratio." 9 0 Notwithstanding the fact that there are several shortcomings which this ratio has - for example, it assumes all women included in the calculation are fecund and it ignores child mortality between birth and the age of 5 years - where precise data were lacking, it has 9 been used as an analytic technique with some degree of success. The fertility ratio is computed as follows: - °~* . k 14-44 where: ^Q- 4 number of children of both sexes under 5 years of age, 14-44 is the number of married females between the ages of 14 and 44 years, k is a constant of 1,0 0 0. In the analysis and discussion of fertility, the fertility ratio measurement has been used as the dependent variable and as q For a discussion of this technique, see, G.W. Barclay, Techniques of Population Analysis (New York: John Wiley, 1958), pp. 24-25; and, W.S. Thompson and D,T. Lewis, Population Problems (New York:McGraw-Hill, 1965), pp. 241-42. For the use of this measurement with successful applications, see, I.B. Taeuber, o p . cit.; D.M. Keer, op. clt; and, E. Vlelrose, Elements of the Natural Movement of Population (New York: Pergamon, 1965), Chapter 5. This technique was also applied with successful results In the now classic study of W.H. Grabill, C.V. Kiser, and P.K. Whelpton, The Fertility of American Women (New York: John Wiley, 1958). 91 an indicator of fertility behavior in Turkey. Spatial Variations of Turkish Fertility Behavior The provincial fertility ratios of the Turkish Republic have a somewhat distinct pattern in their spatial distribution. It appears that fertility ratios tend to increase steadily, for the most part, in an eastward-southeastward direction. This 10 spatial distribution was subjected to a Trend Surface Analysis and the resultant map (see Map 9) of the best fit cubic polynomial function surface, supports this statement. It seems, from the TSA map, that there are "S" shaped isolines, distinguishing fertility behavior differences. The lowest ratios are in the western part of the country, moderate rates in the west-central and northeast Black Sea coastal areas, and high rates In the eastern portion of the Republic. It is quite feasible that this pattern would be closely related to developmental differences and very likely that 10 The computer program used was SUTRAN, originally written at the University of Kansas by M. O'Leary, R.H. Lippert, and O.T. Spitz. The original version was slightly modified by M. Albaum and R. Jang, at The Ohio State University. For a discussion of this technique in a geographic context, see R.J. Chorley and P.M. Haggett, "Trend Surface Mapping in Geo graphical Research," Transactions and Papers, Institute of British Geographers, Publication No. 37, 1965, pp. 47-67. T - 1 6 5 TO - 1 3 9 J 3 5 5 TO 3 8 1 I 8 7 5 TO 9 0 1 0 1 3 9 5 TO 1 4 2 1 * S - 1 1 3 TO - 8 7 I 4 0 7 TO 4 3 3 1 5 2 7 TO 9 5 3 1 4 4 7 TO 1 4 7 3 ft - 6 1 TO - 3 5 H 4 5 9 TO 4 8 5 2 5 7 9 TO 1 0 0 5 * 1 4 9 9 TO 1 5 2 5 Q - 9 TO 1 7 G 5 1 1 TO 5 3 7 3 1 C 3 1 TO 1 C 5 7 - 1 5 5 1 TO 1 5 7 7 P 4 3 TO 6 9 F ^ 6 3 TO 5 8 9 4 1 C 8 3 TO 1 1 0 9 1 6 0 3 TO 1 6 2 9 0 9 5 TO 1 2 1 E 6 1 5 TC 6 4 1 5 1 1 3 5 TO 1 1 6 1 + 1 6 5 5 TO 1 6 e i 6 1 4 7 TO 1 7 3 0 6 6 7 TO 693 6 1187 TO 1213 S 1 7 0 7 TO 1 7 3 3 « 1 9 9 t o 2 2 5 C 7 1 9 TC 7 4 5 7 1 2 3 9 TO 1 2 6 5 T 1 7 5 9 t o 1 7 8 5 L 2 5 1 TO 2 7 7 6 7 7 1 TC 7 9 7 8 1 2 9 1 TO 1 3 1 7 X 1 8 1 1 TO l e 3 7 K 3 0 3 TO 3 2 9 A 8 2 3 TO 8 4 9 9 1 3 4 3 TO 1 3 6 5 Y 1 8 6 3 TO 1 8 8 9 01234567890123456789012 34567890123456789012345678901234567890123456789012 3456789012345678901234 56 78900 1 C C C C C C C C BeBBB88BB8B&8 AAAAA I** 1111 2 CCCCCCCCC BeeeEEeeeaaeBBBeeeseeeBeBe a a a a a a III## 1 1 1 2 2 2 30DD CCCCCCCCC seaBBeeEeeeBBeeeaee^ a a a a a a a a ##«# 1111 222 3 4 CCD00 CCCCCCCC BSBBdeeeeefieee a a a a a a a a «*#*« UU 222 333 4 5E 00000 CCCCCCCC eeeBseeeeeB AAAAAAAA #«##*# 1111 222 333 *45 6EEEE ODDDD CCCCCCC 6 8 B B 0 0 6 6 0 AAAAAAAA # # « l l # l l l l l 2222 33 444 6 7 EEEE DDODO CCCCCC BBBBBBBB AAAAAAAA IIIIII 1 1 1 1 222 33 444 57 8 EEE CDDDC c c c c c c BB E B B B B B AAAAAAA III### 1111 2222 333 444 5558 9 F F E E E E DODO CCCCC BBBBBBB AAAAAAA III## l l l l l 2222 333 444 555 9 O F F F E E E E CCCCD c c c c c c BBBBBBB l l l l l # 1 1 1 1 2 2 2 2 333 444 555 0 1 F F E E E 0 0 0 0 c c c c c c BBtiBBB AAAAAAA # # < # # 1 1 1 1 1 2 2 2 2 333 44 55 1 2 F F F E E E QUOD c c c c c 6 B B B 8 AAAAAA # 1 1 1 # 1 1 1 1 2 2 2 2 333 444 55 62 3 F F F E E E o c c o CCCCCBBBBBB AAAAAAIII### 1 1 1 2 2 2 333 444 55 63 4 F F E E E E ODOO ccccc BBBBBB AAAAAA i i i i i i l 1 1 1 2 2 2 2 333 444 55 4 5 F F F E E E QCDC ccccc BBBBBB A I##### l 111 2 2 2 2 3333 444 555 5 6 F F E E E E 0 0 0 0 CCCC 8EBBBB AAAAAAA i i i i i i l 1 1 1 2222 333 44 555 6 7 EEE DODO CCCC BBBBBB AAAAAAA I 111 2 2 2 2 2 333 444 5557 8 EEE ODOD CCCCC BBBBB AAAAAAA ####11# 11 1 1 1 1 2 2 2 2 2 3 3 3 4 4 4 5 8 9 E DODO CCCCC BBBBBB a a a a a a a a 1 1 1 1 22222 3333 444 5 0 O D D C C C C B B 8 6 & AA 1111 22222 3333 444 0 1 C c c c BGBB AA AAAAA tiltiiilllll i l l l l l l l 222222 3333 441 2 C C C B B B B B AAAAAA m i l l 111111 222222 3333 2 3 BBB AAAAA lium illliil 1 1 1 1 1 1 1 222222 33333 4 AAAAA 141111 1111U 111111111111111111111111111111111 111111111 2 2 2 2 2 2 2 4 5 I I I # 1 1 1 1 1 1 1 1 1 1 n u i i i i 111111111111 2 2 2 2 2 2 5 01234567890123456 789C123456789C12345678901234567890123456789CI234567890123456785012 3456789012 3456 78900to M MAP 9: TURKISH FERTILITY RATIOS BY PROVINCE - CONTOURS OF LUBAR+QUADRATIC+CUBIC TREND SURFACES (1960) 93 distance from the country's major metropolitan area, Istanbul, 11 has some bearing on this matter. It also might be speculated that the spread of new Ideas and innovations which would influence declining fertility or patterns of life which would dictate a small size family, may be highly related to the distance from Istanbul. This will be examined elsewhere in this chapter. Of particular interest is the lower fertility ratios found in the provinces of the northeastern part of the Republic, along the Black Sea coast. The fertility ratios of Artvin and Rize provinces are significantly lower than one would expect. The possible anomoly here, and one assumes that the basic data are not 12 erroneous - other investigators have detected this - may be due to patterns of seasonal migration. Large numbers of Black Sea males migrate to Istanbul, Ankara, and elsewhere for employment, for about one-half of each year. Some remain in these destinations 13 for longer periods of each year. It is highly possible that this migrational pattern may contribute, to some extent, to the lower fertility ratios. It must be acknowledged that this is certainly an effective practice of birth-control. ^ F r e y also suggests this notion. See, F.W. Frey, Regional Variations In Rural Turkey, Report iJo. 4, Rural Development Research Project (Cambridge: M.I.T. Center for International Studies, 1966), p. 1 0. ^Fi^ek and Shorter, op. clt., p. 584. Tumertekin, Internal Migration in Turkey (Istanbul: Geo graphical Institute, University of Istanbul, 1968), 94 In examining the cartographic portrayal of fertility ratios in Turkey* there appears to be a spatial pattern which closely resembles that of level of village development, or the cartographic distribution of Factor II scores (see Maps 10, 11, and 12). It is very possible that the level of village develop ment may be the most significant and most highly correlated "Factor” with fertility. It is hypothesized here that: Factor II (lhich describes a high level of village development) is, in fact, the most significantly correlated Factor with human fertility behavior throughout Turkey, and the relationship is a negative one. This hypothesis will be examined and tested elsewhere In this chapter. Table 13 illustrates the fertility ratios of the Turkish provinces, both for the "entire province" and for "places having a population of less than 10,000 persons." This table also presents the mean fertility ratio of each sub-system group (region). The lowest mean fertility ratio is that for Region 2; Region 1 is slightly higher. Regions 4 and 6 are quite similar - 758 and 754 respectively. Regions 3 and 8, which are contiguous to each other, are relatively close in their rather high mean fertility ratios. The highest, by far, is found in Region 7 (the southeastern-most sub-system), with a mean fertility ratio of 1041. 28 34 40 t W A R / 4 0 m! I--- — |---- 1 MILES 0 50 100 3 6 mediterranean SEA REPUBLIC of TURKEY Pttltlve Score Negative Score (Relatively High Level Village Development) (Relatively Low Level Village Development) HAP 10: DISTRIBUTION OP POSITIVE AND NEGATIVE SCORES: FACTOR II 'O ______I______L U1 MEDITERRANEAN SEA Less than 741 (National Mean - 741) Greater than 741 MAP 11: TURKISH FERTILITY RATIOS - ENTIRE PROVINCE (I960) 28 34 40 W 3ni ^0 3* MEDITERRANEAN SEA REPUBLIC of TURKEY (National Kean • 763) Greater than 763 MAP 12: TURKISH FERTILITY RATIOS - PLACES WITH LESS THAN 10,000 PERSONS (1960) vO ' - l TABLE 13 TURKISH FERTILITY RATIOS FOR ENTIRE PROVINCE (EP) AND FOR PLACES WITH LESS THAN 10,000 PERSONS (PLT): 1955 AND 1960 1955 1960 EP PLT EP PLT REGION 1 665 736 563 595 Edlrne 721 757 574 596 Kirkareli 692 719 563 581 Teklrdag 678 700 553 572 Izmir 570 647 497 523 Manisa 688 752 562 609 Aydin 662 867 550 564 Mugla 721 747 626 648 Istanbul 473 649 470 579 Kocaell 690 725 592 602 Sakarya 753 798 641 677 REGION 2 681 701 568 580 £anakkale 612 628 479 477 Balikesir 632 665 529 554 Bursa 610 649 497 509 Blleclk 617 624 456 455 Canklri 771 784 698 709 Kutahya 667 680 545 552 U$ak 769 795 654 681 Denizli 700 715 648 660 Isparta 752 776 605 623 REGION 3 848 911 842 895 Antalya 811 853 742 774 I^el 810 865 816 851 Adana 886 994 875 963 Hatay 977 1036 957 1010 Gaziantep 757 807 820 879 REGION 4 804 837 731 758 Burdur 743 777 617 645 Afyonkarahisar 789 799 689 707 Eski^ehir 646 723 580 643 TABLE 13 - Continued 1955 ______I960 EP PLT EP PLT Bolu 720 740 584 594 Zonguldak 788 798 684 686 Kastamonu 721 743 557 576 Ankara 706 848 702 795 Konya 786 818 731 767 Kir^ehir 915 936 855 887 Nev§ehir 802 819 699 718 Amasya 744 784 683 720 Kayseri 798 843 737 786 Sivas 833 848 798 806 Malatya 845 873 799 818 Erzincan 844 873 787 805 Tunceli 1030 1031 946 960 Erzurum 826 862 805 818 Kars 946 961 901 911 REGION 5 824 846 781 801 Slnop 785 794 691 696 Sarasun 816 863 778 814 Ordu 874 887 786 793 Tokat 779 819 720 760 (Jorum 760 780 693 714 Yozgat 824 833 786 792 Nigde 828 861 797 826 Mara 9 926 953 904 935 Adiyaman 802 811 858 867 Gumu§hane 849 863 797 809 REGION 6 842 854 748 754 Giresun 907 919 790 800 Trabzon 860 880 780 792 Rize 819 826 740 740 Artvin 784 791 680 684 REGION 7 1082 1098 1029 1041 Agri 1045 1060 978 983 Van 1030 1053 1002 1018 Hakkarl 1169 1180 1106 1115 100 TABLE 13 - Continued 1955______1960 EP PLT EP PLT Bltlis 1149 1177 1077 1110 Mu* 1076 1086 1037 1044 Blngol 1028 1035 975 977 REGION 8 914 947 907 923 Elazig 844 901 800 842 Diyarbakir 882 938 902 918 Siirt 1046 1074 990 987 Mardin 960 966 939 940 Urfa 838 860 906 927 TURKEY 763 843 741 764 101 Within each of the eight delineated regional type sub- systems, fertility behavior has some internal variation. As indicated by the range of fertility ratios (see Table 14), this variation can be observed. The mean fertility ratio for each sub-system, nevertheless, supports the observation that fertility increases going eastward, and more precisely, in a southeastward direction from Istanbul province. Although some internal variation exists in each of the regional type sub-systeras, on the whole, it appears that fertility ratios are relatively similar for most of the provinces in each of the delineated sub-systems. As opposed to the specific numerical ratios, if one were to designate fertility behavior as being low, moderate, or high, then it appears that relative internal homogeneity in each of the sub-systems does exist, with minor exceptions in one or two of the sub-systems. Thus, the first hypothesis, formulated in the opening section of this study, is accepted, bearing in mind that there are two or three exceptions in one or two of the sub-system groups. Recent Fertility Trends With reference to Table 13, in comparing the mean fertility ratios of the sub-system groupr for the 1955 period and the 1960 period, several interesting trends emerge. The general tone appears to be that of fertility decrease, with six of the eight groups 102 TABLE 14 MEANS, STANDARD DEVIATIONS, AND RANGES OF 1960 REGIONAL FERTILITY RATIOS Region Means Standard Deviations Ranges EP PLT EP PLTEP PLT 1 563 595 52 43 179 154 2 568 580 86 92 242 254 3 842 895 80 93 215 236 4 731 758 110 106 389 384 5 781 801 68 70 213 339 6 748 754 50 54 110 116 7 1029 1041 54 60 131 178 8 907 923 70 52 139 145 TURKEY 741 764 160 159 650 660 EP » Entire Province PLT - Places having less than 10,000 persons 103 showing lower fertility ratios for the 1960 period than for the 1955 period. Groups 6 and 2 have the greatest reduction in their re spective mean fertility ratlost with the other decreasing groups showing moderate to slight declines. Group 3, on the other hand, shows a moderate increase, and Group 8, a slight increase in mean fertility ratios. Both of these provincial groups have large segments of their population in rural areas which lack major developmental progress. The socio-economic, ethnic, and other basic characteristics of these two provincial groups have been discussed elsewhere (see Chapter II). The interesting observation, however, is the declining fertility trend of most of the sub-system groups. With regard to individual provinces, the same generalization may be applied, as most of these areal units reflect moderate declines. This is true if one observes the fertility ratios for the "entire province," as well as for the fertility ratios for "places which have less than 10,000 persons." One can assume that In the period of five years separating the two fertility ratio measurements, reporting and recording of vital statistics have Improved, rather than de teriorated. Thus, one can speculate that Turkey may have embarked upon the beginning trend of fertility decline. This, of course, may or may not be proven correct with more information forthcoming 104 from the Turkish Demographic Survey, or the next census of popula tion in 1970. Spatial Analysis of Fertility Correlates The spatial variations of fertility in Turkey certainly have implications on the domestic policies, social and economic institutions, and on future planning programs. What is of major importance and of major interest, however, and one of the major concerns of this study, are the spatial variations of fertility correlates. Identification of areas having high, moderate, or low fertility may indicate where policy formulation and implementa tion is needed. Identification of the most significant correlates of fertility, however, may Indicate what type of policy and what method of implementation would best give optimal results. In accordance with the objectives of this study, it was earlier hypothesized that spatial variations of fertility correlates exist within the context of regional type sub-systems. The analysis and discussion which follows, relates to the testing of this hypothesis. Independent Variable Correlations With Fertility Ratios In order to observe the relationship between fertility be havior (using the fertility ratio as the dependent vairable) and 105 14 variables from the original data matrix* the data were subjected to a correlation analysis. This procedure was carried out for all provinces, as a single group, in order to identify the most signifi cant correlates on a national level; and, for each of the eight de lineated sub-system groups, in order to identify the most significant correlates for each sub-system. TURKEY For the larger Turkish system, the correlation coefficients which were computed revealed relationships which, to some extent, support the findings of previous investigators. (See Table 15.) Basically, the variables which had the highest correlation coeffi cients could be grouped into four categories: (1) literacy/education; (2) level of village development; (3) indicators of information flow; and, (4) ethnic identity. From the point of view of the individual variables, "dis tance from Istanbul" had the highest correlation coefficient: r » +.89. Although in simple terms this may be interpreted as, the greater the distance from Istanbul, the higher the fertility, some interpretive insight as to its possible meaning should be given. As distance from Istanbul increases, accessibility to information Of the 69 variables in the original data matrix, 61 were used as the independent variables and 2 as the dependent variables (separately). Six variables which were of a demographic nature were deleted because of obvious non-relationships with fertility. 106 TABLE 15 CORRELATION ANALYSIS RESULTS: TURKEY r Variable .89 distance from Istanbul .82 per cent females Illiterate - places with less than 10,000 persons .81 per cent females illiterate .78 per cent males illiterate .78 , per cent males Illiterate - places with Jess than 10 ',000 persons -.74 per cent village population living in places having coffee house .73 population per radio .72 per cent population speaking Kurdish ,72 per cent village population living in places having guest house -.71 per cent village population living in homes with tile roof -.71 per cent population whose native tongue is Turkish .65 area per PTT establishment -.61 per cent roads which are all-season .61 per cent village population living in places with livestock as main source of income -.57 per cent villages with electricity -.51 per cent villages having piped water supply only -.50 per cent villages having piped water supply as part of water source All of the above correlation coefficients are significant at the 1% level. 107 and new Ideas decreases; a3 distance from Istanbul increases, levels of village development decline; as distance from Istanbul increases, literacy rates and educational levels attained decline. These are all factors which may be highly related to fertility rates and which, at the same time, are highly interrelated with distance measurements from Istanbul. With reference to the four categories mentioned above, it appears that variables measuring illiteracy had a high positive correlation with fertility behavior; variables which indicate a high level of village development registered high negative corre lation coefficients with fertility; inaccessibility to information flow, as measured by variables such as distance from Istanbul, number of persons per radio, and area per PTT establishment, had high positive correlation coefficients with fertility, while per cent roads which are all season - indicating good roads and acces sibility to information - registered a high negative correlation coefficient. Ethnic group identity indicated a negative relation ship with people who are Turkish speaking and a positive relation ship between fertility ratios and people who are Kurdish. The only economic type variable which emerged in this analysis as having greater than a .50 ijj.relation coefficient, was the per cent pop ulation living in villages where livestock raising was the major source of income. This variable registered an r of +.61, indicating 108 a moderately high positive correlation with fertility. This might have been expected, since this type of activity for a major source of Income in Turkey is found especially in areas having marginally productive land and in areas where developmental levels in agri culture are rather low. This is also, as was brought out in the previous chapter, an activity which goes almost hand-in-hand with the Kurdish ethnic element. REGION 1 In Region 1, which is a region of high level village development, industrial crop and vineyard crop agriculture, and which contains several large urban centers (Istanbul and Izmir), the variables related to fertility are shown in Table 16. In a region having large urban centers, one would likely find that there would be a relatively high number of single women 15 years and older; this would be especially true between the ages of 15 years and the early twenties. Early marriage and female parti cipation in marriage are common traits in traditional areas of Turkey, but this is no longer the case in the large urban centers, especially 15 Istanbul and Izmir, both in Region 1. Therefore, "per cent females 15 years and older who are single," has a high negative correlation ^See, N. Eren, op. cit., pp. 176-83; and P. Stirling, Turkish Village (New York: John Wiley, 1965), pp. 178-220. 109 TABLE 16 CORRELATION ANALYSIS RESULTS: REGION 1 r Variable -.90 per cent females 15 years and older who are single .85 per cent population having more than primary schooling who are male -.82 per cent population urban -.80 total population .79 per cent population living in villages -.79 per cent economically active males 15 years and older in tertiary activities -79 population per radio -.76 per cent economically active males 15 years and older in white collar employment -.76 number of printing houses per 100,000 population All of the above correlation coefficients are significant at the 1% level. TABLE 17 CORRELATION ANALYSIS RESULTS: REGION 2 r Variable .85 9 per cent village population living in places with livestock as main source of income .83 if distance from Istanbul .81 if per cent females illiterate -.79 * per cent area sown in pulses .78 it per cent females illiterate - places with less than 10,000 persons -.75 * per cent village population living in home with tile roof .73 * population per radio - .6 8 * per cent sown area in pulses if significant at the \% level * significant at the 5% level 110 with fertility ratios. It is, of course, obvious that the greater the number of single women, the fewer pregnancies will occur, hence fewer births. Urbanization, total population, and several economic vari ables associated with urban forms, all correlate negatively with fertility in this region. Population per radio, an indicator of information flow, correlates positively with fertility; that is, where the number of persons per radio is high - interpreting this to mean inaccessibility to information for a large number of people - fertility may be high. On the other hand, the number of printing houses, which may be interpreted as another variable indicating flow of information, has a negative correlation with fertility. REGION 2 The second region was identified as being one of high level village development with pulses being the important agricultural commodity. Industrial activity is somewhat limited, as is the number of urban centers. For this region, the correlation coef ficients of the highest correlated variables with fertility are presented in Table 17. Livestock raising as a major source of income and emphasis in pulse crop agriculture have, as economic activities, high corre— Ill latlons with fertility; the former being a positive correlation and the latter a negative. There is obviously some relationship here between the type of agricultural activity and fertility, which is probably indirectly reflected by the relationship be tween the agricultural activity and level of development. Along with this explanation, it also appears that the variable "per cent village population living in homes with tile roof" - indi cating a relatively high level of village development - shows a moderately high negative correlation with fertility. Illiteracy, distance from Istanbul, and population per radio, show high posi tive correlation coefficients, again supporting the notion of high fertility associated with inadequate Information flow. REGION 3 The provinces in this region are industrializing rapidly, and they are attracting many in-migrants as laborers. Although urban growth has been rapid, agrarian structure and level of devel opment remains rather low. Agriculturally, this is a region of important fruit, nut, and industrial crop growing areas. Here (see Table 18), the variables which tend to correlate In a positive manner with fertility are agriculturally based: per cent village population living in places where livestock Is the main income source, and cattle density. Although the correlation 112 TABLE 18 CORRELATION ANALYSIS RESULTS: REGION 3 r Variable -.93 per cent villages having piped water supply only .89 * per cent village population living In places with livestock as main source of Income - .8 8 * per cent village population living In places having guest house - .8 8 * population density - .8 8 * per cent population whose native tongue is Turkish -.83 per cent economically active males 15 years and older in tertiary activities .82 number of cattle per unit area (kn*) -.81 per cent village population living in places with cooper atives .81 per cent economically active males 15 years and older in primary activities -.79 per cent villages with sewerage tfsignlfleant at 12 level *significant at 5% level TABLE 19 CORRELATION ANALYSIS RESULTS: REGION 4 r Variable -.56 per cent villages having piped water supply as part of water source -.56 per cent village population living in homes having tile roof -.52 per cent villages with electricity -.50 per cent village population living in places having coffee house .50 per cent females illiterate .49 population per automobile -.47 per cent village population living in places having guest house All of the above correlation coefficients are significant at the 5% level only. 113 coefficients are not statistically significant, cattle density and per cent economically active males in primary activities are positively correlated with the fertility ratio. Most of the variables with high correlation coefficients in this region tend to be negatively related to the dependent variable- Those which are statistically significant are: per cent villages having a piped water supply only, villages with guest houses, population density, and per cent population whose native tongue is Turkish. The first two variables are obviously indica tors of high level village development. Several other variables which are also indicators of village development, register nega tive correlation coefficients, but are not statistically signifi cant: villages with sewerage, and villages having cooperatives. Population density may be an indicator of urbanization, a factor 16 vjhich has been identified with lower fertility behavior in Turkey. Although not statistically significant, but registering a high negative correlation coefficient, is the variable: per cent economically active males employed in tertiary activities. This also carries with it an urban connotation. The last of the statistically significant negatively correlated variables, per cent population whose native tongue is Turkish, is of paramount importance in this region. As was pointed out previously (see ■^Thls is implied by the data presented in P. Demeny and F.C. Shorter, op. cit. 114 Chapter II), this region has a rather depressed proletariat which 17 Is, to a large extent, Arabic speaking. It is highly feasible that in this region, fertility behavior differentials may be very closely related to cultural differences. From the analysis, it appears that the Turkish speaking ethnic group would tend to have lower fertility patterns. REGION 4 This is the largest of the delineated regional sub-systems and Is primarily a cereals growing region. Urbanization and in dustrialization are limited primarily to the Ankara and Eskl$ehir areas. The major correlates of fertility and their coefficients of correlation are presented in Table 19. Here, as in the pre viously discussed regions, indicators of high level village de velopment - per cent village population living In homes with tile roofs, villages with piped water as part of their water source, with electricity, with coffee houses, with guest houses - have negative correlation coefficients with the dependent variable. The two variables which have positive relationships with fertility are: per cent females illiterate in the entire province and pop ulation per automobile. The latter may be construed as being an Mango, op. cit., p. 143. 115 indicator of low level development, and the former may carry several connotations. It may be related to the prevelance of a traditional form of Turkish life, as a buffer to receiving information, and as an indicator of low social development. Regardless of the exact interpretation, female illiteracy is a strong correlate of high fertility behavior. REGION 5 This region is characterized by a moderate level of village development and high population concentrations in localized areas. Some industrial crops are of agricultural importance and the region lacks any significant urban type development. Table 20 illustrates that In this region too, female illiter acy has a significantly high positive correlation with human fertil ity. The ethnic variable - per cent population speaking Kurdish - emerges as a significantly high positively correlated variable with fertility. The other ethnic variable - per cent population whose native tongue is Turkish - on the other hand, registers a signifi cantly high negative correlation with fertility. Two variables which represent good quality roads are both significantly high in their negative correlation coefficients. This nay be a developmental factor, as well as a factor Indicating information flow, or possibly, both. 116 TABLE 20 CORRELATION ANALYSIS RESULTS: REGION 5 r Variable -.77 H ratio: all season roads/fair weather roads .75 * per cent females Illiterate - places with less than 10,000 persons .75 * per cent population speaking Kurdish -.71 * per cent population whose native tongue is Turkish -.71 * per cent roads which are all season .70 * per cent females illiterate if significant at IS level * significant at 5% level TABLE 21 CORRELATION ANALYSIS RESULTS: REGION 6 Variable .99 if per cent females illiterate - places with less than 10,000 persons .98 * per cent females illiterate -.98 * per cent village population living in places with crops as main source of income -.96 per cent sown area in cereals -.92 per cent automobiles privately owned -.92 KITH energy consumed for industry in places other than pro vincial centers -.92 per capita energy consumption -.91 KITH energy consumed for industry in entire province -.91 per cent villages with electricity if significant at 1Z level * significant at SZ level 117 REGION 6 This region of important fruit and nut growing areas and densely populated village areas, also indicates a strong positive relationship existing between female illiteracy and fertility ratios (see Table 21). Per cent village population living in places where crops are the major source of income - an indicator of economic prosperity in this region - registers an extremely high negative correlation coefficient with fertility. Although not statistically significant, per cent sown area in cereals also indicates a negative correlation coefficient. In this region, cereals are another important commercial crop. The remaining variables which had high, but not statistic ally significant, correlation coefficients with fertility ratios, all are Indicators of economic development. Although most of these variables are related to the consumption of electrical energy, since this region has relatively little industrial activity, it might be assumed that energy consumption here is related to the high level of village development, e.g., many of the villages have electricity (which is also included as a high negatively correlated variable with fertility). Energy consumption may also involve re lated economic activities, such as food processing and the like. 118 REGION 7 In this region of strong Kurdish population concentrations, whatever agricultural development in the form of commercialized crops exists, it tends to be negatively correlated with fertility ratios. As illustrated in Table 22, areas sown in industrial crops and in cereals both have high negative correlation coeffi cients with fertility. On the other hand, the variable indicating sheep density, registers a high positive correlation coefficient, although this is not statistically significant. Male illiteracy appears to be positively correlated with the fertility ratio vari able, but again, not In a statistically significant relationship. REGION 8 This is also a region having strong Kurdish concentrations in its population composition. The only agricultural crops of some commercial significance appears to be pulses. In this region, the ethnic differences appear as significant correlates with fertility: per cent population whose native tongue is Turkish, having a high negative correlation, while per cent pop ulation speaking Kurdish has a high positive correlation coefficient (see Table 23). Per cent sown area in pulses and villages with coffee houses both indicate high negative correlations with fertility. These are apparently the few Isolated areas of some economic prosperity. 119 TABLE 22 CORRELATION ANALYSIS RESULTS: REGION 7 Variable .86 * per cent sown area in industrial crops .83 * per cent area sown in industrial crops .73 per cent sown area in cereals .73 number of sheep per unit area (kra2) .72 per cent males illiterate .71 per cent males illiterate - places with less than 10*000 persons * significant at 5 Z level TABLE 23 CORRELATION ANALYSIS RESULTS: REGION 8 r Variable .95 * per cent population whose native tongue is Turkish -.94 * per cent sewn area in pulses .93 * per cent village population living in placeshaving coffee house .91 * per cent males illiterate .91 * per cent males illiterate - places with less than 1 0 ,0 0 0 persona .91 * per cent population speaking Kurdish .88 * number of goats per unit area (kn»2) .86 per cent females illiterate - placeswith less than 1 0 ,0 0 0 persons * significant at 5 Z level 120 The variable measuring goat density is highly correlated with fertility- It should be noted that in Turkey, wherever goata are found in large numbers, other types of land use are almost Impossible because of the limitations imposed by the physical environment . The raising of goats is prevalent among many of the Kurdish tribal groups and epitemizes subsistence type agri culture. In Region 8, as in several other regions, the variables of illiteracy indicate high positive correlations with fertility. This is true here for both male and female illiteracy variables. Multiple Correlation Analysis of Selected Independent Variables In order to further test the hypothesis that: spatial variations of fertility correlates exist from one sub-system to another, both in the variables themselves and in their explana tory power; the data were also subjected to a multiple correla- 18 tion analysis. Only those independent variables which achieved 18 This was achieved by the use of the multiple regression model of the general form: Y i* ai + b lixli + b2ix2i + ***+ ^ni^ni where: Y^ denotes the fertility ratio in sub-system i; X ^ , Xj^-.-X^ represent the independent variables for the sub-system i; and, a^, bli’ b 2i***bni are constants. For a discussion of multiple correlation, and regression analysis, see, H.M. Blalock, Social Statistics (New York: McGraw-Hill, 1960), Chapter 19. A Multiple Stepwise Regression computer program was used for this analysis. The original version of the program was written at the Health Sciences Computing Facility, Department of Preventive 121 relatively high correlation coefficients in the preceding analysis were used. What is of primary interest here, in order to test this hyposthesis, is the explanatory power of the independent variables taken together, rather than in the relationship between the depend ent variable and each of the independent variables taken separately. Since the analysis was not Intended for forecasting purposes, the variant of the program giving zero intercept was chosen. The results of this analysis are presented in Table 24. Although the analysis was performed for the Republic of Turkey and for each of the regional type sub-systems, the results in the table are for the Republic and only Regions 1, 2, 4, 5, and 7. The re sults for Regions 3, 6, and 8, are of little consequence, since the sample size of their respective membership provinces were too small to work with, in this statistical procedure. However, from the simple correlation analysis, one is able to ascertain which of the independent variables in these regions (3, 6, and 8), had the highest significant correlation with fertility, but unable to determine the explanatory strength in a "multiple-variable" construct. An examination of Table 24 indicates that "distance from Istanbul" accounts for 78 per cent of the explained variance for Medicine and Public Health, School of Medicine, U.C.L.A., and is ident ified as BMD02R. A version modified by Anita Harwick at The Ohio State University was used here. TABLE 24 MULTIPLE CORRELATION ANALYSIS RESULTS Step Variable R R2 Increase TURKEY 1 distance from Istanbul .8849 .7831 .7831 2 area per PTT establishment .9154 .8380 .0549 3 per cent village population living in places having guest house .9313 .8672 .0292 4 per cent population whose native tongue is Turkish .9446 .8923 .0251 5 per cent females illiterate .9542 .9106 .0182 (excluding "distance from Istanbul") 1 per cent females illiterate .8209 .6739 .6739 2 per cent population whose native tongue is Turkish .8879 .7885 .1144 3 per cent village population living in places having guest house .9202 .8468 .0586 4 per cent village population living in home with tile roof .9444 .8918 .0450 REGION 1 1 per cent females 15 years and older who are single .8952 .8014 .8014 2 per cent males Illiterate .9780 .9564 .1550 3 per cent village population living in places with crops as main source of income .9891 .9783 .0219 TABLE 24 - Continued Step Variable R R2 Increase REGION 2 1 per cent village population living in places with livestock as main source of income .8526 .7269 .7269 2 per cent females illiterate .9729 .9466 .2196 3 KWH consumed for industry in places other than provincial centers .9913 .9826 .0360 REGION 4 1 per cent villages having piped water supply as part of water source .5619 .3158 .3158 2 per cent villages having piped water supply only .7339 .5386 .2228 3 per cent village population living in places with livestock as main source of income .8305 .6898 .1512 4 population per automobile .8869 .7867 .0969 5 per cent area sown in pulses .9109 .8298 .0431 6 per cent population urban .9440 .8912 .0614 TABLE 24 - Continued Step Variable R R2 Increase REGION 5 1 ratio: all season roads/fair weather roads .7661 .5870 .5870 2 number of cattle per unit area (k®2) .9038 .8160 .2299 3 per cent villages having piped water supply as part of water source .9553 .9120 .0957 4 per cent area sown in pulses .9849 .9701 .0575 REGION 7 1 per cent sown area in industrial crops .8602 .7399 .7399 2 per cent males illiterate .9977 .9954 .2555 Note: Positive and negative signs are irrelevant for these type correlations. The direction of the multiple has no meaning, since it involves correlations with a number of variables. By convention, the positive square root of R^ is always taken in denoting the multiple correlation coefficient. See, Blalock, op. cit., p. 347. An analysls-of-variance teat for significance revealed that all of the above multiple correlations were significant. Results for Regions 3, 6, and 8 were omitted for reasons discussed in the text. 125 the Republic of Turkey. If this variable is deleted from the multiple correlation model, a total of 90 per cent of the varia tion is then explained by the following four variables: per cent females illiterate: entire province (R2 ■ .67); per cent population whose native tongue is Turkish (R » .11); per cent population living in villages having a guest house (R2 ■ .06); and, per cent village population living in homes having a tile roof (R2 ■ .05). The last two variables, which indicate a relatively high level of village development, add approximately 11 per cent to the explained variation. For each of the delineated regions, the variables which have the most explanatory strength are summarized as follows: Region 1 : per cent females 15 years and older who are single (R2 « .80) per cent males illiterate: entire province (R2 * .16) Region 2 : per cent village population living in places with livestock as the main source of income (R2 - .73) per cent females illiterate: entire province (R2 * .22) Region 3: per cent villages having piped water supply only (variable with highest correlation coefficient) Region 4: per cent villages having piped water supply as part of water source (R2 - .32) per cent villages having piped water supply only (Rz * .22) per cent population living in villages (R2 » -15) population per automobile (R2 " .10) Region 5 : ratio: all seasons roads/fair weather roads (R2 ■ .59) number of cattle per unit area (km.2) (R2 ■ .23) per cent villages having piped water supply only (R2 * .10) TABLE 25 CORRELATION COEFFICIENTS OF FERTILITY RATIOS WITH DELINEATING FACTORS BY REGIONS Region FACTOR jrkey 1 2 3 4 5 6 7 8 I -.22 -.75* -.01 .64 -.06 .31 .64 .18 -.65 II -.88* ,07 -.58 -.91* -.72* -.66* -.95* -.79 -.93* III -.02 .03 .12 .23 .04 .24 .84 .70 .36 IV .12 -.34 .71* -.37 .03 -.31 -.69 -.77 -.61 V .11 .36 -.83* .19 .05 -.27 -.76 -.38 . 36 VI .03 -.67* .02 -.37 .38 .17 .72 -.52 .55 VII -.13 .30 -.06 -.58 -.26 -.16 -.97* .39 .23 VIII -.19 -.45 -.46 .07 -.25 -.41 -.98* .55 .50* * Significant at the 5Z level. 127 Region 6: per cent females illiterate: entire province (variable with highest correlation coefficient) Region 7: per cent sown area In industrial crops (R * *74) per cent males illiterate: entire province (R^ ■ .20) Region 8: per cent population whose native tongue is Turkish (variable with highest correlation coefficient) The above summary does, in fact, suggest that there are variations in regional fertility correlates, both in terms of the individual variables themselves, and in their explanatory strength. This tends, therefore, to verify the acceptance of the hypothesis that spatial variations of fertility correlates exist in the Turkish system of regional type?. However, the acceptance of this hypothesis must be made bearing in mind the fact that the variables which give greatest explanatory strength in each province, are those variables which appear to be almost directly related to both economic and social development. Delineating Regional Factors and Fertility Ratios A correlation analysis was performed using fertility ratios as the dependent variable and the factor scores of each of the eight factors previously used (see Chapter II) to delineate the regional type sub-systems. The purpose of this analysis was to investigate whether or not there was any significant relationship between fertility and the clusters of interrelated variables which differ entiate the regional type sub-systems. It was earlier hypothesized 124 that of the major clusters of interrelated variables, that factor which described a high level of village development (Factor II), would be most significantly correlated with fertility, in a nega tive relationship. The resultant correlation coefficients of this analysis are presented in an 8 x 9 matrix of 8 Factors on 9 regional systems (the Republic of Turkey and the 8 delineated sub-systems), in Table 25. As illustrated in this matrix, in Region 1 , high level urban development and population concentrations (which would likely go together), Factors I and VI respectively, have significant nega tive correlations with fertility. Region 2 displays a significant positive correlation between the dependent variable and Factor IV (agricultural land use in cereals with a low level of village devel opment); and, a signficant negative correlation between the dependent variable and Factor V (absence of pulses). Both Regions 1 and 2 display relatively low fertility behavior, compared to the other regional sub-systems. Regions 3, A, 5, 6, and 8, which vary from moderate to high in fertility behavior, all share significant negative correlations between Factor II (relatively high level of village development) and the dependent variable. Region 6, in addition to having this signi ficant correlation on Factor II, also has significant negative corre 129 lations between fertility ratios and Factor VII and VIII (Industrial activity and high level village development in western Turkey). Region 8, which has been included In the group of regions having a significant negative correlation between Factor II and fertility ratios, also has a significantly high positive correlation between the dependent variable and Factor VIII. It should be noted that for the eastern provinces (which make up the membership of Region 8), Factor VIII was identified as being "Kurdish ethnic identification with livestock raising activity" (see Chapter II). R egion 7, which has the highest fertility behavior of all the sub-systems, had no correlation coefficients which are statis tically significant at either the 1 per cent or 5 per cent levels. However, this sub-system did have three moderately high coefficients of correlation. High negative coefficients were recorded for Factor II (relatively high level of village development), and Factor IV (agricultural land use In cereals). Factor III (agricultural land use in fruits and nuts with some industrial crops) registered a moderately high positive correlation coefficient with fertility ratios. On the national level, the highest and only significant correlation coefficient is that for Factor II, a negative relation ship between fertility and level of village development. 130 It appears, from the 8 x 9 matrix of correlation coeffi cients (Table 25), that six of the eight delineated regions indi cate a significantly high negative correlation between fertility ratios and the level of village development factor- Interestingly, this is not the case for Regions 1 and 2, with the lowest fertility ratios of the sub-systems. As mentioned previously, the map indi cating village development and that map which portrays fertility variations, appeared to be strikingly similar. It does appear that the two are indeed highly correlated with each other and the pre viously made hypothesis concerning this relationship, is accepted. Further support is given to this by the fact that Factor II, in a 2 multiple correlation analysis, registered an R of .8 8, and an R of .77 (accounting for 77 per cent of the explained variation). Summary This chapter of the study was devoted to an analysis of human fertility and its correlates, in Turkish sub-systems. The regional type sub-systems which were delineated in the previous chapter, were utilized in this chapter for the analysis of regional variations of fertility, as well as fertility correlates. After some introductory statements concerning the implications of util izing a rigorously delineated system of regions, several previous research Investigations of Turkish fertility behavior were noted. 131 The use of the "fertility ratio" measurement, as the dependent variable, was discussed and explained. Insight was given Into the spatial variations of Turkish fertility behavior and recent temporal trends in this behavior were noted. The purpose of this chapter was to perform analyses on the data in order to identify the most significant correlates of fertility and to identify those correlates which had the great est explanatory strength. Simple correlation and multiple corre lation analyses were used here, for these purposes. These analyses provided the basis for the acceptance of the hypotheses that: (1) spatial variations of fertility correlates exist from one sub-system to another, both in the vari ables themselves and in their explanatory power; and, (2) level of village development is most significantly correlated with fertility (where level of village development Is an index made up of many interrelated variables, e.g., Factor II). The results of the findings of this chapter are of major importance for economic, social, and political policy formulation. The implications of these results are presented in the following chapter. CHAPTER IV CONCLUDING STATEMENTS The purpose of this study has been to analyze the correlates of human fertility within a delineated system of regional types in the Turkish Republic. It was the dual ob jective of this study to identify and analyze the spatial vari ation of reproductive behavior and primarily its correlates, as well as to delineate regional type sub-systems for utilization as a framework through which this analysis could occur. Results and Interpretations In accordance with the set purpose and objective of this study, a series of questions were posed, forming the Investigative core of this undertaking. The following discussion centers around these questions and the findings of this study, as they relate tc these questions. (1) On the basis of interrelated and interdependent social, econ omic, and demographic characteristics of areal units within the larger system of Turkey, what are the regional types or sub-systems which emerge? It was found that slightly over 75 per cent of the variance 132 133 of the 67 provinces of Turkey on 69 variables, could be accounted for by eight dimensions or factors. The eight factors which dif ferentiate the sub-systems of Turkey are: (1) relatively high level of urban development; (2) relatively high level of village development; (3) land use in fruits, nuts, and to some extent, industrial crops; (4) land use in cereals; (5) land use in pulses; (6) population concentrations; (7) industrial activity; and, (8) level of rural development for western Turkey and an ethnic identification and livestock activity for eastern Turkey. Through a grouping procedure, based on the principle of the discriminant function, the 67 Turkish provinces were grouped into eight regional type sub-systems, minimizing within group variances, while max imizing between group variance. It was found that the spatial organization of Turkey, or the state of the larger system, was greatly influenced by agrarian structure and land use patterns. Although this is not surprising in a system heavily dependent upon an agricultural economy, the regional type sub-systems which emerged, give a more accurate presentation and a more precise description of the characteristics which differentiate these segments of the larger whole, than has been previously delineated. Although spatial contiguity was not a constraint set upon sub-system membership, provincial members of most of the delineated sub-systems were, in fact, contiguously 134 arranged In space. Geographically, the eight sub-systems are organized In such a fashion as to clearly distinguish one segment of the Republic from another, in a general sense. The eight regional type sub-systems which emerged, on the basis of interrelated and interdependent spatial attributes are: Region 1: Ten provincial members, located along the Aegean coastal area, Thrace, and two provinces adjacent to Istanbul, make up this grouping. It has been identified as a region of high level village, high level urban, and high level socio economic development. Its agricultural base is primarily In industrial crops and fruits (mainly vineyard type). Region 2: This region is composed of nine provincial members, located in the western portion of the Republic. It is character ized as being a region of relatively high level village develop ment with land use in pulses being relatively important. Region 3: This group of provinces emerged as a contiguous array of five areal units along the Mediterranean coast of south-central Turkey. It is a region of low village developmental levels, but paradoxically, relatively high levels of urban structure and de velopment. Agrarian land use here is dominant in fruits, nuts, and some forms of industrial crops. It is also a region which 135 has substantial non-Turkish ethnic groups (Kurds and Arabs). Region 4: The largest sub-system emerged with eighteen provincial members, extending from western Anatolia across to the northeastern provinces. The spatial attributes of this regional type are pri marily in its relatively low level of village development and the emphasis of cereals in its agriculturally dominant economy. Region 5: Ten provinces located in the central-eastern segment of Turkey, peripheral to Region 4, make up this sub-system. Al though lacking in urban development, it is moderately developed in its village structure, and characterized also by high local population densities. Agriculturally, industrial crops appear to be the major land use. Region 6: Composed of four contiguously arranged provinces along the Black Sea coast of northeastern Turkey, this regional type sub-system is characterized by a relatively low level of urban development, but a relatively high level of village develop ment, Its major economic activity is heavily dependent upon fruits, nuts, cereals, and industrial crops - indicative somewhat of a mixed farming type region. Region 7: Located in the far southeastern portion of the country, the six contiguous provinces of this sub-system are differentiated 136 on the basis of their extremely low levels of urban and village development. The most common attribute among these provinces is its large Kurdish population. Economically, this relatively bleak regional type is void of major commercial activities, even in the agricultural sector. Livestock herding appears to be its major activity, and much of this is a subsistence type activity. Region 8: Five provinces, contiguously arranged in the near southeastern segment of Turkey, delineate this regional sub system. Their common attributes are primarily in their large Kurdish populations, low level village and urban development, and pulses as their only land use of any consequence. It has been clearly established here, that on the basis of the interrelated and interdependent variables utilized to describe the attributes and spatial organization of individual members of the larger Turkish system, these individual provinces can be grouped into an array which delineates eight separate sub systems. (2) What spatial patterns and variations in human fertility be havior exist in Turkey? Do these spatial patterns and vari ations relate to the delineated system of regional types? With the absence of precise data for the measurement of fertility behavior in Turkey, the "fertility ratio" measurement was computed for each of the 67 provincial units of the Republic. 137 Although this study has been concerned with the period of 1960, measurements were also calculated for the period of 1955, in order to make temporal comparisons. Fertility ratio means were computed for each of the eight delineated regional type sub-systems, along with their ranges and standard deviations. Fertility ratios were computed for the "entire province" and for "places having less than 10,000 persons". The former being a measure of aggregate fertility behavior of the entire provincial population, in all segments of economic life and in all levels of settlement. The latter, on the other hand, was more indicative of fertility behavior in rural areas, villages, and small towns. The differences between the fertility ratios for the "entire province" and for those "places having less than 10,000 persons" were clearly visible from the data, as well as from the analysis. Almost all of the provinces had lower fertility ratios for the "entire province" than for "places having less than 10,000 persons." This was also the case when comparing the sub-system mean fertility ratios for each of these two categories. A distinct spatial pattern of fertility behavior was identified through cartographic analysis, as well as through the utilization of the Surface Trend Analysis technique. It was found that fertility is lowest in the western portions of the Republic, and tends to increase with distance, in an eastward-southeastward 138 direction. The spatial patterns of fertility behavior appear to be so distinct and so closely related to the patterns of development, that it was reasonable to assume that these two phenomena are strongly interrelated. More specifically, the spatial patterns of village development and those of fertility behavior were almost identical. It is also quite feasible that the distance from Turkey’s major metropolitan areas, Istanbul, is closely related to fertility behavior - this was, in fact, detected in the analysis of fertility correlates. As the distance from Istanbul province increases, the accessibility to ideas, information, and trends which would influence fertility behavior, obviously declines* Within each of the delineated regional type sub-systems, fertility behavior appeared to have some internal variation, with the range between the highest and lowest ratios noted. Even with these internal variations, on the whole it appeared that fertility behavior in most of the delineated regional sub-systems was generally similar. This is especially true if one were to classify fertility behavior on the basis of low, moderate, and high, as opposed to the specific numerical ratios. Regions 1 and 2 (in the western portion of Turkey), had relative homogen eity with regard to having relatively low internal fertility ratios. Regions 4, 5, and 6 (in the central, north-central, and 139 northeastern areas of the country), appeared to have relatively moderate-to-high fertility ratios, with several provinces In each of these sub-systems showing deviations from the regional norm. This was especially true in Region 6, with the relatively low fertility ratios of Rize and Artvln provinces. The highest fertility behavior, also having relative internal similarities, was for Regions 3, 7, and 8 (which are contiguous to each other), which lie in Turkey's south, southeastern, and eastern areas. In analyzing temporal change and differences between the 1955 and 1960 fertility ratio measurements, it was observed that fertility had declined in almost all of the provincial units. This appeared the case using the fertility ratio measures for the "entire province” and those for "places having less than 10,000 persons.” Although It was speculated that Turkey may have, in fact, embarked upon a trend of general fertility decline, this speculation can only be verified with the use of data which are, as of this time, unavailable. Thus, the spatial patterns and variations of fertility behavior in the Republic of Turkey have been identified and an alyzed. In general, these variations and patterns conformed with the delineated sub-systems and provided the basis for accepting the first hypothesis stated in the opening chapter: Reproductive behavior is a response influenced by 140 and derived from certain inherent characteristics of a sub-system (region) within a larger system* The spatial variations of this behavior can be associated with the spatial variations of these characteristics. Through identifying the spatial patterns of fertility behavior and associating these patterns with the delineated sub-systems, the basis for the analysis of fertility correlates was established. (3) What are the major correlates of this fertility behavior in the larger system and in each of the sub-systems? Are these correlates similar within all sub-systems? and (4) What is the explanatory strength of these correlates? Do they explain fertility behavior in a similar way in all regions, or are there significant regional variations in their explanatory strength? The utilization of correlation analytic procedures, both bi-variate and multiple variable model types, were made to identify the most significant correlates of human fertility and to analyze the explanatory strength of each of the most significant correlates. These procedures were performed for the larger system of Turkey and for each of the eight delineated sub-systems. For the larger system of Turkey, the major correlates of fertility were identified as being variables which were grouped into four categories: (1) literacy/education; (2) indicators of information flow; (3) level ov village development; and, (4) ethnic 141 group identity. In terms of individual correlates, "distance from Istanbul" was the most significant variable which correlated with fertility, in a positive relationship. This finding added further support to the observation and comments made previously (in the discussion under question 2), regarding fertility be havior and those factors which are interrelated with distance from Istanbul, e.g., accessibility to information, development, and literacy. It was found that (with significant variables correlated simultaneously) five variables accounted for 91 per cent of the explained variance. These were, in order of explana tory strength: distance from Istanbul; areas per PTT establish ment; per cent village population living in places with a guest house; per cent population whose native tongue is Turkish; and, per cent females illiterate: entire province. It was further found that with the "distance from Istanbul" variable deleted, the simultaneous correlations accounted for 89 per cent of the explained variation, through the following corre lates: per cent females illiterate: entire province; per cent population whose native tongue is Turkish; per cent village pop ulation living in places having a guest house; per cent village population living in homes having a tile roof. These variables appear in the order of their explanatory strength. It Is appar ent that in the larger Turkish system, literacy offered the 142 greatest explanatory strength, v:hen distance from Istanbul was not considered, confirming and supporting the findings of pre vious investigators. Ethnic group identity and level of village development offered further explanation of the variance. For each of the eight sub-systems, the most significant correlates of fertility were identified. These correlates were further analyzed and, in each sub-system, their explanatory strengths revealed that several independent variables, when simultaneously correlated with fertility, did account for large percentages of the explained variation. The analyses confirmed the hypothesis that fertility correlates do vary among sub systems, both In signficant relationships, as well as in their strength in accounting for explained variations. It was noted, in accepting the hypothesis, that the variables which give the greatest explanatory strength in each provincial grouping, are also variables which appear to be related to economic and social development. Since many of the significant variables appeared to be interrelated, a further analysis was made, correlating the de lineating "factors" with fertility behavior. It was also hypo thesized that the "high level village development" dimension - Factor II - would be the most significantly correlated factor, when applied as an independent variable. The results of the 143 analysis confirmed this hypothesis. It also indicated that for the larger system, as well as for those sub-systems in which fertility ratios are either moderate or high, "high level village development" was a significantly high negatively correlated factor. In those regions where fertility ratios are relatively low, this did not appear to be the case: in Region 1 , high level urban development (Factor I) and population concentrations (Factor VI) were significant negative correlates; in Region 2, land use dimensions - pulses (Factor V) and cereals (Factor IV) - were the significant correlates, the former negative and the latter positive. With reference to the posed questions 3 and 4, it was concluded that meaningfully significant correlates of fertility could be, and were identified. It was further concluded that within the context of the delineated regional type sub-systems, the correlates of human fertility behavior do vary from one sub-system to the next - both in their significant relationships with fertility, as well as in their explanatory strength. Implications It is not difficult to recognize that a population problem exists in Turkey, and that its spatial variation is identifiable. Those provinces which appear to be the least developed economically. 144 socially, and in institutions of a higher developmental level, are the provinces which can least afford large numbers of young dependents. Paradoxically, these also are the very provinces in Turkey which reflect the highest fertility behavior. Even the crudest type of statistical data which exist, make this evident. In an absolute quantitative sense, population density In many of the regions of Turkey is considerably low. However, if one takes into account the qualitative aspects - the quality of the land and the economy of the province, as well as the attributes of its population - then most of Turkey would be considered densely over-populated at this time. The lagged difference between population growth and economic growth and development, often results in poverty, disguised unemployment, and numerous social problems for a large segment of Turkey's population, especially In the agrarian sector. Internal migra tion from poverty-stricken rural areas of the country into the urbanizing centers of the Republic has been prompted by "popula tion pressure" on available resources in much of Turkey. How ever, migration has not resulted In an adequate solution to the host of problems which axist; rather, it has created a whole new dimension of social, political, and economic diffi culties in both place of destination and place of origin. 143 To cope with the increasing population and the multiple problems which result, programs for the modulation of population growth will be necessary. These will be extremely costly, will extend over long periods of time, and may produce results that will be obscure in the initial phases. Some programs will, un fortunately, fail to penetrate to the population sectors most concerned, and some approaches may have a negative rather than a positive effect. Therefore, it is of utmost importance that preliminary studies be conducted regarding the type of program one is to recommend and the method through which this program should be implemented. It is not the purpose here to either recommend a particular program, nor to criticize existing ones. The major implications which come from this study are the research findings, which have great practical applicability. More specifically: (1) This has been the first major attempt to de lineate multivariate sub-systems of regional types in the Repub lic of Turkey. The advantages of utilizing such a system are many. Certainly, the characteristics and attributes of the various sub-systems delineated in this study offer greater in sight into regional disparities and variations, than do admin istrative sub-divisions or physical features of the landscape, which are so frequently employed for delineating purposes. Since 146 family planning programs are still In an experimental stage of development, there is often need for precise data for large program-developraent areas, and even for small experimental areas, In order to evaluate different program designs. In dealing with human behavior and human attitudes, policy makers and those who implement the policies, cannot rely on the utilization of ad ministrative regions, or regions delineated on the basis of physical features. Regions must be utilized where the delineating basis has been the multiple characteristics of the place, and more important, of the people living in the place. (2) With the correlates of fertility identified, and their explanatory power analyzed, it is possible that pro grams of population control may utilize this information. This study has revealed that in certain regional type sub-systems, fertility has a negative relationship with certain characteristics of the place and of the people, and positive relationships with other characteristics. These identified relationships have pos sible utilization as the basis of establishing priorities within planning programs. In certain regions, priorities should be given to the drastic improvement of literacy rates ana education; in other regions, the priority emphasis may lie in village development; and yet in other regions, priorities might be established to improve the flow of information accessibility to larger numbers of people. 147 Each region of Turkey has inherent differences from other regions of the Republic. Each sub-system of the larger Turkish system must be treated as an independent entity, to a large entent - having its own problems, its awn resource de velopment potential, and its own capabilities to react favorably (or unfavorably) to any population program - with regard to policy and decision making. Recommendations for Further Research Modified Replication of Present Study It is apparent from this undertaking that many new areas of research potential could and should be developed. Although this study was limited by the data currently available and acces sible, this does not preclude the fact that as additional data become available, the sub-systems approach in identifying human fertility variations and correlates may be utilized once more. It is recommended, however that a replicated study of this type include the following modifications: (1) DATA: Although the ’’fertility ratio" measure ment has been used with success in several studies, and has been utilized in t'.:*s study, actual data concerning births, mortality, and other related demographic events, would add to a better under 148 standing and more rigorous analysis of fertility behavior in Turkey. Analyses could be made utilizing several computed fertil ity measurements, in order that the short-comings of some measure ments be compensated by the use of others. Additional data should also be sought and utilized, which would give greater insight into the socio-economic attributes of each place. (2) AREAL UNITS: Data of smaller unit areas should be employed, e.g., provincial districts (of which there are 571), in order that a more refined analysis could be performed. De lineation of sub-systems would be further strengthened through the use of data at a level which would obviously reveal internal variations which exist within some of the provinces themselves. This is especially Important for the larger provincial units. "Attitudinal" Sub-Systems and Fertility Behavior It appears that fertility behavior, which is greatly In fluenced and affected by a host of interrelated social, economic, and "distance" factors, can and should be analyzed In the constant ly changing dimensions of regional sub-systems. What is of equal importance, however, are the behavioral habits, tendencies, and attitudes of the people - the many individuals directly concerned with fertility decisions. It would prove extremely beneficial, if fertility behavior could be analyzed within a framework of 1 4 9 "attitudinal" regions, or "behavioral sub-systems", as well as within the context of regional types illustrated by this study. It is very possible and feasible, that information derived from sample surveys regarding behavior and attitudes could be utilized to delineate these sub-systems. In turn, these sub-systems could be used for population planning strategy, policy, and re source allocation. The Testing of Diffusion Theory From the analysis of fertility correlates made in this study, the correlate of "distance from Istanbul" was the most significant in the larger system. The implications are many. It probably denotes the diffusion processes which are taking place within the larger system, and the sub-systeins. It is quite clear that in the larger system, the distance variable is extremely significant in its relationship with fertility, liter acy, economic and institutional development, and other related phenomena. This In itself, opens up a whole new area of research possibilities, which have, as of this time, yet to be applied to Turkey. The whole notion of declining fertility as a diffusion process related to the diffusion of other phenomena, appears to be a theoretical framework which would be well suited for testing in the Turkish Republic. Concluding Statement The overall conclusion of this study, is that the pop ulation problem of Turkey, which in itself has spatial variation, must be resolved within a broader problem-solving effort. This must be done within the framework of a comprehensive program, with a developed economy, expanded social services, expanded and im proved educational facilities, and expanded networks for the flow of information. Government, as well as private resources, must be made available to cope with and solve a complex of social and econom-'': problems related to the problem of fertility. It is only within this larger framework that effective solutions to existing problems can be devised, What must be achieved in the long run, is the creation of a desire, on the part of the Turkish people, to live a full life within the scope of an optimized family size. The motivation for family planning and fertility control must be achieved through the communication of ideas, in formation, and current practices to a population which is prepared and willing to adjust to new patterns of life. APPENDIX The original data for this study were obtained from various documents, published and unpublished, Issued by agencies of the Turkish government. These documents are listed as follows: 1. Documents published by the State Institute of Statistics, Prime Ministry, Republic of Turkey, Ankara: DENIZ VE MOTORLU KARA NAKIL VASITALARI, 1960. (Ships and Motor Vehicles Statistics, 1960.) Publication No. 417, 1961. GENEL NUFUS SAYIMI, 1960. (Census of Population, 1960.) Publi cation No. 452, 1963. GENEL NUFtlS SAYIMI, 1965. (Census of Population, 1965.) Publi cation No. 568, 1969. ISTATISTIK YILLIGI, 1960-1962. (Statistical Yearbook. 1960-1962.) Publication No. 460, 1963. KOYLER ISTATISTIGI, 1960. (Statistics of Village Characteristics, 1960.) Publication No. 451, 1963. HUHTARLIK BINA SAYIMI, 1963. (Building Census, Places With 5,000 And Less Population, 1963.) Publication No. 497, 1966. ZIRAI BUNYE VE ISTIHSAL , 1958-1960. (Agricultural Structure and Production, 1958-1960.) Publication No, 421, 1962. 151 152 APPENDIX - Continued 2. Documents published and unpublished by other agencies of the Turkish government: ELEKTRIK ENERJISI ISTATISTIK BULTENI, 1961. (Bulletin of Electric Power Statistics, 1961.) Electric Power Survey Commission, Ankara, 1963. PTT ISTATIS TIKLERI, 1960. (Statistics of Post, Telephone and Tele graph, 1960.) Director General of PTT, Ankara, 1961. RATES OF NATURAL INCREASE, I960. Unpublished tabulations furnished by the Office of the Minister of Health and Social Assistance, Ankara, 1968, in personal communication. TURKIYE'DE EGITIH IHKANLARI - ANALIZLERI ILE BIRLIKTE EGITIM VERILERI. (Educational Opportunity in Turkey - A Source Book of Facts on Education With An Analysis.) Ministry of Education, Ankara, 1964. YILI SONU DEVLET VE VILAYET YOLLARI DURUMU, 1959. (Lengths of National and Provincial Roads by Surface Types, end of 1959.) Unpub lished tabulations furnished by the Office of the Director General, Highway Department, Planning Division, Ankara, 1968, in personal communication. BIBLIOGRAPHY Abu-Lughod, J. "Urban-Rural Differences as a Function of the Demographic Transition: Egyptian Data and an Analytical Model," American Journal of Sociology, Vol. 39, 1964, pp. 476-90. Adelman, I. and C. T. Morris. "A Quantitative Study of Social and Political Determinants of Fertility," Economic De velopment and Cultural Change, Vol. 24, 1966, pp. 129-57. Ahmad, Q. Indian Cities: Characteristics and Correlates. Re search Paper No. 102, Department of Geography, University of Chicago, 1965. Albaum, M. "A Spatial Analysis of the Demographic Transition Model," Paper presented to Southeast Division, Association of American Geographers, Meeting, 1968. Barclay, G. W. Techniques of Population Analysis. New York: John Wiley, 1958. Basavarajappa, K. G. "Effects of Declines in Mortality on the Birth Rate and Related Measures," Population Studies, Vol. 16, 1963, pp. 237-56. Beeley, B. W. "Spatial Aspects of Development in Turkey," Paper presented to Association of American Geographers Meeting, 1968. Berrien, F. K. General and Social Systems. New Brunswick: Rutgers University, 1968. Berry, B.J.L. "An Inductive Approach to the Regionalization of Economic Development," Essays on Geography and Economic Development, Research Paper No. 62, Department of Geography, University of Chicago, 1960. ______. "A Statistical Analysis," Atlas of Economic Development, Research Paper No. 6 8, Department of Geography, University of Chicago, 1961. 153 154 ______. "A Method for Deriving Multi-Factor Uniform Regions*" Frzeglad Geograflczy, Vol. 33, 1961, pp. 263-82. ______. "Approaches to Regional Analysis: A Synthesis," Annals of the Association of American Geographers, Vol. 54, 1964, pp. 2- 1 1. ______. Essays on Commodity Flows and the Spatial Structure of the Indian Economy, Research Paper No. Ill, Department of Geography, University of Chicago, 1966. ______. "Interdependency of Spatial Structure and Spatial Be havior: A General Field Theory Formulation," Papers of the Regional Science Association, Vol. 21, 1968, pp. 205-27. ______. "A Synthesis of Formal and Functional Regions Using a General Field Theory of Spatial Behavior," in Berry and D. Marble(ed.). Spatial Analysis: A Reader in Statistical Geography. Englewood Cliffs: Prentice Hall, 1968. ______and D. Marble. Spatial Analysis: A Reader in Statistical Geography. Englewood Cliffs: Prentice Hall, 1968. Beshers, J. M. Population Processes in Social Systems. New York: Free Press, 1967. Blalock, H. M. Social Statistics. New York: McGraw-Hill, 1960. Bogue, D. J. "An Outline of a Complete System of Economic Areas," American Journal of Sociology, Vol. 60, 1954, pp. 136-39. Borchert, J. R. "Geography and Systems Theory," i i S.B. Cohen (ed.). Problems a.id Trends in American Geography. New York: Basic Books, 1967. Buckley, W. F. Modern Systems Research for the Behavioral Scientist. Chicago: Aldine, 1968. Carlson, G. "The Decline of Fertility: Innovation or Adjustment Process," Population Studies, Vol. 20, 1966, pp. 177-93. Casettl, E. Classificatory and Regional Analysis by Discriminant Iterations. Technical Report No. 11 , Department of Geography, Northwestern University, 1964. Multiple Discriminant Functions. Technical Report No. 12 9 Department of Geography, Northwestern University, 1964. 155 ______and G.J. Demko. "A Diffusion Model of Fertility De cline: An Application to Selected Soviet Data - 1940-65," Discussion Paper, No. 5, Department of Geography, The Ohio State University, 1969. Chorley, R. J. and P. M. Haggett. "Trend Surface Mapping in Geo graphical Research," Transactions and Papers, Institute of British Geographers, Publication No. 37, 1965, pp. 47-67. and . Models in Geography. London: Methuen, 1968. Chung, R. "Space-Time Diffusion of the Transition Model: The Twentieth Century Patterns," Paper presented to Population Association of America Meeting, 1966. Coale, A. J. "Factors Associated With the Development of Low Fertility: An Historic Summary," Paper presented to United Nations World Population Conference, 1965. Davis, K. "The Amazing Decline in Mortality in Underdeveloped Areas," American Economic Review, Vol. 46, 1956, pp. 305-18. ______and J. Blake. "Social Structure and Fertility: An Analy tical Framework," Economic Development and Cultural Change, Vol. 4, 1956, pp. 211-35. Easterlin, R. A. "Towards A Socio-Economic Theory of Fertility: Survey of Recent Research on Economic Factors in American Fertility," Fertility and Family Planning. Ann Arbor: University of Michigan, 1967. Eren, N. Turkey, Today and Tomorrow. New York: Frederick A. Prager, 1963. Erin$, S. and N. Tun^dllek. "The Agricultural Regions of Turkey," Geographical Review, Vol. 42, 1952, pp. 179-203. Fifek, N. H., Y. Heperkan, and J. Rumford. The Evolution of the Turkish Demographic Survey. Ankara: Turkish Ministry of Health and Social Welfare, January, 1960. (Mimeographed.) ______and F. C. Shorter. "Fertility Control in Turkey," Demography, Vol. 5, 1968, pp. 578-89. Fisher, W. B. The Middle East. London: Methuen, 1963. 156 Frey, F. W. Regional Variations In Rural Turkey. Report No. 4, Rural Development Research Project. Cambridge: M.I.T. Center for International Studies, 1966. Friedlander, S. and M. Silver. "A Quantitative Study of the Deter minants of Fertility Behavior," Demography, Vol. A, 1967, pp. 10-70. Glass, D. V. (ed.) Introduction to Malthus. New York: John Wiley, 1953. Grabhill, W. H., C. V. Kiser, and P. K. Whelpton. The Fertility of American Women. New York: John Wiley, 1958. Haddan, J. K. and E. F. Borgatta. American Cities: Their Social Characteristics. Chicago: Rand McNally, 1965. Haggett, P. J. Locational Analysis in Human Geography. London: St. Martins, 1967. Hagood, M. J. "Statistical Methods for Delineation of Regions Applied to Data on Agriculture and Population," Social Forces, Vol. 21, 1943, pp. 287-97. ______, N. Danilevsky, and C. 0. Beura. "An Examination of the Use of Factor Analysis in the Problem of Subregional Delineation," Rural Sociology, Vol. 6, 1941, pp. 216-33. Harman, H. H. Modern Factor Analysis. Chicago: University of Chicago, 1967. Hartshorne, R. Perspective on the Nature of Geography. Chicago: Rand McNally, 1959. Heer, D. M. "Economic Development and Fertility," Demography, Vol. 3, 1966, pp. 423-44. Helling, B. and G. Helling. Rural Turkey: A New Socio-Statistical Appraisal. Istanbul: Istanbul University Institute of Economics and Sociology, Publication No. 102, 1958. Hershlag, Z. Y. Turkey: The Challenge of Growth. Leiden: E.J. Brill, 1968. Horst, P. Personality: Measurement of Dimensions. San Francisco: Jossey-Bass, 1968, 157 Huang-Chang, C, The Econoinlc Principles of Confucius and Hio School. New York: Hafner, 1911. Issawi, C. An Arab Philosophy of History. London: Cambridge University, 1950. Jensen, M. (ed.) Regionalism in America. Madison: University of Wisconsin, 1951. Kazamias, A. M. Education and Quest for Modernity in Turkey. Chicago: University of Chicago, 1966. Kele^, R. Y. Regional Disparities in Turkey. Ankara: Ankara University Faculty of Political Science, 1964. Kendall, M. G. A Course in Multivariate Analysis. London: Charles Griffin, 1957. ______. "Stochastic Processes and Population Growth,1' Journal of the Royal Statistical Society, Vol. 11, 1949, pp. 230-64. ______. "The Geographical Distribution of Crop Productivity in England," Journal of the Royal Statistical Society, Vol. 102, A, 1939, pp. 21-62. King, L. J. "Discriminatory Analysis of Urban Growth Patterns in Ontario and Quebec, 1951-1961," Annals of the Association of American Geographers, Vol. 57, 1957, pp. 566-78, ______. "Cross-Sectional Analysis of Canadian Urban Dimensions: 1951-1961," Canadian Geographer, Vol. 10, 1966, pp. 205-24. ______. Statistical Analysis in Geography. Englewood Cliffs: Prentice-Hall, 1969. Kolars, J. F. Tradition, Season, and Change in a Turkish Village. Research Paper No. 82, Department of Geography, University of Chicago, 1963. Lawley, D. N. and A. E. Maxwell. Factor Analysis As A Statistical Method. London: Buttersworths, 1963. Lee, E. S. "A Theory of Migration," Demography, Vol. 3, 1966, pp. 47-57. Lewis, B. The Emergence of Modern Turkey. London: Oxford University, 1961. 158 Lorimer, F., et. a l . Culture and Human Fertility. Paris: UNESCO, 1954< McCleary, G. F. The Malthusian Population Theory. London: Faber and Faber, 1953. Maithus, T. R. An Essay on the Principle of Population. London: Reeves and Turner, 1798. Mango, A. Turkey. New York: Walker, 1968. Marble, D. F. Some Computer Programs for Geographic Research. Special Publication No. 1, Department of Geography, North western University, 1967. Mauldin, W. P. "FertilJty Studies: Knowledge, Attitude, and Practice,” Studies in Family Planning, No. 7, 1965. Minshull, R. Regional Geography - Theory and Practice. Chicago: Aldlne, 1967. Moser, C. A. and W. Scott. British Towns: A Statistical Study of Their Social and Economic Differences. London: Oliver and 3oyd, 1961. National Academy of Sciences - National Research Council. The Science of Geography: Report of the Ad Hoc Committee on Geography. Washington, D. C.: NAS-NRC Earth Science Division, 1965. Odum, H. W. Southern Regions of the United States. Washington, D.C.: U.S. Government Printing Office, 1940. 0l9en, N. "The Geographical Distribution of Public Investments,” Planning In Turkey, edited by S. Ilkin and E. Inan^. Ankara: Middle East Technical University, 1967. Olsson, G. and S. Gale. "Spatial Theory and Human Behavior," Papers of the Regional Science Association, Vol. 21, 1968, pp. 229-42. Pearl, R. Studies in Human Biology. Baltimore: William and Wilkins, 1924. ______and L. J. Reed. "On the Rate of Growth of the Population of the United States Since 1790 and Its Mathematical Repre sentation," Proceedings, National Academy of Sciences, Vol. 6, 1920, pp. 275-88. 159 ______, L. J. Reed, and J, F. Kish. ’’The Logistic Curve and the Census of 1940," Science, Vol. 92, 1940, pp. 486-88. Quadir, N. A. "The Economic Ideas of Ibn Khaldun." Indian Journal of Economics, Vol. 22, 1942, pp. 898-907. Ridley, J. C., et. al. "The Effects of Changing Mortality on Natal ity: Some Estimates From A Simulation Model," Milbank Memorial Quarterly, Vol. 55, 1967, pp. 77-97, Rivkin, M. D. Area Development for National Growth: The Turkish Precedent. New York: Frederick A. Fraeger, 1965. Robinson, R, D. "Turkey's Agrarian Revolution and the Problem of Urbanization," Public Opinion Quarterlv, Vol. 22, 1958, pp. 307-405. The First Turkish Republic: A Case Study In National Development. Cambridge: Harvard University, 1963. Robinson, W. C. "The Development of Modern Population Theory," American Journal of Economics and Sociology, Vol. 23, 1964, pp. 375-92. Russett, B. M. International Regions and the International System; A Study in Political Ecology. Chicago: Rand McNally, 1967. Ryder, N. B. "The Influence of Declining Mortality on Swedish Re productivity," In Current Research in Human Fertility. New York: Milbank Memorial Fund, 1955, pp. 65-81. Schutz, T. P. "An Economic Model of Family Planning and Some Empir ical Evidence From Puerto Rico," Memorandum RM-3405-RC/AID, The Rand Corp., 1967. Semple, E. C. "The Regional Geography of Turkey: A Review of Bansef Work," Geographical Review, Vol. 11, 1921, pp. 338-50. Sewell, G. H. Squatter Settlements in Turkey: Analysis of A Social, Political, and Economic Problem. Unpublished Doctoral Dis sertation, Department of Economics and Social Science, M.I.T., 1964. Shorter, F. (ed.) Four Studies on Economic Development In Turkey. London: Frank Cass, 1967. 160 ______. "Information on Fertility, Mortality, and Population Growth In Turkey." Ankara: Hacettepe University Institute of Population Studies, 1968. (Mimeographed.) Splegelman, M. "Longevity and Mortality in the A m e r i c a n Population, In Population: The Vital Revolution. Edited by Preedman. Chicago: Aldine, 1964. State Planning Organization, Republic of Turkey. Five Year Development Plan: 1963-1967. Ankara: Central Bank of Turkey, 1964. Stirling, P. Turkish Village. New York: John W i l e y . 1965. Taeuber, I. B. "Population and Modernization in Turkey. Population Index, Vol. 24, 1958, pp. 101-122. ______. "Japan’s Demographic Transition Be-examl1"*^ , Population Studies, Vol. 14, 1960, pp. 28-39. Thompson, J. H., et. a l . "Toward A Geography of Economic Health: The Case of New York State," Annals of the Assuc i & ion American Geographers, Vol. 52, 1962, pp. 1-20, Thompson, W. S. and D. T. Lewis. Population Problem*.- ^ ew York: McGraw-Hill, 1965. Thornburg, M. W. Turkey: An Economic Appraisal. Newt York: Twentieth Century Fund, 1949. Turoertekln, E. Internal Migration in Turkey. I s t a n b u l : Geographical Institute of the University of Istanbul, 196® * Turkish Geographical Congress. Turk Cografya Kongre^.^Jj^ -S^bl • (Boojt of the Turkish Geographical Congress.) Ank/»*",a: 1941. United Nations, Department of Social Affairs, Popular l°n Division. The Determinants and Consequences of P ooula_t 1.5Zn .T.r York: 1953. United States National Resources Committee. Keg ip n_a_l _ — 111 National Planning and Development. Washingt ^ : * Government Printing Office, 1935. Vianelli, S. "A General Dynamic Demographic Scheme Its to Italy and the United States," Econotncl_r_i_rJ*-* * * pp. 269-83. 161 Vielrose, E. Elements of Natural Movement of Population. New York: Pergamon, 196b. Ward, J. H. Hierarchical Grouping to Optimize an Objective Function," journal of the American Statistical Association, Vol. 58, 1963, pp. 236-244. Weaver, J. C. Crop Combination Regions in the Middle West," Geo— graphical Review. Vol. 44, 1954, pp. 175-200. Weiker, W. F. ''Growth Patterns of Some Turkish Provincial Capitals," Paper presented to American Political Science Association Meeting, 1968. Vestoff, C. F. "The Fertility of the American Population," in Population: T h ^ y Whelpton, P- K. and C. v. Kiser (eds.) Social and Psychological Factors Affecting Fertility, Volumes I-V. New York: Milbank Memorial Fund, 1946-1958. Whittlesey, D. "The Regional Concept and the Regional Method," in American Geography: Inventory and Prospect. Edited by P. E. James and C. F. Jones. Syracuse: Syracuse University, 1954. Wilson, E. B. and R. R. Puffer. "Least Squares and Population Growth, Proceedings, American Academy of Arts and Sciences, Vol. 68, 1933, pp. 287-382. Zarate, A. 0. "Fertility in Urban Areas of Mexico: Implications for the Theory of the Demographic Transition," Demography, Vol. 4, 1967, pp. 363-73, Zobler, L. "Statistical Testing of Regional Boundaries," Annals of the Association of American Geographers, Vol. 47, 1957, pp. 83-95.