78-5911

REIMER, Toni Tripp, 1946- GENET I C DEMOGRAPHY OF AN URBAN GREEK IMMIGRANT COMMUNITY. The Ohio State University, Ph.D., 1977 Anthropology, cultural

University Microfilms International,Ann Arbor, Michigan 48106

(‘Sj Copyright by Toni T r i m Reimer 1977 GENETIC DEMOGRAPHY OF AN URBAN GREEK

IMMIGRANT COMMUNITY

DISSERTATION

Presented in Partial Fulfillment of the Requirements for

_ the Degree Doctor of Philosophy in the Graduate

School of the Ohio State University

By

Toni Tripp Reimer, B.S., M.S., M.A., R.N.

*****

The Ohio State University

1977

Reading Committee;

Dr. Frank E. Poirier, Chairman Approved By

Dr. Erika Bourguignon Dr. Paul Sciulli (fldWLVlk ^ Adviser Department of Anthropology ACKNOWLEDGMENTS

The cooperation and assistance of a number of indi­ viduals contributed to the preparation of this disserta­ tion. I truly appreciate Dr. Paul Sciulli, who provided direction and assistance in all phases of this research.

I am greatly indebted to Dr. Frank E. Poirier for en­ couraging my efforts throughout graduate school and for his thorough editing of this dissertation. I also thank

Dr. Erika Bourguignon, who initially led me to see the importance of integrating the biological and cultural aspects of anthropology.

I am most grateful to the people of the Greek community of Columbus for their cooperation and con­ tinuing friendship. In particular, I wish to express my sincere thanks to Father A. Sarris and Mrs. Kosmos

(Diana) Synadinos.

Finally, I wish to acknowledge Ms. Randy B.

Pollack, whose support and assistance made the prepara­ tion of this manuscript possible. VITA

December 1 4 , 1946 . . . Born - Ames, Iowa

1969...... B.S. in Nursing, University of Maryland, College Park, Maryland

1969-1972 ...... Nurse, U.S. Army Nurse Corps, General Leonard Y/ood Army Hospital

1972-1973 ...... Research Associate, Nursing School, The Ohio State University, Columbus, Ohio

1973 ...... M.S. in Nursing, The Ohio State University, Columbus, Ohio

1973-1976 ...... Teaching Associate, Department of Anthropology, The Ohio State University, Columbus, Ohio

1974 ...... M.A. in Anthropology, The Ohio State University, Columbus, Ohio

1976-1977 ...... Project Research Director, Department of Anthropology, The Ohio State University, Columbus, Ohio

1977-present ...... Assistant Professor, Nursing School, University of Iowa, Iowa City, Iowa

PUBLICATIONS

1975 "Psycho-cultural Exegesis of a Case of Spirit Possession from Ceylon." Transcultural Psychiatric Research Review. 12:147-149.

iii 1977 "Variations in Alcohol Metabolism Among Three Human Populations." In Summary of Research and Experimentation on Alcohol and Alcoholism, ed. Association of American Indian Social Workers, Sioux City, Iowa: Social Science Research Consultants.

1977 "Applied Medical Anthropology: The Appalachian Patient." Nursing Clinics of Worth America. March Symposium.

1977 Student Manual for In Search of Ourselves. Minneapolis: Burgess Publishing Company.

iv TABLE OF CONTENTS

page ACKNOWLEDGMENTS ...... ii

VITA...... iii

LIST OF TABLES...... ix

LIST OF FIGURES...... xii

Chapter

I. INTRODUCTION...... 1

G o a l s ...... 1 Sample...... 2 Purpose ...... 3 Outline ...... 7 Summary ...... 8

II. PERSPECTIVES ON THE RELATIONSHIP BETWEEN DEMOGRAPHY AND ANTHROPOLOGY...... 10

The nature of demography...... 10 Rationale for using demographic theory in anthropology...... 12 Demographic contributions to anthropo­ logical subdisciplines...... 16 Contributions demography can make to anthropology as a unified discipline. . . . 20 Anthropological contributions to demographic theory...... 22 Summary...... 29

III. THEORETICAL FRAMEWORK...... 30

The relationship between demography and microevolution...... 30 Population structure ...... 34 Vital rates...... 40

v Forces of micro evolution...... 53 The significance of cultural factors to population studies...... 63 Cultural factors influencing fertility . 64 Cultural factors influencing migration . 72 Cultural factors influencing mortality . 73 Summary...... 74

IV. THE GREEK COMMUNITY...... 75

History of Greek immigration into the United States ...... 75 Factors promoting emigration ...... 75 Pattern of Greek immigration...... 79 Historical and cultural characteristics of the Columbus Greek community...... 82 Geographical distribution...... 82 Education...... 82 Occupation...... 88 Family and kinship...... 89 Religion...... 98 World view ...... 101 Summary...... 103

V. METHODOLOGY...... 105

Conduct of the research...... 105 Data collection...... 106 Documents...... 106 Structured interviews...... 107 Participant observation...... Ill Data analysis...... 112 Sources of e r r o r ...... 112 Methods of analysis...... 115 Summary...... 117

VI. RESULTS...... 118

Population structure and movement ...... 118 Age and sex distribution...... 118 Migration analysis ...... 139 Marriage patterns ...... 149 Marital status ...... 149 Age at first marriage...... 153 Congruence in spouses' place of origin . 156 Greek ancestry endogamy...... 159 Fertility patterns...... 162 Age of menarche...... 162 Rates of fertility ...... 164 vi Reproductive wastage...... 171 Chi Id spacing...... 175 Patterns of "birth control...... 179 Mortality patterns...... 181 Mortality rates...... 181 Causes of death...... 189 life t a b l e ...... 193 Summary...... 198

VII. DISCUSSION...... 199

Effects of social and cultural factors on the population structure...... 199 Effect on migration patterns ...... 200 Effect on patterns of mortality...... 205 Effect on fertility patterns ...... 207 Effect on mate selection...... 212 Microevolutionary implications of the changing population structure ...... 215 Natural selection...... 215 Genetic drift...... 215 Gene flow...... 224 Inbreeding...... 230 S u mmary...... 235

VIII. SUMMARY AND CONCLUSIONS...... 236

Findings of the s t u d y ...... 236 Demographic characteristics of the Columbus Greek community population structure...... 236 Potential for microevolution within the Columbus Greek community ...... 240 Inference of cultural influences on forces of microevolution...... 242 Summary...... 243 Implications for future research...... 244

APPENDIX

A ...... 247

B ...... 249

C ...... 250

D ...... 253

vii E ...... 254

E ...... 255 G ...... 253

H ...... 271

I ...... 272

BIBLIOGRAPHY...... 274

viii LIST OF TABLES

1. Educational trends for males ...... 85

2. Educational trends for females ...... 86

3. Highest occupational status: males ...... 90

4. Highest occupational status: females ...... 92

5. Age distribution table: 19 1 0 ...... 119

6. Age distribution table: 1920 ...... 120

7. Age distribution table: 1930 ...... 121

8. Age distribution table: 1940 ...... 122

9. Age distribution table: 1950 ...... 123

10. Age distribution table: I960 ...... 124

11. Age distribution table: 1970 ...... 125

12. Age distribution table: 1976 ...... 126

13. Total migration rate into the Columbus Greek community...... 143

14. Comparison of in-migration to immigration. . . . 146

15. $> immigration from five major areas in Greece. . 148

16. Total migration from provinces and major islands in Greece for period 1390-1976 ...... 150

17. Kale marital status by decade of b i r t h ...... 151 18. Female marital status by decade of birth .... 152

ix 19. Age at first marriage for Columbus Greek females...... 154

20. Age at first marriage for Columbus Greek males and differences in means between males and females...... 155

21. Place of birth.: female and spouse by decade of female b i r t h ...... 157

22. Mating in the Columbus Greek community by decade of female's birth...... 160

23. Comparison of ethnic vs. geographical endogamy by decade of female's birth...... 161

24. Age at menarche of females in the Columbus Greek community...... 163

25. Crude birth rates...... 165

26. Fertility rates of women in the Columbus Greek community...... 167

27. Births by age of mother...... 169

28. Number of livebirths/female...... 170

29. Rate of miscarriage by year of mother's birth. . 172

30. Rate of stillbirth by year of mother's birth . . 173

31. Mean age at marriage and mean number of years before birth of first child by year of woman's birth...... 176

32. Methods of birth control...... 180

33. Methods of infant feeding by decade of mother's birth...... 182

34. Crude death rates...... 183

35. Male deaths by a g e ...... 185

36. Female deaths by a g e ...... 186

37. Mean age at death...... 188

x ia of individuals who fail to survive to reproductive age ...... 190

Causes of death (when known) for males by year of birth ...... 191

Causes of death (when known) for females by year of birth...... 192

Life table for Columbus Greek males...... 194

Life table for Columbus Greek females...... 195

Selection potential from differential motality (lm ) for Columbus Greek population ...... 217 Selection potential from differential fertility (lf) for Columbus Greek population ...... 219 Index of Total Selection for the Columbus Greek community...... 220

The Index of Total Selection for various human populations...... 222

A comparison of Crow's Index of Selection between the Pittsburgh Polish Hill and the Columbus Greek communities ...... 223

Coefficients of breeding isolation of various human populations...... 223

Inbreeding coefficients (f) of various human populations...... 234

xi LIST OF FIGURES

1. Greek immigration to the United States: 1880-1960 81

2. Present geographical distribution of the Columbus Greek community ...... 83

3- Population pyramid for the 1910 Columbus Greek community...... 128

4. Population pyramid for the 1920 Columbus Greek community...... 129

5. Population pyramid for the 1930 Columbus Greek community...... 130

6. Population pyramid for the 1940 Columbus Greek community...... 131

7. Population pyramid for the 1950 Columbus Greek community...... 132

8. Population pyramid for the I960 Columbus Greek community...... 133

9. Population pyramid for the 1970 Columbus Greek community...... 134

10. Population pyramid for the 1976 Columbus Greek community...... 135

11. Total migration into Columbus 1900-1979...... 140

12. Total migration into the Columbus Greek community by s e x ...... 142

13. Map of Greece...... 147

14.' Mean ratios of Index of Birthing Y e a r s ...... 178

xii CHAPTER I

INTRODUCTION

Goals

This study examines the population dynamics and

history of the urban Greek immigrant community of

Columbus, Ohio. Broadly subsumed under the topical rub­

ric "demographic (or population) anthropology," this

research was conducted for a number of reasons. The

major purpose was to examine and describe the potential

and operative processes of microevolution in a single

urban ethnic population since its formation in the late nineteenth century.

A more general goal of this dissertation is the

integration of data and theories from two anthropological

subdisciplines (cultural and physical) through a common unit: population structure. In this study, factors

determining the population structure (fertility, mor­

tality and migration) will be shown to be the processes involved in the microevolution of any population.

1 Further, I will examine the effects of cultural beliefs

and social organization on the rates of these factors.

It will then be possible to relate the influence of cul­

tural factors on the microevolution of a single popula­

tion, and the broader goal of integrating anthropological

subdisciplines will have been initiated.

Sample

The Greek community of Columbus was chosen as the

sample population for a number of reasons. First, the population was found to be a suitable unit of study for

cultural factors. Although confronted by continuing

acculturation pressures and a growing population, the

Greek community is attempting to preserve many facets of

the traditional way of life. Through numerous organiza­

tions, church groups, sports clubs and informal associa­

tions, members of this community maintain close communi­

cation and interaction among themselves and retain an

"ethnic identity." Further, Greek immigrant groups have

received scant attention in the anthropological litera­ ture dealing with American ethnic groups.

Second, the population was found to be a suitable unit of study for the process of microevolution. It appears that a majority of the population has a deep

committment to the Greek Orthodox Church. The combination of this commitment, a church doctrine which strongly promotes endogamous marriages, and a high degree of ethnic identity and cohesion within the population result in a high rate of ingroup marriage. Thus, while this population is politically and economically inte­ grated into the larger Columbus community, it is cul­ turally distinct and, in part, reproductively isolated.

Third, for reasons which will be discussed at length later, there is a need for microevolutionary studies of urban endogamous groups. As will be seen, previous such studies have been rare or incomplete.

Columbus was chosen as the site of this research for a number of personal reasons, one of which was my commit­ ment to the completion of a second research project.

Purpose

Population structure and vital rates can be useful to physical anthropologists concerned with determining patterns and potentials for microevolution. In addition, cultural factors may significantly influence the rates of vital processes. Numerous individual studies providing the data for these two theoretical formulations have been performed in anthropological populations. The most important of the studies are the following: 4

I. Determining microevolution through demography A. Investigations involving a single micro- evolutionary force 1. Relating demography and genetic drift: Glass 1956; KcEusick 1964; Giles 1966; Roberts 1963b; Cavalli-Sforza 1969. 2. Relating demography and gene flow: Lasker I960; Roberts 1967; Boyce, Kucheman and Harrison 1967; Laughlin 1963; Wienker 1972; lamb 1975. 3. Relating demography and natural selec­ tion: Crawford and Goldstein 1975. 4. Relating demography and population growth: Roberts 1968a.

II. Cultural factors influencing vital rates and population structure A. Factors promoting endogamy: Spuhler and Kluckhohn 1953; Dunn 1953, I960; Bonne 1962; Scott 1965; Gustafson 1969. B. Culture and childspacing: Potter 1963; Davidson 1971; Barnett, et.al. 1971; Hinshaw, et.al. 1972. C. Factors influencing the season of birth: Cowgill 1966; Malina and Himes 1977. D. Cultural factors influencing fertility: Roberts 1955; Otterbein 1965; Burch and Gendell 1970, 1971; Nag 1972; Saucier 1972; Fiasnick and Katz 1976; Wolf 1976; Friedl and Ellis 1976; Ryder 1976; Frisancho 1976; Liberty, et.al. 1976a, 1976b; Kuniiz and Slocumb 1976; KcAlpine and Simpson 1976. E. Culture and general population structure: Cross and McKusick 1970.

In summary, the significance of anthropological populations in the study of microevolution has been widely recognized and cultural factors influencing the population structure is also an important area of study.

However, the available literature is incomplete in at least two areas. First, most investigations utilizing demographic

parameters to evaluate microevolution have been concerned

with only one microevolutionary force (drift, gene flow

or natural selection). Few studies have considered

demography and multiple microevolutionary factors even

though this approach is necessary for a comprehensive

understanding of the microevolution of a population.

Further, the populations in which such a comprehensive

approach has been applied have been limited to Brazilian

Indian tribes, the Ramah Navajo, and mixed Mexican com­

munities. No comprehensive microevolutionary study has

been performed on an endogamous urban group.^ The im­

portance of studying the demography of groups living at

different cultural levels has recently been stressed in

the literature. Zubrow (1976), in particular, has called

for more descriptive studies over a wider range of popu­

lation types than previously known, and has stressed the

importance of learning about the demography of sub­

cultural groups in highly industrialized nations.

Second, investigations relating cultural factors to

population structure could logically be extended to in­

clude an analysis of the effect of this on the biological

1. Crawford and Goldstein (1975) studied urban Polish- American migrants; however, they concentrated on only one of the microevolutionary forces, natural selection. microevolution of the population. To my knowledge, there has not been a systematic presentation of the effects of cultural factors on the operative and potential micro- 2 evolutionary forces in a population. Because demo­ graphic processes are largely determined by social con­ ditions, investigating both the cultural and biological aspects seems to be essential to a more complete under­ standing of population change.

Thus, there is a need for an investigation of the demography of an urban ethnic population and there is a need for a study which examines the effect of cultural factors on the microevolution of a population. The explicit objectives of the present study are as follows:

1. To describe the population structure of an urban Greek immigrant community.

2. Two studies have been performed which mention the relationship between cultural factors and a specific microevolutionary force. Kluckhohn and Griffith (1950) found that the effect of clan exogamy on the Ramah Navajo tended "toward forcing genes from other groups to be spread widely in the population." Salzano, Neel and Maybury-Lewis (1967) noted that the practice of polygyny among the Xavante Indians resulted in the higher fertility and hence greater "genetic fitness" of village chiefs. However, these studies are not exceptions to my generalization concerning the lack of a systematic presentation of the effects of cultural factors on microevolution for two reasons: they were nonquantita- tive studies which dealt in only general terms with the cultural effects, and they focused on the' effect of only one microevolutionary force. 7

2. To measure the demographic factors of fertility, migration, mortality and marriage patterns in this population and determine changes and trends in these rates.

3. To infer from the demographic processes the potential for microevolutionary forces to have been operative in the population.

4. To elucidate the significance of cultural factors on the population structure of this population.

5. To integrate the subdisciplines of physical and cultural anthropology by exploring the significance of cultural factors on the operative and potential microevolutionary forces in a single community.

6. To develop and test a computer program which can be used by other anthropologists concerned with the microevolution of human populations.

Outline

The general plan of presentation of this research includes, in order:

1. A discussion of the relationship between demography and anthropology, including a rationale for using demo­ graphic theory and methods in anthropology and a review of the types of contributions a study of anthropological populations can make to demographic theory.

2. A review of the literature concerned with the two major topical areas: demography and microevolution, and the influence of cultural factors on population structure.

3. A discussion of the nature of this research, 3 including the three major objectives of this study.

4. A presentation of the general history of Greek immi­ gration to the United States, the history of the develop­ ment of the Columbus Greek community, and a brief ethno­ graphic description of the Columbus Greek communitjr.

5. P description of the methods and materials used in collecting and analyzing the data, and a discussion of the development of the computer program for demographic research.

6. A verbal and graphic presentation of the results of the research.

7. A discussion of the results as they relate to the potential for microevolution to have occurred in this community, and as they explicate the relationship between cultural influences and population structure. Further, the results will be compared to those of other popula­ tions and generational trends within this population will be examined.

3. A summation of the results indicating both the impli­ cations of this study and the possibilities for future research.

Summary

In this chapter, I have presented the major sub­ stantive aims of this study: to describe the demographic characteristics of an American urban immigrant community to determine the potential for microevolution within the population; and to examine, by inference, the ways in which cultural factors influence microevolution. The clear need for this study was demonstrated by showing the v.'ays in which data from this study would fill gaps in the available literature. Finally, the plan of pre­ sentation of this dissertation was described. CHAPTER II

PERSPECTIVES ON THE RELATIONSHIP

BETWEEN DEMOGRAPHY AND ANTHROPOLOGY

In this chapter I will discuss two major topical areas: first, the definition of demography and a dis­ cussion of the nature of the subject; second, the rationale for using demographic theory and method in anthropology. This involves a discussion of the appro­ priate aims and fields of study in anthropology, how demography can be applied to the subdisciplines of anthropology, and finally, what anthropology can contri­ bute to demographic theory.

The Nature of Demography

The term "demography11 was coined by Guillard in

1855 (Cox 1970). It comes from the Greek words "demos" - the people, and "graphia" - to write. It is, then, a study of "the people" or "the population." Demography has been defined by Bogue (1969:1) as

10 11

...the statistical and mathematical study of the size, composition and spatial distribution of human populations and of changes in these aspects through the five processes of fertility, mortality, marriage, migration and social mobility.

The population structure is the age and sex distribution; the composition includes the range of sociodemographic characteristics including marital status, income, race, education, occupation, or religion; distribution refers to the spread and location of a population over a given territory (Goldscheider 1971).

Demography may be conceived in a narrow sense as

"demographic analysis," which is seen by Hauser and

Duncan (1959) as being confined to the study of compo­ nents of population variation and change. This formula­ tion is also synonymous with what Petersen (1975) and

Eammeyer (1975) call "formal demography," defined as the gathering, collating, statistical analysis and technical presentation of population data. Thus, demography in a narrow sense is concerned with three major tasks: ascertaining the numbers, characteristics and distribu­ tion of people in a given area; determining changes in these over time; and explaining the major factors accounting for these changes (the factors being derived from one of the following three variables: fertility, mortality and migration). Here, then, one set of popu­ lation characteristics are used as independent variables 12 to explain variations in another set of population characteristics.

Demography in a broader sense encompasses both

"demographic analysis" as described above, and also

"population studies or analysis." Population analysis may be seen as the systematic study of population trends and phenomena in relation to their social setting

(Petersen 1975). This perspective integrates demographic analysis with material and theories from other disci­ plines. Thus, depending on the problem to be researched and the background of the investigator, concepts, theories, data and methods of analysis from disciplines such as anthropology, biology, economics, history, socio­ logy, genetics, psychology, etc. can be used in "popula­ tion studies."

Rationale for Using

Demographic Theory in Anthropology

As noted by Spuhler (1959)» demography has some­ times been defined as a branch of anthropology (as in the

1955 Oxford Universal Dictionary). However, in current

American practice, demography is not a branch of anthro­ pology. In fact, until recently, the two sciences have had little connection. Except for a few scattered pieces of research, anthropologists traditionally paid only very casual attention to population studies. However, in the

past decade there has been a surge of interest in the use

of demography in anthropology. Indications of the in­

creased interest in demography among anthropologists are

twofold: first, an increase in publications concerned

with demographic anthropology including books (Salzano

and Freire-Kaia 1970; Polgar 1971, 1975; Harrison and

Boyce 1972; Spooner 1972; Crawford and Workman 1973;

Weiss 1973; Freire-Maia 1974; Swedlund 1975; Underwood

1975; Kaplan 1976; Swedlund and Armelagos 1976; and

Zubrow 1976), review articles (Baker and Saunders 1973;

'Weiss 1976) and a multitude of individual reports in

journals such as Current Anthronology, American Journal

of Physical Anthropology, Human Biology and Social

Biology. The second indication of an increased interest

among anthropologists in the field of population studies has been the appointment of anthropologists to national

and international councils concerned with population

policies.

There are two major reasons why demographic vari­

ables should be studied in anthropology: first, to con­

tribute to demographic or, in its broader scope, popula­

tion theory. Before discussing the first of these, how­

ever, I will discuss the nature of the aims, goals and

appropriate lines of investigation in anthropology. 14

After this discussion, it will be easier to explicate possible contributions of a demographic perspective.

Anthropology as a unified discipline is the study of the physical and cultural similarities and differences of human populations and how these conditions evolved from the interaction between biology and culture (beha­ vior). Anthropologists hold that a biocultural orienta­ tion is necessary for an adequate understanding of human nature and human evolution. In addition, humans must be studied from a perspective that is comparative across time and space, thus historical and cross-cultural.

As Eluckhohn and Griffith (1950) have noted, the social anthropologist must familiarize himself with genetics and other aspects of human biology because if his reading and research are limited to sociology, eco­ nomics, politics and the other social sciences, he ceases to be, in the strict sense, an anthropologist. Further, we should attempt to find concepts and methods that can integrate the biological with the cultural aspects of human behavior not only because this is the operational definition of anthropology, but also because human deve­ lopment, genetic and physiological adaptations are set within a social and cultural framework.

To understand both the behavior of humans in a cul­ tural setting and biological variation, the unit of study 15 must be the population, not the individual. Human popu­

lations are structured; they are patterned with a defi­

nite form, both in the social organization and in the

physical population structure.

In discussing the social structure of a population,

I shall follow Graburn (1971) and look at it as a "map”

that places a society's individuals into categories,

thereby giving them expectations about how they will be

treated and a set of rules to guide them in their beha­ vior toward other people. Societies place people into

categories or positions according to such variables as kinship, residence, economics, religion, politics, age,

gender and occupation. Social structure includes the

study of all these and the types of ideal and real beha­ vior that occur between these organized groups or between persons. Social structure does not exist at an indivi­ dual level; thus, the proper unit of study of the social structure is the interacting population.

As Johnston (1966) and others have noted, the pro­ per unit of study for human evolution and variability is also the population. This is because human evolution and variation result from changes in gene frequencies within a population.

The overall aim of anthropological research is to

■understand and compare social and physical similarities and differences in human populations, and how these

characteristics evolve. Demography can he of use to

anthropology as it contributes to the pursuance of these

aims. The specific manner by which this can be accomr plished will be revealed as we examine the two ways in which demography can contribute to anthropology: by con­ tributing separately to each of the subdisciplines, and by providing concepts and methods which can be used to

integrate the subdisciplines of anthropology.

Demographic Contributions

to Anthropological Subdisciplines

Physical anthropologists are beginning to see demo­ graphic methods as useful tools. Most physical anthro­ pologists today define both macro- and microevolution in terms of gene frequency changes within populations.

The determinant modes of gene frequency change are muta­ tion, natural selection, genetic drift and gene flow. As

Spuhler (1959) has noted, physical anthropologists have developed an interest in demography because the forces of demographic variability (fertility, mortality, mating, migration and population size and composition) are how microevolution operates. To study microevolution empiri­ cally, these factors must be measured. This relationship will be further explicated in the chapter devoted to the 17

theoretical framework encompassing demography and micro­

evolution.

In archeology, too, demographic information has

become increasingly important. As Weiss (1973) has

noted, even the most trite archeological data are struc­

tured at least in part by demographic factors. The age

and sex structure of a population will be reflected, if

only indirectly, in the number of points, the volume of

pots, or the size of the settlement area. More abstract­

ly, more complex archeological parameters such as length

of site occupation or the prevalence of special activity

sites are influenced by the demographic characteristics

of the population.

Demographic variables have also been viewed as a

factor in the causation of major evolutionary transfor­ mations. Population growth has been cited as an impor­

tant factor related to the origins of Near Eastern agri­

culture. According to the Flannery-Binford Model

(Wright 1371), cereal domestication in the Near East

arose as a consequence of population growth in "optimal"

ecological zones, which produced migrations to adjacent

"marginal" aones. In these marginal zones, population pressure called for new kinds of adaptations or innova­ tions in subsistence strategies. This model is partially an outgrowth of the work of Boserup (1965) and her 18 hypothesis that population pressure is a factor in inten­

sifying means of subsistence.

The development of urbanization and state formation have also been linked to demographic variables. Cameiro

(i960) has argued for a relationship between increasing population size and the level of organizational com­ plexity. Clark (1951) has suggested that the permanence of settlement sites and conflicts between settled groups resulted from population increases and the resultant dwindling of land resources.

linguists may also depend on demographic variables.

For example, the "dialectical tribe" is one of the cen­ tral concepts in Birdsell's explanation of Australian demography.

Cultural anthropologists have employed demographic factors, relating them to the social organization of the anthropological population. Of all the subdisciplines, cultural anthropology has probably had the longest his­ tory of interest in demographic factors. For example, in

The Division of Labor in Society, Durkheim (1393) related the size of a population to its degree of complexity, and Pitt-Rivers (1922) discussed the relationship between sex ratio and form of marriage. Carr-Saunders (1922), however, was probably the first to compile a comprehen­ sive cross-cultural review of the relationship between 19 social organization and a demographic parameter (ferti­ lity) .

In cultural anthropology, demographic studies have usually focused on one of the following topics:

1. A description (sometimes including a "functional analysis") of a specific social custom that influences a demographic parameter. For example, the practices of infanticide, warfare and human sacrifice have been related to mortality; postpartum abstinence, methods of abortion and ritualized celibacy have been related to fertility, etc.

2. The relationship betwenn the demographic parameters

(fertility, mortality and migration) and social organi­ zation have been studied. For example, Lorimer (1954) concluded that societies emphasizing unilineal descent and having strong corporate kinship groups tend to generate strong cultural motives for high fertiltiy rates.

3. Studies have related specific features of population structure, especially population size, to specific types of cultural configurations, particularly social com­ plexity and stratification, marriage and kinship pattern, and type of political organization.

A more complete development of the relationships between cultural factors and population structure will be seen in the next chapter. However, this cursorj’- outline 20 shows the various ways demography can contribute to the subdisciplines of anthropology.

Contributions Demography Can Make

to Anthropology as a Unified Discipline

I have discussed the contribution demographic methods and perspective can make to each subdiscipline of anthropology. However, this is only a part of the poten­ tial contribution of demographic anthropology. A broader, possibly more important contribution demography can make is to serve as a vehicle for the integration of the sub­ disciplines of anthropology.

As previously noted, anthropology is a discipline striving for an understanding through time and space of the evolution of the human condition. It is a holistic science in that it looks at humans from both a biological and a cultural perspective. As we usually find it, how­ ever, anthropology is not practiced as a holistic disci­ pline. Par too often, research in a subarea is conducted without regard or acknowledgement of the significance of the research to the other subdisciplines, or to how the research fits into the entire framework of the discipline.

One regnon for this fragmentation, besides the technical specialization in the subdisciplines, has been that there were few unifying concepts except evolution 21 and culture. Further, these concepts are not easily measured, and in fact are not used by the subdisciplines in the same way. Even within the subdiscipline of cul­ tural anthropology, there are many heated arguments on the validity of the concept of cultural evolution, and it has been only recently, as we have begun to discuss the mutually reinforcing feedback system of biocultural evo­ lution, that the subdisciplines of anthropology seem to stand on common ground.

Demography, however, offers a unifying theme: the concept of population and the variables therein. We can examine both biological and social phenomena using a com­ mon unit: the statistical population. Furthermore, the concept of population is already prevalent and well accepted in both cultural and physical anthropology.

Population structure is discretely measurable, unlike other unifying themes such as evolution and culture.

Finally, if we are to understand the process of popula­ tion adaptation to the environment, we need to assess the interaction between culture and biology. While this can be accomplished through a multidisciplinary study, I pro­ pose that it can also be accomplished by an individual anthropologist in a single research study.

Demographic anthropology can have its own clear and distinct place in anthropology. Its goals are to 22 identify, illustrate and analyze systematically and rigorously the junctures of biological and cultural pro­ cesses through demographic processes. The demographic approach to anthropology argues that anthropologists cannot fully understand the nature of human society and human biological variation without a clear comprehension of the integral role played by population processes in the dynamics of social and biological life.

Physical anthropology is the study of the funda­ mental biological processes of human evolution and diver­ sity. This process orientation necessitates building a unified theory relating evolutionary biology to socio­ cultural behavior, with the understanding that biologi­ cally relevant aspects of human populations are reflected in demographic variables.

Anthropological Contributions to Demographic Theory

A second major reason for studying demographic anthropology is for the contribution it can make to know­ ledge and theory in the discipline of demography. That demography is in need of an expanded framework is not greatly in doubt. Although demographers1 complex mathe­ matical models may not always be appropriately applied to small populations, the inclusion of anthropological information in demographic theory is nevertheless 23 necessary if demographers are to improve their theories and generalizations.

Demography has used a limited scope and the fol­ lowing problems have resulted from this perspective, first, demographers tend to work v/ith national census figures, and thus have traditionally been limited to

Western societies. Most demographic models apply only to the dominant mode in a national population, and do not apply to subcultures such as immigrant groups, religious isolates, ghettos or other isolated or semi-isolated groups. Secondly, demographers tend to stop their analy­ sis short of what other social scientists would consider complete. Demographers tend to look first to a demo­ graphic factor when making causal explanations, for example, if the number of births decreases and the number of marriages is also found to have decreased, the latter phenomenon may be taken as the cause of the former. And if the "causal" demographic factor is not found, they turn most readily to an economic explanation. Demo­ graphers are accustomed to measurement and are usually ' content only if measurable relationships can be found

(Noonan 1972). However, this suppresses a more complete understanding of the process involved and promotes the idea that quantitative measurement (which is desirable if attainable) is the only tool for understanding human 24

"behavior.

As Freedman (1962) notes, even when demographers

look toward more social explanations for demographic fac­

tors, they look from a sociological perspective because

that is the primary home base of demographers in academia.

The resulting categories used to explicate the relation­

ships between social and demographic factors may be

inappropriate for anthropologists. For example, if a

demographer attempts to relate fertility to social vari­

ables, he will likely categorize people on the basis of

their education, occupation, urbanization or geographic

area. This sociological orientation varies from the

anthropological one, in which the unit of analysis is the

endogamous population.

As stated, demographers tend to use data from only

Western societies when they are theorizing. This is

partly because the demographic data is most accurate and

complete for Western societies. However, national cen­

suses and vital registration systems, although highly valuable, leave very serious gaps in knowledge about

determinants and consequences of population phenomena.

As Hag (1975:29) points out,

...the familial and socio-cultural aspects of these phenomena, at all levels of industrial development, may best be understood through coordinated studies of small communities using participant observation, informal interviews, historical research, tests of cognitive and affectual dispositions, etc. Anthropologists bring a slightly different perspec­

tive to population studies. This approach is partially

the result of data from circumscribed communities,

usually known intimately by the researcher. In this

framework, the investigator is often able to recognize

influences of fertility and fecundity of which the demo­

grapher may be less cognizant. This would be due to the

fact that the data commonly used by demographers

(national samples or census data) are so divorced from

the social situation within which these influences have

their reality (Kaplan 1976).

Further, a realistic view of population problems

and dynamics requires a view of 'humankind in its entirety.

A population theory purported to have universal applica­

tion, yet based only on data from Western societies, is

obviously ethnocentric and, of course,.incomplete. For

these reasons, demographic theory has been plagued by

overgeneralizations which the introduction of anthropolo­

gical data can help correct.

An obvious case of oversimplification is the "demo­

graphic transition theory," a major cornerstone in demo­

graphy. This theory contends that as a nation indus­

trializes, its mortality rate declines first, while the birth rate (through the application of the technology of birth and death control) is attenuated later. The lag in 26 time between the decline in rates accounts for the extra­ ordinarily rapid population growth in developing nations.

The stages of the demographic transition have been sum­ marized by Bogue (1969) as follows:

1. The pretransitional stage: little regulation or con­ trol of either death or birth rates, with the consequence of high vital rates but almost zero growth.

2. The transitional stage: death and birth rates are in the process of being reduced; death rates are reduced first, and the population increases.

3. The posttransitional stage: both birth and death rates are low; contraceptive methods keep vital rates in balance with each other; population growth is low or approaching zero.

The idea of demographic transition is still common among demographers. Petersen (1975), for example, characterizes five types of societies ranging on a con­ tinuum from the preindustrial type with high fertility, high mortality, and highly fluctuating growth rates, to the modern Western urban economy with controlled ferti­ lity, low mortality and usually low growth rates.

Anthropologists have attacked many aspects of this traditional demographic transition theory. First, demo­ graphers tend to view preindustrialized societies as

"poised on the brink of extinction." But anthropological studies of hunters and gatherers, and even of early agri­

culturalists, have shown that fertility and mortality

patterns may be quite ’’moderate" in preindustrial

societies and are not necessarily "high." And, as noted

by Polgar (1971), there are several lines of evidence

indicating that the voluntary regulation of family size

may well have been one of the earliest features of human

culture. Birdsell (1968) has stated that systematic in­

fanticide has been a necessary procedure for spacing

human children, presumably since the beginning of human

entry into the niche of bipedalism and lasting until the

development of advanced agriculture. Further, he esti­

mates that between 15-50^ of the total number of births may have ended in infanticide. Devereux's (1955) study

of 350 preindustrial societies further supports the

anthropological position. He found that in these

societies, abortion is a universal phenomenon and he con­

cluded that it probably has been present from at least very early in human history.

Therefore, the common postulate of demographers

that cultural forces in preindustrial societies are all

directed to maximize births (to compensate for "very high" mortality), is open to serious question. In fact, even the idea of "very high" mortality is questionable based

on studies of hunting/gathering populations such as the 28 IKung Bushmen and on Polgar's (1964) evidence that among

hunter-gatherers and precontact agriculturalists, the

mortality rate was undoubtedly lower than in preindus­

trialised urban societies because most contagious disease

pathogens cannot survive in low density populations.

Numerous ethnographic studies have demonstrated

that there is a great variation in both the fertility

and the mortality levels of preindustrial societies. The

fertility regulating practices of nonindustrialized

societies are often ignored by demographers in their

analysis of population dynamics.

Thus, modern ethnographic, paleopathological and

archeological data tend to show that transition theory

does not hold for all populations. In this respect, we must remember that transition theory was originally for­ mulated to explain data from Western Europe. Anthropo­ logists have been useful in demonstrating that these demographic characteristics are neither geographically nor temporally uniform.

Last, demographers have usually held that the human

growth curve had a very slow, gradual increase until about the mid-eighteenth century. Both physical and cul­ tural anthropologists have provided evidence that there were at least three other drastic increases in population size, one occurring with the inception of big-game 29 hunting, the second at the time of the toolmaking revo­ lution, and the other at the time of the agricultural revolution. These other changes in the growth curve are frequently ignored by demographers, as they were unknown before anthropological data was provided.

Thus, anthropologists can be of great assistance to demographers in describing the prehistory and cross- cultural variability of human demography, and, therefore, greatly improving the data base from which demographers derive their theories.

Summary

In this chapter I explored the relationship between demography and anthropology. The aims of this chapter were to explicate the nature of demography, to present a rationale for using demographic theory and methods in anthropology, and to review the types of contributions a study of anthropological populations can make to demo-: graphic theory. CHAPTER III

THEORETICAL FRAMEWORK

The general aims of this study are: (1) to infer from the demographic processes the extent of potential and operative microevolutionary forces in the Columbus

Greek population; (2) to examine the influence of cul­ tural factors on demographic variables; (3) to infer the interrelationship between cultural factors and microevo­ lution in a single population. In this chapter, I will present a review of the literature pertinent to the first two general aims of this study.

The Relationship Between

Demography and Microevolution

One of the main objectives of physical anthropology is to document and describe patterns of evolution, both on macro and micro levels. There are two major approaches to the study of human microevolution: one is to measure allelic frequency differences between popula­ tions; the other is to observe the structure of a

30 population through time in an attempt to determine which evolutionary mechanisms are operating. When genetics was formally introduced into anthropological methodology, it was initially used by typologists, such as Boyd (1950), who were concerned with the genetic classification of populations. This method, however, yielded little infor­ mation concerning the reasons populations varied; it was not a process-oriented approach. Gradually, with the development of relatively sophisticated models by geneti­ cists, anthropologists concerned with microevolution shifted their focus from counting and comparing gene fre­ quency differences between populations to attempting to understand the processes and mechanisms responsible for the differences in the observed gene frequencies.

The introduction of the population genetics methods to anthropological studies on human microevolution has been approached from two different perspectives: the theoretical and the observational. The former is based on mathematical models developed by Fisher, Haldane,

Wright, Crow and others. As models, they are simplifica­ tions of reality which apply perfectly only to "ideal" populations. However, as noted by Freire-Maia (1974), although the genetic theories of the process of evolution were developed for populations with ideal theoretical properties, they may also be used to interpret processes 32 in real populations (e.g. tlie Castle-Hardy-Y/einberg for­ mula assumes conditions impossible in real populations, but it has still proven to be a valuable tool in the interpretation of some microevolutionary problems).

Because the idealized conditions assumed for the theoretical models are never found in human populations, anthropologists must incorporate the second approach (the observational) in order to obtain factual data on real populations. With this data we can compare actual and expected population measures. Ultimately, this leads to the discarding of some of the simplifying assumptions in order to build more realistic models. As noted by .

Benoist (1973) there is a dialectical movement between theory and observation. We obtain simplified models from theoretical mathematics; we observe reality to find cases that approximate the models; then, observed data induce us to construct more elaborate theoretical models which must again be modified by reality. It is from the synthesis of the "ideal" population genetic theory and data from observed populations that allows us to ■under­ stand actual processes at work in the genetic structure of human populations (Lewontin 1972).

As was discussed by V/right (1955) , microevolution- ary changes result from the interaction of mutation, gene flow, natural selection and genetic drift. In human 33 populations, the latter three concepts are not them­ selves easily measurable and we usually only infer their presence and strength by observing other more easily measured variables. It is to the field of demography that we turn for these discernable variables.

As previously noted, demography has been defined by

Bogue (1969:1) as

...the statistical and mathematical study of the size, composition, and spatial distribution of human populations and of changes in these as­ pects through the five processes of fertility, mortality, marriage, migration and social mobility.

These demographic variables are the basic tools for the inference of the mechanisms of evolution. Natural selec­ tion is inferred from measures of differential fertility and mortality; gene flow from migration and marriage data; and genetic drift from migration, population size and mating patterns. In fact, evolutionary forces oper­ ate through the demographic mechanisms. Therefore, popu­ lation surveys are the first step to obtain data which can then be manipulated by the theoretical tools of popu­ lation genetics.

The dynamics of demographic mechanisms reveal the processes of ongoing human evolution. 34

Population Structure

The structure of a population is described by its

age and sex composition and is the result of the inter­

action of a series of variables: population size, migra­

tion, births, deaths, inbreeding, sex ratios, and mating

patterns. It is possible to compare populations and find

them very similar in structure; however, because these

similar structures could be maintained by very different

vital rates, we can understand very little about the

dynamics maintaining the population structure unless we

determine the magnitude of the demographic mechanisms.

Further, we need to determine the vital rates of a speci­

fic population before we can make inferences about mic: ?-

evolutionary processes operating within that population.

Because an understanding of these three major groups of

concepts (population structure, demographic vital rates, and microevolutionary forces) is critical to this study, we will discuss these concepts in more detail and trace the history of their use in genetic demography.

The population's composition is related to its bio­ logical factors (age and sex composition) and growth characteristics. Of these two variables, age structure is probably the single most important demographic index of population structure (Swedlund and Armelagos 1976). 35

Age distribution: Petersen (1975) has noted that the most important single figure summarizing a population1s age structure is its median age, which divides the popu­ lation into older and younger halves. Grouping the popu­ lation into three categories can also be analytically significant. These categories are defined as follows:

1. dependent children: the proportion of the population under 15 years of age.

2. dependent aged: the proportion of the popula- aged 65 a n d older.

3. the active population: the proportion of the population between the ages 14 and 65; this is an estimation of the labor potential. (Petersen 1975)

There is, at first glance, a surprising relation­ ship between the factors influencing the age distribution in a closed population (fertility and mortality). If we closely examine the interrelationships, we find that mor­ tality affects the age distribution in most populations much less than does fertility, and in the opposite direc­ tion from what we might originally think. The prolonga­ tion of life by the reduction of death rates has the rather surprising effect of making the population some­ what younger. This effect will now be explained: while it is true that as death rates fall, the average age at which people die is increased, the average age of a popu­ lation is the average of living persons, not their average age age at death. Further, while we easily realize that as death rates fall, the number of older people in the population increases, it is less apparent that the reduced mortality increases the number of young people as well. In fact, reduced death rates usually make a population younger because the typical improve­ ments in health are aimed at producing the greatest in­ creases in survivorship among the young rather than the old (Coale 1964).

Petersen (1975) has devised a measure to examine the age category most affected by a change in mortality.

This is termed the Index of Aging and is equal to

persons 65 years and over x -^qq children 14 years and younger

There are other observations which explicate the relationship between demographic variables and the age structure of a population which should be mentioned to facilitate a discussion of the age structure of the

Columbus Greek population.

1. Current and recent high fertility produce a younger population than would low fertility, and the converse is also true.

2. Transitory waves of unusually high or low fertility create peaks and valleys that move through the age dis­ tribution as the cohorts move through life.

3. A long period of high fertility, or a period of rising fertility, creates a section of the age 37 distribution that tapers rapidly with age. Conversely, a long period of low fertility or a period of falling fer­ tility creates a relatively flat (or even rising) section of the age distribution.

4. When a cohort of unusual size reaches childbearing age, it sets up an attenuated and flattened out "echo" in the number of births.

5. The rising fraction of the aged in Western countries lias not resulted from lowered death rates, but almost wholly from a long history of declining fertility (Coale

1957).

Sen distribution: The sex ratio is an indication of the relative numbers of males and females in a population.

Three categories of sex ratios can be defined by the age of the group when the ratio is determined. Convention­ ally, the primary sex ratio exists at the time of ferti­ lization; the secondary sex ratio is that of live births

(sometimes including stillbirths); the tertiary sex ratio is that of a cohort at any specific given age after birth. All sex ratios are calculated by the same method:

number of males ^ -j^q number of females

(Teitelbaum 1972).

Available evidence indicates that many more males than females are conceived. However, the actual primary 38 sex ratio in a population is impossible to determine accurately with present methods for obvious reasons.

The secondary sex ratio, on the other hand, lends itself quite well to empirical study. The sex of a live- born child is rareljr misclassified. Several factors have been associated with variations in the sex ratio in various populations; these include maternal ABO blood groups (Plant and Buncher 1976), birth order, family size, sex of first infant, maternal age, paternal age, relative ages of parents, and stress conditions. As Teitelbaum

(1972) has noted, however, the results of the multitude of studies dealing with maternal and paternal age factors have unfortunately led to little agreement as to which factors are significant. Partially, the problem is that in most studies there is insufficient data to allow the investigator to control for two or more of the suggested factors. Possible relevance of these studies will be discussed after the results from the Greek community have been presented.

Although the basis for variance in the secondary sex ratio is still in question, the fact of the variance in different human populations is not in dispute, and these ratios have been calculated for several populations.

Por example, Lerner and Libby (1963) report the following secondary sex ratios: 39

Cubans: 101 U.S. Blacks: 103 U.S. Whites: 106 Native Greeks: 113 (See Appendix A)

Factors contributing to tertiary sex ratios are

generally much more straightforward in their determina­

tion. In general, tertiary sex ratios will result from a

combination of four factors: the differences in propor­

tion of sexes at birth, the differences in the number of

immigrants of each sex, the differences in the number of

deaths of the two sexes at various ages, and the number of

emigrants of each sex. Obviously, in immigrant popula­

tions such as the Columbus Greek community, the tertiary

sex ratio may be quite interesting to investigate.

Population pyramid: For easy visualization of the

tern of population composition, a population pyramid is

constructed whereby males and females are divided. These two categories are then further subdivided into age

groups, usually at 5 or 10 year cohorts, e.g.: 30+ 70-30 60-70 ja1 50-60 40-50 30-40 1 20-30 10-20 0-10 J males females

A population pyramid can be informative, especially when the cultural patterns of the group are known because it

represents the outcome of vital rates operating in pre­

vious years. For example, a broad base often designates

a growing population, while a narrow' base may represent

the result of low fertility or high infant and child

mortality (Underwood 1975)*

Vital Rates

A population's age-sex composition is determined by

two factors: the population's sex ratio at birth

(secondary ratio) and the historical pattern of the vital

rates of birth, death and migration.

Births: A livebirth is the

...complete expulsion or extraction from its mother of a product of conception, irrespective of the duration of the pregnancy, which, after such separ­ ation, breathes or shows any other evidence of life (Cox 1970:12)

Fetal death is death prior to the complete expulsion or

extraction from its mother of a product of conception,

irrespective of the duration of the pregnancy; a still­ birth is a fetal death occurring late in the gestation period (after 23 completed weeks of gestation) (Cox 1970)

The most basic measure of the vital rate of birth

is the crude birth rate, the ratio of livebirths per cal­

endar year to the average midyear population of the same year expressed in thousands (Sutter 1963). This is only 41 a very rough measure, however, because the total popula­ tion is not the population "at risk" for births, because it contains males and females outside the childbearing years.

More specific and informative measures of rates of birth have been developed and are termed rates of ferti­ lity.^* A graph depicting the fertility rate curve gener­ ally shows an inverted U shape. It starts low but rises sharply in the teen years, it is highest for women in their twenties, then it declines for women past thirty until it reaches zero at menopause. Fertility rates are dependent on several factors which may be grouped as fol-. lov/s:

1. age of sexual maturation

2. duration of the reproductive period

3. average age at marriage (or mating)

4. length of the interval between marriage and the birth of the first and successive offspring.

Three of these factors (1, 2, and 4) have both biological and cultural components of determination. Factor 3 is essentially a cultural factor. The biological influences on factors 1, 2 and 4 will be presented here. Cultural

1. We will use the term "fertility" or "natality" to refer to realized reproduction, and another term, "fecundity," to refer to potential reproductive capacity. This clarification is necessary because some disciplines use the terms in the completely opposite sense (Harrison and Boyce 1972b, Polgar 1971). ■ 42 influences on all of the factors will be discussed in the second major section of this chapter, which deals with cultural influences on the population structure.

Numerous factors have been associated with variable age of menarche. The trend toward earlier ages of men- arche have variously been attributed either to better nutrition or heterosis. The majority of evidence tends to indicate that nutritional factors are of prime signi­ ficance in the age of the first menstrual period (Tanner

1973). The onset and maintenance of regular menstrual function seems to be dependent on the maintenance of a minimum weight for height; this apparently represents a critical fat storage (Frisch 1975). Other environmental factors such as altitude (Tanner 1973 2nd Abelson 1976), and light (Wurtman 1964) have also been shown to in­ fluence age at menarche.

The biological duration of the female reproductive cycle extends from menarche to menopause. Unless arti­ ficially induced, as with oopherectomies or total hyster­ ectomies, the onset of menopause is not as discrete as the onset of menstruation. Women may pass through an extended transitional period of greatly decreased fecund­ ity, usually beginning between ages 40-45. The same fac­ tors which delay the onset of menarche have also been found to precipitate the onset of menopause. Thus, for 43 example, a poorly nourished population would probably have a delaj^ed period of average age of menarche and an early onset of menopause.

While childspacing may be highly culturally influ­ enced (either by abstinence or by contraception and abor­ tion) , there is a biological parameter which gives the minimum spacing between offspring. Immediately following a birth (parturition), the mother's menstrual cycle is either absent (amenorrhea) or incomplete (anovulatory cycle) and conception is not possible. The length of this period of infecundity is largely dependent upon two factors: the mother's nutritional status (Frisch 1975) and the length of the period of lactation (the period of time the mother breastfeeds the new infant) (Cox 1970).

Fertility rates of interest in this study are:

1. General fertility rate (the ratio of livebirths in 1 year/1000 women of childbearing age)

2. Fertility ratio (the number of children aged 0-4/1000 women between 22 and 44 years)

3. Age specific fertility rate (the number of births in 1 year/1000 women of a given age cohort)

4. Total fertility rate (an estimate of the number of children a cohort of 1000 women would bear if they all went through their reproductive years exposed to the age-specific fertility rates that were in effect at a particular time; it is computed by summing the age-specific fer­ tility rates for all cohorts and multiplying by the interval into which the ages are grouped)

(DeJong 1972) 44

Deaths; The crude death rate is perhaps the most com­ monly used measure of mortality. It is the ratio of the number of deaths in a given population within a specified year to the size of that population at midyear. As with the crude birth rate, the crude death rate is often not a very accurate indicator, in this case because mortality rates are highly affected by the age structure of the population. A young population will have a lower crude death rate than an older population even though the death rates at each age in the two populations are identical.

Further, differences between two populations in their sex ratio will also affect the crude death rate because males at all ages usually have death rates somewhat higher than those for females (Heer 1968).

Because the crude death rate is an imprecise tool, age-specific mortality rates have been developed. The ages at which age-specific mortality rates are most lilcely to be high are indicators of how well a society is adapting to its environment. In general, the age- specific mortality curve has a U shape: high in the first year of life, decreasing rapidly in the second and third years -until age 9, remaining low until middle years then increasing at a rapid rate until the older years

(Bogue 1969)• 45

Of particular interest to genetic demographers are mortality rates during the pre-reproductive years. The following have been demonstrated to be very useful measures:

1. Infant death rate:

deaths nrior to 1 year of age ^ 1000 number of births that year 2. Early childhood death rate:

______deaths of ages 1-4______-v yoOO number of births - deaths prior to 1 year

3. Pre-reproductive death rate:

deaths nrior to reproductive age (15) x i ooo number of births in past 15 years

It is life tables, however, that provide the most complete picture of mortality in a given population. Two types of tables can be constructed: (a) a "period life table," which is the most common, summarizes the age-sex- specific mortality conditions occurring in a given year, and (b) an abridged life table, which provides data for persons in age groups, usually of 5 year cohorts.

The former type assumes a cohort of fixed size at birth (usually 100,000) and provides the following data for each year of age:

1. (qx) the probability of death during the year for those persons entering an exact age x

2. (dx) the number of deaths occurring between exact age x and exact age x + 1 46

3. (lx) the number of survivors to exact age x

4. (Ijx) the number of years of life lived by the cohort between exact age x and age x + 1

5. (Tx) the total lifespan of years lived by the cohort from age x to the end of the human life­ span

6. (c) the mean number of years of life remaining from age x to the end of the lifespan.

For the abridged life table, the same data are col­ lected, except for ax, dx and Lx. Thenumber counted are those affected in the designated interval group, not a one y e ar period (Heer 1963).

Migration; lee (1966) has defined migration as a change of residence from one region or place to another. When migration occurs across national boundaries it is called immigration or emigration (depending upon whether indivi­ duals are entering or leaving a specified nation); move­ ment within national boundaries but between regions is termed "in-" or "out-migration" (Swedlund and Armelagos

1976).

Of the three basic elements determining population structure, migration varies the most from country to country, both in its importance and in the accuracy with which it is measured.

To measure the crude rate of migration, the number of total migrants during the year is divided by the mid­ year population. The rate of out-migration is the number of out-migrants divided by the midyear population of the place of origin. The rate of in-migration is the number of in-migrants divided by the midyear population of the place of destination. The net migration rate is the ratio of migrants to or from divided by the midyear popu­ lation (Heer 1968).

Breeding size: We have discussed the calculation of the vital rates which will be important for our genetic analysis. However, we are not interested in calculating the vital rates for a total population living in a given area. Humans do not mate randomly, but within subdivi­ sions or isolates, which are circumscribed by geographi­ cal, economic, religious, ethnic or other cultural bar­ riers. Because the term "isolate" has been variously defined, we will elaborate on the development of the con­ cept and specify how it will be considered in this study.

morris (1971) states that the Swedish scientist

Yr’ahlund introduced the term "isolate." In 1928 he con­ sidered the case of two closely related panmictic popu­ lations which exchanged individuals across their boundaries; he termed these populations isolates.

As Dahlberg (1929) used the term, an "isolate" referred to an abstract breeding unit; it was panmictic and did not take into account differential family size.

Further, he devised a method for estimating the size of 48 the isolate by a formula using the number of first cousin marriages occurring within a certain group:

(N - 1) = 2b(b - l)/c where N is the size of the isolate b is the average number of children reaching adult­ hood and marrying c is the frequency of first cousin marriage.

This formula, however, may not be used for populations in

Ohio as all first cousin marriages are prohibited by law.

Roberts (1963) suggested that the term "isolate" be restricted to "...those breeding entities within a cul­ turally homogeneous population which, by their existence, promote genetic heterogeneity among one another and homo­ geneity within themselves." This definition eliminates not only small isolated populations in which the breeding population is identical to the population as a whole, but also subgroups of large populations either socially or geographically defined (Freire-Maia 1974).

Eenoist (1973), however, rejected Roberts' defini­ tion, especially for breeding groups in complex societies.

The definition of an isolate adopted by Benoist will be utilized in this study: "Those human groups whose main characteristics are their small size and social or geo­ graphic isolation."

However, even the isolates present a population contingent much larger than the basic parameter of 49 interest to the genetic demographer. A more important measure than isolate size is the size of the breeding population (N). This may be calculated by the method of

Glass (1952) as the number of parents who have children with ages ranging from 1 day to the mean reproductive age

(usually taken to be 30). Therefore, the breeding popu­ lation excludes infertile couples, celibates, persons under reproductive age and those v/hose children are all over 30 years. Generally, the breeding population is roughly 35/° of the total population (Freire-I.Iaia 1974).

Because of a number of factors (differential ferti­ lity, a distorted sex ratio or inbreeding) the' estimate of the breeding population may be a rather biased para­ meter. In humans, corrections may be introduced into the

estimate of breeding size to obtain an estimate of the

"effective breeding size." Morris (1971) notes that the

effective breeding size (l>e) is the breeding size (I\T) reduced so that the remaining number is equivalent to the ? number of individuals in the ideal population.

The correction for differential fertility is the one chiefly used for humans because fertility differen­ tials are usually the most important factor in reducing

2. In the "ideal, population's" gene pool, a "random gamete has an equal probability of having come from any parent (all of whom are unrelated) and of mating with any other gamete." the effective breeding size. Using this correction, the

effective size of the breeding population is the number of reproducing adults/generation weighted for their con­ tribution to the next generation. It was initially cal­ culated by Wright (1938) as

4N - 2 e where I\Tg is the effective breeding population size N is the number of parents in the population ^ -I- is the variance in number of gametes contri- buted to the next generation.

Wright (1938) has also determined other correction factors:

1. for unequal number of sexes:

4NfNm Ne + Km where Nf is the number of breeding females Km is the number of breeding males Nf + Km = N (the breeding population)-

2. for inbred populations:

where P is the inbreeding coefficient (Morris 1971).

However, these latter two corrections need only be made if the inequality in number of sexes or the magnitude of inbreeding is extreme.

Population growth: The biological fitness of an indivi­ dual or a population is measured by its relative contri­ bution of viable, fertile offspring to the next 51 generation. Tiie actual achieved reproductivity of a population is a balance between loss by death and infer­ tility and gain by birth. Biological fitness is measured by the rate of increase or decrease in the total size of the population by a quantity (r) called the intrinsic rate of increase. This rate (r) is calculated from age- specific birth and death rates and was first used to describe population fitness by Fisher (1930) who called it the Malthusian parameter.

The inherent capacity for population growth is referred to as the "biotic potential" and refers to the theoretical maximum rate of growth which a population might achieve if optimum conditions prevail. If a popu­ lation occupied an ideal environment within which reproductive performance could be maximized, it would be nossible to attain the maximum rate of increase (r ). max This theoretical maximum is rarely realized, however, and usually is present only for brief periods in the early stages of colonization. The highest intrinsic rate of increase of any human population has been recorded among the Hutterites, where a ratio of 10.4 livebirths was reported for women past reproductive age (Underwood 1975).

Over long periods of time, birth and death rates in a closed population tend to attain a state of equili­ brium so that there are only minor fluctuations around a 52 relatively stable equilibrium level. The equilibrium point (where the growth rate stabilizes at zero) is designated as the carrying capacity of the environment

(Underwood 1975).

There are two corollary concepts related to popula­ tion growth which are fundamental to an understanding of population dynamics. These are the concepts of station­ ary and stable populations. In the former, there is no growth or decline in population numbers: birth rates equal death rates, and migration rate is zero. In the latter, there is an increase or decrease in population numbers at a constant rate: birth rate does not equal death rate, but their rates remain constant (Cavalli-

Sforza and Bodmer 1971).

Lotka (1925) first proposed the idea of a "stable" population. He discovered that in a population closed to migration and with constant age-specific rates of birth and death, the age distribution of a population would approach a final distribution, with the total size growing ultimately at a fixed rate (r).

Among anthropologists, only Eoberts (1963) has used the intrinsic rate of increase to measure the biological fitness of a population. He studied the population on

Tristan de Cunha and calculated the intrinsic rate of in­ crease from the fertility and mortality history of 53

cohorts. He found that the fertility of the founder

group was the highest of all cohorts.

Cavalli-Sforza and Bodmer (1971) have shown that

the intrinsic rate of increase can be obtained as the

solution of lotka's fundamental equation m Z. e"rxl b = 1 x=0 x x

where x measures time in units of 1 or more years 1 is the probability of survival from birth to age x bx is the age-specific birth rate (which is the number of births to individuals in the age group x to x + 1. (See Appendix B)

The calculation of r is usually done in terms of the

females:

r - 10geHo I where Rq is the net reproductive rate (a measure of the rate of increase of the population per genera­ tion) T is the length of a generation in years.

Forces of Kicroevolution

Genetic drift: Genetic drift results from random fluctu­ ations in gene frequencies between generations as a con­

sequence of sampling error. Ileiosis and fertilization are the biological basis of random drift in gene frequen­

cies. The two alleles which occupy each autosomal locus in the fertilized egg are a sample of the four genes at 54 that locus in the two parents. In small populations, gene frequencies have a high probability of generational fluctuation because of this sampling process. In small populations, the magnitude, but not the direction, of change is determinate. As Wright (1950) noted, genetic drift will only occur as a relevant evolutionary force v/hen a population has a small effective size (Kg)* This small N may result from any of the following: (a) at the inception of the group (founder effect), (b) at any given moment from a nonselective disaster (bottleneck effect), (c) at regular intervals along time (in insects as a result of seasonal variations in climate), or (d) constantly.

The anthropological study of genetic drift has in­ volved a number of human populations. Glass (1956) stu­ died the Dunkers in Pennsylvania and attributed genetic variation between a migrant population and their European parental population to the effects of genetic drift.

Giles (1966) attributed gene frequency differences . betv/een two New Guinea highland populations who had split off from the parental population to genetic drift (par­ ticularly founder effect). Roberts (1967) found that both founder effect and inbreeding contributed to vari­ ation in the genetic structure of Tristan de Cunha.

Cavalli-Sforza (1967) compared small Italian peasant 55 villages which had experienced no major immigration since the 7th century B.C. and concluded that genetic drift can dramatically affect microevolution in small popula­ tions over a short period of time. In larger peasant villages, however, gene flow is great enough that the effects of drift are usually of little consequence

(Freire-Maia 1974).

There are two primary methods used to calculate genetic drift. First, according to Wright (1940), random drift in a population may be calculated as

N aq _ ^ e 2 where 'dq is the variance resulting from drift q is the gene frequency I\Te is the effective population size.

In successive generations, the variance is compounded, so o that in generation "g" the variance )g is

q(l - q) 1 - (1 - £Ne) g

(Wright 1942).

Second, Lasher and Eaplan (1964) devised a measure for estimating the potential occurrence of genetic drift.

This measure, the coefficient of breeding isolation, is calculated by multiplying the effective size of the breeding population (N ) by the effective immigration V rate. The smaller this index of isolation, the greater the likelihood that random genetic drift has been a relevant microevolutionary force in that population.

According to Roberts (1956), coefficients of isolation higher than 50 correspond to populations where the ef­ fects of random drift are slight; coefficients below 5 imply significant microdifferentiation from genetic drift coefficients lower than 0.5 characterize populations under a very strong action of genetic drift.

Inbreeding: For the population geneticist, consanguinity refers to a relationship between two individuals sharing one or more common biological ancestors. Inbreeding is a genetic consequence of consanguinous matings. Inbreeding is a departure from random mating; its main genetic con­ sequence is to increase the proportion of homozygotes in a population. Thus, through inbreeding, rare recessive genes are phenotypically more apparent.

In 1913 Pearl expressed a need for a coefficient by which the geneticist could quantify the degree of in- breeding (Reid 1973). Two major formulations of an in- breeding coefficient were subsequently proposed.

First, Wright (1921) defined an inbreeding coeffi­ cient (F) as the genetic correlation between gametes at fertilization. This correlation could be caused by bio­ logical kinship of the parents, by various types of assortative mating, or by mating "within local races." 57

Tiie second inbreeding coefficient (f) was developed by Haldane and Moshinsky (1939) and Malecot (1943) and is based on probabilities ratber than correlations. In this case, the inbreeding coefficient is the probability that genes at a given homologous locus in uniting gametes are identical by descent (they were copied from a single gene carried by a common ancestor). This approach, unlike

Wright's, limits the problem to parental consanguinity.

The method of ascertainment of inbreeding coeffi­ cients for a whole population will depend upon whose definition (P or f) we wish to use in our measurement.

Por Wright's correlation, the most common method used is bioassay. This technique has been developed by Morton and Yasuda (1962) and Yasuda (1963) and uses the "method of maximum likelihood" to find the inbreeding coefficient and allele frequencies with the highest probability of producing the observed data. This method of estimation involves the use of derivatives of log functions and an understanding of the procedure requires an understanding of differential calculus (Reid 1973).

There are two primary methods for calculating the inbreeding coefficient for whole populations when using the "f" model. The first, determined by Malecot (1948) is based on pedigree studies. Here, the individual 53 inbreeding coefficient (F)^ is calculated for each mem­ ber of the population. Then the population coefficient of inbreeding (f) is the arithmetic mean of the indivi­ dual inbreeding coefficients:

•p t? S. F f = P = -5T The second method was developed by Crow and Monge (1965) and is called the method of isonymy. This approach esti­ mates total population inbreeding coefficients by mea­ suring the frequency of marriages between persons of identical surnames. This approach assumes that spouses are chosen without regard to surnames. Any increase over the randomly expected frequency of isonymous marriages is viewed to result from consanguinous marriages. The observed value of the proportion of isonymous unions is divided by 4 to give the inbreeding value of the popula­ tion.

Reid (1973) finds no record of a human population in which the inbreeding coefficient is greater than 0.05, and most human populations have inbreeding coefficients below 0.005- Spuhler (1975) notes that because inbreed-' ing coefficients are sufficiently small in most human populations some workers ignore them completely when dealing with problems of genetic dynamics of human

3. This is not the same as Wright's "F." populations. Sometimes, however, inbreeding effects be­ come very apparent if deleterious rare recessives exist in the population, or if inbreeding depression can be detected.

Gene flow; Gene flow results from migration and inter­ breeding with the result that there is an exchange of genes between two initially different populations. Gene flow leads to an increase in the genetic variability within populations and a decrease in the genetic variabi lity between populations. Gene flow thus tends to make populations more alike as opposed to drift, which has a diversifying effect. Maruyama (1970) gives the rate of decay of heterozygosity as

m'TT 2 2N2 where m is the rate of migration between adjacent iso­ lates N is the number of isolates.

Migration with inbreeding also allows mutants arising in one population to be exposed to new genetic combinations in many different environments. In this way, gene flow acts to increase the adaptive potential of the species, just as segregation and recombination provide new opportunities for adaptive combinations of genes within a population. Several anthropological investigators have studied gene flow. Baker and Saunders (1972) have summarized these studies and conclude the following. Hunting and gathering populations have high rates of gene flow en­ couraged by social mechanisms stimulating outbreeding

(e.g. the incest taboo). Tribal groups in South America also have high rates of gene flow, but.the operative social influences are different. With the South American

Indians, organized warfare causes gene flow of a differ­ ent geographical nature than that of the hunters and gatherers. Among peasant groups, new factors such as social class become important in the pattern of gene flow'.

There are two methods for the determination of gene flow. The first is a direct method utilizing geneologi- cal records with birthplaces of spouses recorded. Here gene flow into a population is measured by

number of immigrant spouses, number of local born spouses

The second method utilizes gene frequency differ­ ences between populations. Here, migrants from two dis­ tinct parental populations (p^ and Pg) are present in proportions m and 1 - m. When they establish a hybrid population (H), then 61

where is the average gene frequency of all migrants,

and when we have a gene "A" whose frequencies in and

Pg are q^ and q2 respectively (Workman 1973).

Natural selection: Natural selection is the evolutionary

process through which gene frequencies are changed in a

population as the result of differences between indivi­

duals in Darwinian fitness. It occurs through differen­

tial transmission of genes from individuals to the suc­

ceeding generation. This variance in transmission may

result either from differential fertility or differential

mortality.

Historically, the opportunities for natural selec­

tion appear to have varied during human evolution.

Underwood (1975) holds that during the majority of the preindustrial period of human evolution, differential mortality was the major selective ajent; in industrial­

ized nations where prereproductive mortality is very low,

differential fertility is the major selective agent.

Further, Kirk (1963) has determined that, at least for

the United States, the opportunity for natural selection has been decreasing over the past few generations. He

concludes that this trend is the result of demographic

changes in urban populations such as decreasing birth rate, and a decreasing variance in the number of off­

spring produced by women. 62

While it is difficult to measure actual selection, it is possible to estimate the opportunity for it. Crow

(1953) devised a measure of the maximum amount of differ­ ential fertility and mortality in a population called the

Index of Total Selection.

The calculations of Crow's Index requires that all females be counted at a single time (birth), so that both survivors along with those who failed to survive to their reproductive years are included in the sample.

The index of selection potential from mortality is

where p^ is the probability of death prior to reproduc­ tive years pg is the probability of surviving from birth to reproductive age.

The component from differential fertility is cal­ culated as

2 where S~ is the variance of the offspring of the survi- _ o vors X is the square of the mean, s The Index of Total Selection (I) then becomes

This index is not an accurate measure of actual selection, but provides an estimate of the upper limit of that rate of change from natural selection in a population and it indicates which variable (differential fertility or mor­ tality) has probably been the most affected.

The Significance of

Cultural Factors to Population Studies

Cultural, as well as biological, factors shape population strcuture. Each of these forces (fertility, mortality and migration) and some of their social modi­ fiers have been discussed in anthropological literature.

However, the degree of attention and the sophistication of analysis certainly has not been equivalent among the three forces. Studies of the influence of cultural fac­ tors on the force of fertility have been much more pro­ minent in the anthropological literature than have stu­ dies investigating the effect of social forces on mor­ tality or migration. As Nag (1976) has noted, "...their focus is almost entirely on fertility and kinship." In fact, in the most recent anthropological book on the relationship between social organization and population structure (Nag 1976), eleven articles deal with the rela­ tionship between cultural factors and fertility, none deal with the relationship between cultural forces and mortality, and only two are concerned with cultural in­ fluences on migration. In these two migration studies, 64

one deals with the influence of migration on fertility

and the other totally omits the influence of migration on

population structure. This is an example of the fact

that the factors of mortality and migration have not been

systematically organized, and the framework for analysis

of these factors is in a more embryonic stage of develop­ ment .

In this section on the theoretical foundation of

the present study, I will present an analytical framework

for cultural influences only as they relate to fertility.

The theoretical foundation of the cultural influences on migration and mortality will be discussed primarily in terms of the deficiencies of extant studies for the pur­ pose of this research.

Cultural Factors Influencing fertility

Sporadic accounts of cultural influences on ferti­ lity can be found in nineteenth century ethnographies.

Carr-Saunders (1922), however, was the first to attempt a

cross-cultural review focusing on the relationship between cultural factors and fertility. After presenting a rather extensive review of anthropological literature on societies at different technological levels in all parts of the world, he concluded that the evolution of human culture brought a universal tendency toward the maintenance of an "optimum population" appropriate to the resources of each area and the level of economic techno­ logy of its occupants. He noted that population growth is limited by practices such as prolonged lactation and prepubertal intercourse. He also found that every

"primitive race" uses abstinence, abortion and infanti­ cide either singly or in combination to control popula­ tion size. Because his data were drawn from the fragmen­ tary and highly ethnocentric studies of the nineteenth century ethnographers, his study is not considered reliable today.

Several years later, Ford (1945, 1952) completed a second cross-cultural study of human reproduction. Using the Human Relations Area Files' data on 200 societies, he concluded that fertility is an acquired motive rein­ forced by social rewards and punishments. He also found that there is a universal concern with female infertility and that abortion and infanticide are universal in primi­ tive societies.

In an early interdisciplinary study sponsored by

UNESCO, an anthropologist (Raymond Firth), a demographer

(Frank Notestein) and others investigated the relation­ ship between cultural variables and fertility. Lorimer

(1954), who was responsible for compiling the final re­ port, concluded the following: 66

1. There is a relationship between polygyny and the lactation taboo.

2. Postpartum abstinence is not chiefly an expres­ sion of individual preference, but is cultur­ ally prescribed.

3. Postpartum abstinence is entirely congruous with a strong cultural emphasis on high ferti­ lity.

4. Social disorganization and religious attitudes promote or inhibit high levels of fertility.

5. Corporate kinship groups provide powerful moti­ vation for high fertility and these kinship groups tend to be formed in societies with a strong emphasis on unilineal descent.

6. In societies emphasizing unilineal descent and corporate kinship groups, children are valued because they insure the continuance of the lineage.

The studies discussed above provided generaliza­ tions on the influence of cultural factors on fertility.

However, none of them provided an analytical tool for the comparative study of fertility. In 1956, Davis and Blake set forth such an analytical framework in an article on social structure and fertility. They first presented a classification of the intermediate variables through which any social factors influencing the level of ferti­ lity must operate. They then discussed in broad outline how some types and elements of social organization, acting through these variables, appear to enhance or depress fertility. Their framework is structured by the three necessary steps generally recognized to be 67 necessary for reproduction:

I. Factors affecting exposure to intercourse ("Intercourse variables") A. Variables governing the formation and dis­ solution of unions in the reproductive period 1. Age of entry into sexual unions 2. Extent of permanent celibacy 3. Amount of reproductive period spent after or between unions a. When unions are broken by divorce, separation or desertion b. When unions are broken by death of the husband B. Variables governing the exposure to inter­ course within unions 4. Voluntary abstinence 5. Involuntary abstinence (from impotence, illness, unavoidable but temporary separations) 6. Coital frequency (excluding periods of abstinence

II. Factors affecting exposure to conception ("Conception variables") 7. Fecundity or infecundity as affected by involuntary causes 8. Use or non-use of contraception a. By mechanical or chemical means b. By other means (rhythm, withdrawal, etc.) 9. Fecundity or infecundity as affected by voluntary causes (sterilization, sub­ incision, medical treatment, etc.)

III. Factors affecting gestation and successful parturition ("Gestation variables") 10. Fetal mortality from involuntary causes 11. Fetal mortality from voluntary causes

In this framework, all of the variables are con­ sidered to be present in every society, either in a posi­ tive, negative or neutral way. 63

Davis and Blake noted that societies differing in their social organization do not necessarily have dif­ ferent fertility values with respect to all of the vari­ ables. Different cultures may exhibit similar values on some variables (for example, some nomadic tribes and settled agrarian villages may have the same age at mar­ riage; and a "primitive" group may practice the same rate of abortion as an industrialized society). However, they concluded that two contrasting societies are not likely to manifest similar values for all the variables

(even when their general fertility rates are nearly equal.

In 1962 Nag drew data from a core of 61 societies and concluded the following in terms of Davis and Blake's intermediate variables:

1. Age of entry into sexual unions: Late age at first marriage in women causes a reduction in the fertility levels of some Western societies; how­ ever, the data did not demonstrate a general signi­ ficant negative association between the age of women at marriage and the fertility level. (Note: Nag only dealt with the age at marriage of women because the reproductive span of men is longer than that of women and the fertility measures used were based on the reproductivity of women. He did dis­ cuss, however, the possibility that a large dis­ crepancy between the ages of the husband and wife could affect the wife's reproductive performance.) The effect of premenarcheal sexual relations on fertility is not clearly known.

2. Extent of -permanent celibacy: There is very little quantitative data on the celibacy or perma­ nent nonmarriage of women in the selected societies; - the extent data indicated that there is generally very little loss of fertility associated with celibacy in the selected societies. 69

3. Amount of reproductive -period spent after or between unions: There is a tendency toward a nega­ tive association between the frequency of separa­ tion or divorce and the fertility level, but this trend was not borne out by a test of significance. There are a few societies (e.g. Jamaica) in which instability of marriage is considered to be a major factor responsible for the reduction of fertility. There is a significant positive association between the frequency of separation and the inci­ dence of sterility. Postwidowhood celibacy does not have a general negative effect on the fertility level of the selected societies.

4. Voluntary abstinence: There is a significant negative association between the period of post­ partum abstinence and fertility level. Two inter­ vening variables were associated with this factor: that the period of lactation tends to prolong the interval between pregnancies, and the extent of poljrgyny may affect the length of the postpartum abstinence period. Coitus is avoided with a menstruating woman in almost all societies. However, this does not seem to be of any general significance in ex­ plaining variance in fertility because a woman is not fecund during her menstrual period. In some societies, restrictions on coitus may be in connection with special occasions such as ceremonies, economic undertakings, war, etc. While these may significantly affect fertility in some societies, a generalization is not possible from the available data.

5. Involuntary abstinence: The temporary absence of married and marriageable men from their homes is a common phenomenon in some nonindustrialized societies. While this may be the most important factor affecting the fertility in some societies (e.g. Puraui), there is not enough evidence to com­ ment on its general importance for fertility levels of nonindustrialized societies. (note: Nag did not consider other factors associated with involuntary abstinence.)

6. Coital frequency: Fertility may be affected negatively if €his frequency is either too low or too high. However, the data were inadequate for 70

testing an association between frequency of coitus and fertility.

7. Fecundity or infecundity as affected by invol­ untary causes: The data for the selected societies were not adequate for evaluating the effects on fertility of age at menarche, the period of adoles­ cent sterility, and age at menopause. There are contradictory results regarding the effect of cli­ mate on age at menarche. The effect of diet is more clear: a high protein diet seems to acceler­ ate the onset of menarche.

3. Use or non-use of contraception: Coitus inter- ruptus is the most widely used method of contra­ ception in the societies selected, but it was generally practiced to avoid pregnancy during the postpartum period or to avoid premarital pregnancy.

9. St erilization: In many societies drugs (herbs) are used to induce at least temporary sterility. This practice does not have a significant associa­ tion with fertility.

10. Fetal mortality from involuntary causes: The data regarding the frequency of miscarriage and stillbirth available for the societies are not reliable.

11. Fetal mortality from voluntary causes: In at least one society (Yapese), the practice of volun­ tary abortion seemed to be mainly responsible for the low fertility level. In comparing his data to that of V/estern societies, Nag indicated that abor­ tion is generally practiced more frequently among industrialized societies. Among Western societies it is practiced mostly as a measure of birth con­ trol, while in nonindustrial societies it is prac­ ticed primarily to terminate premarital pregnancies.

Rag has continued his interest in the study of cul­ tural influences on fertility. Recently (1975), he in­ vestigated the effects of four aspects of marriage and lcinship institutions on fertility through their influence on the intermediate variables of Davis and Blake. These 71 four aspects were the form of marriage, type of union, family type and corporate descent group. Again, Nag focused upon nonindustrialized societies in which modem contraceptives are not widely used. In this study he concluded the following:

1. Relation of form of marriage to fertility: Societies in which polyandry is an ideal or ap­ proved form of marriage are rare in the contempor­ ary world. In the two examined, there was no sig­ nificant difference between the fertility levels of polyandrously married and nonpolyandrously married women. The results of studies relating polygyny and fertility are often contradictory and inconclusive. However, well designed studies tend to indicate that polygynously married women have lower ferti­ lity than monogamously married women. The mechanism by which polygyny can reduce fertility is not well understood.

2. Relation of tynes of unions and fertility: Of three types of unions examined in various soci­ eties, there is general agreement that the visiting type of union is generally associated with lowest fertility, common law unions are intermediate, and legal unions are generally associated with the highest fertility.

’ 3. Relationship of family type and fertility: Contrary to prominent but generally untested hypotheses, the cumulative fertility of women living in extended families is somewhat lower than that of women living in nuclear families.

4. Relation of corporate descent groups and fer­ tility: There is no statistical evidence that societies emphasizing unilineal corporate descent groups generate stronger cultural motives for high fertility. 72

Cultural Factors Influencing Migration

Cultural anthropologists have recently experienced

a dramatic increase of interest in migration as noted in

the review article by Graves and Graves (1974). The majority of these studies have dealt with rural to urban migration. Common areas of investigation are the adap­ tive strategies used by the migrant, the psychological variables of the migrant, and "push and pull" factors for migration. When migration is considered as a selective process, Graves and Graves note that it has become some­ thing of a cliche to find that migrants will be dispro­ portionately drawn from those segments of the population which occupy the least favored structural positions.

lor the present study, however, we are interested

in migration as it relates to the population structure.

In order to determine this, we must know the age and sex

composition of the migrants. The cultural factors of im­

portance, then, are those which differentially select for

age and sex. Cultural anthropologists have not consi­

dered this topic thoroughly. Occasionally, references

will be made to differential sexual selection for migra­

tion (e.g. Herskovits 1963 for Africa in general; Otter-

bein 1965 for the Caribbean in general); however,

quantitative data is lacking. Further, information con­

cerning age distribution of migrants is also almost 73 totally lacking.

Turning to sociology does not improve the situation.

Petersen (1975) makes the generalization that "...mi­ grants are usually young," and that "...one sex usually predominates." While he noted that the sex which pre­ dominates will depend on the social factors, these

"social factors" have yet to be systematically examined.

Thus, previous studies examining cultural factors influ­ encing age and sex composition of migrants have not been performed.

Cultural Factors Influencing Mortality

There are a vast number of studies in cultural anthropology which discuss mortality. These investiga­ tions come from the topical areas of political, anthropo­ logy (e.g. war), psychological anthropology (e.g. sui­ cide, anorexia nervosa), ecological anthropology (star­ vation, freezing, infanticide), and especially medical anthropology. However, an analytical framework such as that proposed by Davis and Blake for fertility has not been presented for mortality. A possible analytical framework will be examined in the section on implications for future study. Because the level of mortality in the population discussed in this study is so low, this topic will not be discussed further here. Summary

Drawing together conceptual tools from the disci­ plines of anthropology, demography, genetics and biology,

I have formulated the theoretical framework used in this study. The theoretical background just reviewed indi­ cates that population structure and vital rates can be useful to physical anthropologists concerned with deter­ mining patterns and potentials for microevolution. In addition, I have shown how cultural factors may signifi­ cantly influence the rates of the vital processes. CHAPTER IV

THE GREEK COMMUNITY

History of Greek Immigration into the United States

Eactors Promoting 'Emigration

The first settlement of Greeks in the United States dates from 1735 when a Scottish physician, Dr. Andrew

Turnbull, founded the Greek Colony of New Snyrna, Florida.

The colony did not survive long, even though more than two hundred Greeks had been initially recruited. Most of the settlers died from malaria or in skirmishes with the

Indians (Polites 1945).

A second small scale migration dates to the time of the Greek War of Independence (1321-1829) when American missionaries brought over a number of young boys chiefly from the island of Chios. These youths were educated at

Amherst, but they did not form a permanent settlement; most returned to Greece after their education was completed.(Polites 1945).

75 76

Kajor Greek immigration to the United States was

chiefly a product of the late nineteenth and early

twentieth centuries. During this period, migration de­ pleted the population of Greece by about one fifth. The most prominent factors accounting for this mass exodus were economic hardship, relative overpopulation, communi­

cation, and political oppression.

Economic factors: Nearly all persons who have studied

Greek emigration conclude that the primary impetus pro­ moting migration was the search for improved economic conditions. The bulk of early Greek immigrants came from the Peloponnesus, chiefly the rocky, mountainous regions of Arcadia and Laconia. In 1891 and 1399 severe economic crises resulted from the nearly complete failure of the currant crop in that area (Xenides 1922).

In addition, changes in the commercial policies of

Prance and Russia severely disturbed the Greek economy.

Because its own crop was destroyed by phylloxera, Prance had purshased about half the Greek currant crop from 1863 to 1890. In a rising currant market, Greek farmers allowed the silk culture to decline and many destroyed their olive orchards to allow more ground for planting vines. However, when the French developed an insect resistant vine, they no longer needed to import Greek currants. When the French vineyards were replanted and 77 their yield increased, France enacted a protective tariff that literally legislated Greek currants out of the mar­ ket. Russia adopted a similar policy. The resultant sharp decline in the demand for Greek currants forced severe economic hardships on the Greek farmers (Fairchild 1922).

Several other factors contributed to the economic problems of the Greek peasant. The government imposed heavy taxation on the populus to support continuous ter­ ritorial disputes with Turkey. In addition, the Great

Powers imposed a trade blockade (1387-1391) on Greece for engaging in hostilities with Turkey (Vlachos 1964).

Finally, the necessity of supplying a dowry for the un­ married females in the family prompted fathers and bro­ thers to migrate in order to send back money.

Population -pressures: After 400 years of Turkish domina­ tion, the Greeks achieved independence in 1830. At this time, however, only a small portion of the Greek terri­ tory was freed: the Peloponnesus and the mainland of

Greece south of Thessaly. Persons in other areas which remained under Turkish rule existed in a chronic state of political unrest and a series of uprisings among the

Greeks drove groups of refugees into the independent areas of Greece, especially from Crete and Macedonia.

Thessaly was united with Greece in 1332, and the emancipation of other adjacent areas from Turkish rule was achieved as a result of the Balkan War (1912-13).

The exchange of populations under the Treaty of Lausanne in 1323 introduced more than 1,000,000 refugees from Asia

Minor, Eastern Thrace and Southern Bulgaria; this in­ creased the population by 23$. Thus, while the geographi­ cal area of Greece increased about threefold, the popu­ lation increased over sevenfold (Valaoras I960). Given the nature of the Greek soil (about 30$ nonarable land), this influx resulted in an overpopulation of the avail­ able farm land.

Political and religious factors: Greeks emigrating from the Ottoman empire often left for political and religious rather than economic reasons. The constant political up­ rising in areas under Turkish rule resulted in continuous friction between Turkish and Greek peasants. In addition, fear of conscription into the Turkish army was a factor promoting migration. Prior to 1903, Greeks residing in the Ottoman Empire were exempt from military duty. How­ ever, the new Turkish constitution of 1903 required

Greeks residing within the Turkish empire to render mili­ tary service to Turkey (Saloutos 1964). Some citizens of

Greece also left their homeland to avoid the compulsory two year military service, especially in the period just prior to 1912. 79

Communication: Vlachos (1964) suggests that another

motivating factor for emigration was the extensive adver­

tisement of the United States by the steamship agents

who regularly canvassed the rural districts in search of

prospective passengers. These men placed posters in the

coffeehouses and told exaggerated tales of the ease of

acquiring wealth in the United States.

The constant stream of letters sent back to Greece

by the first immigrants to the United States furthered

this glamorous advertising. In addition, money sent back

to Greece by the immigrants in the United States appeared

to be great wealth to the poverty stricken peasants in

Greece. Each Greek in America became the nucleus of a

rapidly increasing group of his own kin or neighbors

(Fairchild 1922).

Pattern of Greek Immigration

Even though Greeks came to the United States

earlier in the country’s history, the records of the Com­ missioner General of Immigration make no reference to

them until 1924, when one is listed. In 1848 another

immigrant arrived, and in 1350, two more. After 1830 the pattern changed; more than 100 arrived during 1882. In

1391 more than 1000 arrived for the first time. Immigra­ tion was most intense between 1905 and 1915. The peak 80

year was 1907 when 36,530 Greek immigrants were recorded.

The immigration rate was considerably decreased in

1921 when Congress passed an immigration law limiting the

number of immigrants to the United States to 3 cf° of the

people from any given country as shown by the census of

1910. In a second lav; passed in 1924, the quota was re­

duced from 31° to 2$ and the base population was changed

from the 1910 to the 1390 census. These acts were deli­

berately meant to limit immigration from Southern and

Eastern Europe. However, the national quota system was

finally abandoned in the Immigration Act of 1965 which

went into effect in 1963, and there has been an increase

in immigration from Greece since that time (Saloutos 1964,

Vlachos 1964 and Petersen 1975). Figure 1 depicts yearly

Greek immigration to the United States.

The pattern of settlement in the United States

seems to have been established by the turn of the century.

Nearly always, the Greek immigrant settled in an urban

area. The most prominent sites of settlement were the

Eastern seaboard (New York City, Boston and Lowell) and

the cities of the North Central United States (Chicago,

Detroit and Cleveland) (Vlachos 1964). -1-0

uf\ <\J no cr> 0'S CO

Figure. 1,— Gieek immigration to the United States? 1880-1960, (Adapted from Vlachos-1964) ^ H 82

Historical and Cultural

Characteristics of the Columbus Greek Community

Geographical Distribution

The first Greek settler in Franklin County arrived in 1393; by 1900 he had been followed by at least 13 other Greek immigrants. This number increased over 1000$ in the next decade. In the first part of this century, the majority of Greek settlers lived in the area around

Front, Neil, I.Iound, Gay and Gift Streets, or what we might call the center and near-north side of Columbus.

Since that time the members of the Greek community have moved away from that central location and they are now geographically dispersed over the entire greater Colum­ bus metropolitan area. Figure 2 depicts the present geo­ graphical distribution of the members of the Greek community.

Education

In Greece, higher education has always been highly valued and given status worthy of sacrifice. Lee (1953) noted that education is perhaps the most prized good in

Greece. This emphasis on education was brought by Greek immigrants in general (Vlachos 1964) and also can be seen in the Columbus Greek population. The Columbus Greeks 83

1 - Worthington 6 - Whitehall 2 - Upper Arlington 7 - Bexley 3 - Gahanna 8 - Grove City 4 - Grandview Heights 9 - Obetz 5 - Reynoldsburg

Figure 2 — Present geographical distribution of the Columbus Greek community. 84 whom I interviewed strongly supported education for several reasons. First, they prize knowledge as it re­ lates to classical Greek history. More significant socially, they also value education as a means to higher economic status. In reporting which values they wished to give to their children, Greek-American parents ranked highly the one in which the child would value education.

Numerous families related family histories in which material sacrifices were made so that all children would have the opportunity to attend college. Even more fre­ quently, parents reported limiting the size of their families to a number that they could adequately care for and educate.

Although the majority of early Greek settlers were of the peasant class and usually illiterate when they arrived, they valued education. In most cases, parents attempted to provide a college education for their child­ ren. Tables 1 and 2 depict the highest level of educa­ tion attained by males and females respectively by decade of birth for the Columbus Greek population. It can be seen that the Greek immigrants were successful in their goal to educate their children. A steadily rising per­ centage of offspring have attended college or profession­ al school. For males born in the decade 1951-1960, only

6.3fo have not at some time attended college. The trend 35 Table 1 — Educational trends for males.

DECADE HIGHEST LEVEL OP EDUCATION ATTAINED* OP BIRTH 1234567 N

1871-1880 84.6# 15.4# 0# 0# 0# 0# 0# 13 1881-1890 73.1 15.4 11.5 3.8 0. 0 0 26 1891-1900 83.9 3.2 12.9 0 0 0 3.2 31 1901-1910 45.5 18.2 9.1 9.1 18.2 0 0 11 1911-1920 11.4 11.4 20.0 34.3 11.4 2.9 8.6 35 1921-1930 0 6.1 16.3 15.3 38.8 0 26.5 49 1931-1940 8.0 4.0 6.0 10.0 33.0 4.0 30.0 50 1941-1950 0 12.8 2.3 23.1 30.8 2.3 28.2 39 1951-1960 0 0 5.1 66.1 25.4 0 3.4

1961- 1 a n i' r \ ID Ll Ll U a b J.O l not comnleted present

Total 22. 0# 7.3# 12.1# 21.0# 22.0# 13.0# 14.1# 313

*Key: 1 - did not complete grammar school 2 - did not complete high school 3 - completed high school 4 - some college 5 - B.A. degree 6 - M.A. degree 7 - Ph.D. or professional degree 86 Table 2 — Educational trends for females.

DECADE HIGHEST LEVEL OP EDUCATION ATTAINED* OP BIRTH 1 2 3 4 5 6 7 N

1871-1880 Ofo 0# Ofo Ofo Ofo Ofo 0# .0 1831-1890 0 0 0 0 0 0 0 0 1391-1900 75.0 5.0 15.0 5.0 0 0 0 20 1901-1910 70.0 17.4 8.7 0 4.3 0 0 23 1911-1920 32.1 11.1 22.2 7.4 18.5 7.4 0 27 1921-1930 5.4 18.9 45.2 13.5 16.2 0 2.7 37 1931-1940 0 2.6 34.2 18.4 31.6 5.3 7.9 38 1941-1950 0 2.3 11.4 32.8 43.2 4.5 6.8 44 1951-1960 0 5.7 8.6 51.4 34.3 0 0 35 1961- Education not completed present l—1 CM o • CO • Total 18.8# \_n 21.4 f 24.6# 2.7# 3.1# 224

*Key: 1 - did not complete grammar school 2 - did not complete high school 3 - completed high school 4 - some college 5 - B.A. degree 6 - M.A. degree 7 - Ph.D. or professional degree 37 toward increased higher education is also seen in the table depicting female schooling. Although the number of females entering college and professional school is some­ what lower than for males, it is still high compared to the national average. A striking statistic is that for females born in decades since 1930, over 50$ have attended college.

Another indication that education and knowledge are highly valued by the Greek population is the strong com­ munity support for Project Paideia, a fund-raising effort for a program in Modern Greek studies at Ohio State Uni­ versity. Because the Greek community pledged to raise

$10,000 each year for four years, the university was able to initiate the Modern Greek Studies Program in Fall,

1976. Ohio State University will attempt to cover fund­ ing for the program after the initial four year period.

The program in M o d e m Greek Studies presently includes language and literature courses, but it will eventually be a multidisciplinary program including history, cul­ ture and political science courses.

In addition to supporting higher education, the

Greek-American population of Columbus has supported a

Greek community school since 1920. Originally, the Greek school met for two hours most afternoons after public school and was taught by the priest. The primary 33 function of this school has been to teach Greek language and history. Presently, classes are taught 3-2 hours on

Saturday by a lay person hired by the community.

Occupation

I,lost early immigrants came from the rural areas of

Greece and, settling in an urban area, had to learn new skills and accusations. In the early years of Greek set­ tlement in Columbus, Greek men chose occupations where their inability to speak English was not a handicap.

Most became laborers, employed by the railroad.

Because Columbus does not have heavy industry, as does Cleveland or Canton, factory jobs were not readily available. In addition, Greeks have stated a definite preference for "being their own boss." For these reasons, men would start a flower, fruit or shoeshine stand as soon as possible. The success of these small businesses in the face of a fair amount of discrimination seems to stem from a very great determination to succeed. This determination was evident in nearly every interview with older members of the community as they spoke with pride of the 80 hour Greek work week.

After a man accumulated sufficient capital, he usually became the proprietor of a larger business! a restaurant, confectionary or floral shop. The speed of 39 their upward mobility is especially remarkable because many men sent the major portion of their earnings back to

Greece.

The combined effect of this economic success and the strong value on higher education resulted in a dras­ tic trend upward in the occupations of the Greek males.

The highest occupation held, by decade of birth, is listed for males and females in Tables 3 and 4 respec­ tive^. It is apparent that the males moved rapidly first into small businesses and then to professional occupations. The percentage of laborers in the commun­ ity has consistently decreased except for the recent period, which reflects the new wave of immigrants from

Greece and the American born younger males who have not yet achieved their highest occupational status.

The statistics on the women of the Greek community show an interesting pattern. Although more than half have attended college, the majority do not work outside the home. This seems to reflect the very strong cultu­ ral belief that it is desirable to have the mother pre­ sent when children are in the home.

Family and Kinship

Early in the century, a typical house unit con­ sisted of four to ten unmarried males living communally. 90

Table 3 — Highest occupational status: males.

1 — housewife 2 — college student 3 — child 4 — teacher 5 — lawyer 6 — doctor 7 - engineer 8 — other professional 9 — restaurant owner 10 _ other business 11 — restaurant worker 12 — factory worker 13 — other laborer 14 — candy maker 15 — pink collar 16 — disabled 17 — artist Table 3 — Highest occupational status: males.

DECADE OF BIRTH -P S i i I I I i 1 1 1 I a) HO HO HO HO HO HO H O H O H O H in t—CO oocn CTi O O H H c\l CM r<0 rO "si" ^1“ LT\ unco CO 0) -p co oo co oo co ct\ cn cn cn cn cn cn Cncn Cncn cn cn cn fn O HH HH HH HH HH HH H H i—1 i—1 H H H ft EH

1 01° 01° 0/a 0/o 0/ 0/ 0/ 0/ 0/a 0/a 0/ 2 0 0 0 0 0 0 0 2.0 46.8 0 6.6 3 0 0 0 0 0 0 0 0 34.2 99.5 38.4 4 0 0 0 0 7.8 1.7 1.9 8.2 1.3 0 1.8 5 0 0 0 0 7.3 5.1 5.6 12.2 0 0 1.8 6 0 0 0 0 0 13.8 13.0 2.0 2.5 0 3.3 W 7 0 0 0 7.1 4.9 13.8 9.3 4.0 0 0 3.4 o 3.6 o 8 0 0 0 7.1 4.9 5.2 16.7 6.1 2.5 0 o q 56.3 68.9 60.0 35.7 34.1 24.1 14.8 6.1 3.8 0 17.2 10 12.5 3.4 8.6 14.3 19.5 24.1 20.4 22.4 3.8 0 9.8 0 3.6 1.3 0 3.6 a 11 0 10.3 5.7 7.3 1.7 16.3 O 12 0 0 0 0 2.4 0 0 0 •0 0 0.2 H 0 EH 13 31.2 10.3 22.9 35.7 9.8 6.8 3.6 12.2 0 6.3 14 0 6.9 2.9 0 0 0 0 0 0 0 0.4 0 0 0 0 1.7 1.9 2.0 0 0 0.4 o 15 0 o 16 0 0 0 0 0 0 3.6 2.0 1.3 0 0.7 o 17 0 0 0 0 2.4 1.7 5.6 4.1 2.5 0.5 1.4

N 16 29 35 14 41 58 54 49 79 177 552

co H 92

T able 4 — Highest occupational status: females.

Key: 1 — housewife 2 — college student 3 — child 4 — teacher 5 — lawyer 6 — doctor 7 — engineer 8 - other professional 9 — restaurant owner 10 — other business 11 — restaurant worker 12 — factory worker 13 — other laborer 14 — candy maker 15 — pink collar 16 — disabled 17 — artist Table 4 — Highest occupational status: females.

DECADE OF BIRTH

i i i i H O H O H O rl O OlO CM ro m "M" 'M* lp> co cn cncn cn cn cn cn 1961- Total 1951- 1960 present 1920 1911- 1—1 I—1 1901-19 1910 H i—1 rH rH rH rH

1 93.1$ 83.3$ 74.3* 73.9* 50.0$ 55.5$ 7.5$ 0$ 44.5$ 2 0 0 0 0 0 0 45.0 0 5.6 3 0 0 0 0 0 0 15.0 100.0 26.3 4 0 5.6 12.9 6.5 13.9 13.3 7.5 0 6.6 5 0 0 0 0 2.8 0 0 0 0.3 6 0 0 0 0 0 4.4 0 0 0. 6 w 7 0 0 0 0 0 2.2 0 0 0.3 oP, o 8 0 0 0 2.2 11.1 11.1 5.0 0 3.8 9 3.4 0 0 0 0 0 0 0 0.3 10 0 0 3.2 0 5.6 4.4 2.5 0 1.9 11 0 0 0 2.2 o 2.8 2.2 0 0 0.9 M 12 0 0 0 0 0 2.2 0 0 0.3 EH <3 13 0 5.6 0 2.2 2.8 0 0 0 0.9 14 0 0 0 0 0 0 0 0 0 o 15 3.4 5.6 6.5 10.9 8.3 6.7 10.0 0 6.0 16 0 0 3.2 0 0 0 0 0 0.3 17 0 0 0 0 2.8 0 7.5 0 1.3

N 29 18 31 46 36 45 40 74 319

VO Ul Today, however, the typical household in the Greek com­ munity is composed of the nuclear family. The Greek-

American family is intact for longer periods than typical in American society because children (especially females) frequently live with their parents until they are married.

In addition to this type of family unit, 5^ of the fami­ lies interviewed consisted of a nuclear family with an in-law residing in the same household, and 3^ consisted of a mother and an unmarried adult child living in the same residence. Other compositions were an aunt and adult nephew, a nuclear family and the husband's -uncle, and two multi-family units.

In earlier generations, marriages were usually arranged by the family, pending the approval of the child involved. More frequently, spouse selection is left to the child, with the parent's approval. Marriage partners most often meet through mutual acquaintances or at Greek community sponsored functions. In addition, a number of marriages have resulted from relationships developed at college. Females have considerably less freedom to date than do their brothers and it is not uncommon for them to be prohibited from dating until they are seniors or out of high school.

In Greece, brothers would postpone their marriages in order to provide a dowry for their sisters, and 95 customarily did not marry while the sisters remained un­ married. This practice was followed relatively strictly by the members of the first and second generations, but seems to be a much less common practice at this time.'

Parents of most children have stated that they would prefer their children to marry a person of Greek heritage. Some have stated that "we hate to dilute the blood," but more often the reason given is a functional one: marriage is difficult enough, and the more that people have in common, the more likely they will have a successful marriage. In addition, parents have stated that a daughter or son-in-law who is of Greek heritage would understand them better and fewer intergenerational conflicts would occur.

Greeks are restricted by the church from marrying relatives through the degree of second cousin without a special dispensation from the Archbishop. In addition to this restriction, there are marriage restrictions between persons of fictive kinship. Besides consanguinal and affinal ties, persons are also linked by fictive kin­ ship established through ritual sponsorship. This set of relationships is subsumed by the term "koumbaria" and they are reciprocal relationships. A baptismal sponsor ideally, but not always, is the godparent to the couple's first child. One consequence of this practice is that 96 the children of the godparent become spiritual siblings of the godchild and mating between them or other first degree relatives is considered incestuous and is pro­ hibited. However, the exact interpretation of this rela­ tionship differs in various families.

Greek community members are very family-oriented.

Mothers are expected to stay home whem children are young so that they can properly socialize the children; this is considered the mother's most important life responsi­ bility. Families spend much time together, and parents frequently take the children along to social functions rather than leave them with babysitters. While the child is not the focus of the household, he is usually included in most activities.

The family is usually patriarchally oriented. A male is expected to be the head of the household, al­ though in recent years there has been a trend toward more equality in decision-making. This authority pattern is also seen in child discipline. Mothers will tell a child numerous times to behave in a certain pattern, and the child may or may not comply. When a father instructs a child to change behavior or to perform a task, however, the child seems quick to respond.

Family closeness is also seen as a characteristic to be perpetuated. When asked what values or traditions 97 parents would like to pass on to their children, 977°

spontaneously responded that they would like their child­

ren to retain the close family unit.

The pattern of naming an infant is a custom which

further ties the child to his Greek heritage. Tradition­

ally, the first born son is given the same name as his paternal grandfather and his middle name is his father's

first name; thus alternating generations have the same names. First born daughters are sometimes given the first name of the paternal grandmother, but more often they carry the name of the maternal grandmother. If cus­ tom is strictly followed, the infant girl will also

receive her middle name from her father's first name.

Family planning, well Imown even in rural Greece, has been intensively practiced by the immigrant popula­ tion. Friedl (1962:50-51) found that in a Greek village,

"...parents who have more children than they can ade­ quately feed and care for are accused of behaving like animals... and are said to have neither brains nor self-

control." I also found a high value placed on having only as many children as could be adequately supported and educated. To this end, families effectively limit the number of children by various forms of birth control.

The primary methods of birth control differ between native bora Greeks and this Greek-American population. 98

Safilios-Rathchild (1969) found that in Greece, abortion rates are quite high and that abortion is socially ac­ ceptable, inexpensive, and performed by qualified gyneco­ logists, even though it is illegal and against the offi­ cial church position. She hypothesized that the high abortion rate in Greece results because control of con­ ception is left primarily to the male (through the use of condom or withdrawal); if conception occurs, the female then limits the family size by abortion.

In the Columbus Greek community, however, the women most often determine the method of contraception. Fur­ ther, abortion is considered improper by the majority of women even though it is legal. Hence, the patterns in methods of limiting family size have changed.

Religion

During the Turkish occupation, the Greek Orthodox

Church was the institution primarily responsible for the preservation of the Greek heritage, including language.

Priests became teachers and village leaders and.they ultimately sparked the War of Greek Independence (Xenides

1922). In this historical context, the importance of the Greek Orthodox Church can be understood today. In

Greece, the Orthodox faith is state supported and is essentially the only religion. 99

A combination of religion and patriotism pervades the whole Greek attitude toward the Church, and the cul­ ture is not separable from the religion. Religion in

Greece permeates Greek life. No one would think of ini­ tiating an important endeavor without a religious inaugu­ ration. Houses, new businesses and even journeys are blessed (Lee 1953).

Religion is not as personalized in Greece, however, as it is among United States Protestants. Interestingly, when members officially leave the Greek Orthodox Church they are many times drawn by fundamentalist Christian religions. In Columbus, the priest now leads an evening prayer meeting in a response to congregational criticism of the "meaninglessness of the ritual." In addition,

Sunday schools have been formed in Columbus and in most other American Greek Orthodox Churches, but are almost entirely unknown in Greece.

The church in Columbus is headed by a priest, accountable to the bishop in Chicago and, ultimately, to the Archbishop of North and South America, located in

New York.

In the first decade of the Greek community in Col­ umbus, there was no formal church; community members were served by itinerant priests. In 1910 a charter was granted for the establishment of a "Greek Orthodox 100

Church" and services were held at that time in a building at the comer of long and High Streets. In March, 1913» members of the Greek community rented the Masonic Temple on South Third Street and in the spring of that year the first permanent priest arrived. Since that time there have been eleven other priests. In 1922, the building of the Annunciation Greek Orthodox Church on Park and

Goodale Streets was completed (Greek-American Community

1962). In 1974 the Parish Council and Future Develop­ ment Committee contracted for 43.7 acres of land at High­ way 1-270 and Cleveland Avenue. Y/hen this is purchased, it will be the site of the relocation of the church and recreation facilities (Kropke 1975).

The Greek Orthodox Church in America differs some­ what from that in Greece in its attitude toward mixed marriages. In Greece, the Church requires that children resulting from mixed marriages be raised in the Orthodox religion; in the United States, it is only considered advisable and not required (Vlachos 1964).

In a study of Greek mixed marriages in the United

States, Katsoulis (1969:5) states that

Among Greeks, intermarriage has traditionally been looked upon as something to be avoided at all costs. A Greek son who married outside his group could become an outcast and be stigmatized as an ungrateful errant who was setting a bad example for others. The predicament of a daughter who deviated from the matrimonial form was viewed as 101 something even more tragic.

In stun, he concluded that marriage to a non-Greek Ortho­ dox was strongly disapproved by the Church, parents, relatives and friends, and only somewhat accepted if the other member agrees to convert or at least be married in the Greek Church. However, the amount of endogamy seems to be decreasing: in 1966, intermarraiges constituted

31.9$ of all Greek marriages (Katsoulis 1969) while in

1976 this percentage has risen to 46.8^ of all Greek mar­ riages (Methodios 1977).

'World View

Dimen (1976) has characterized the dominant value profile of persons in Greece as a strong sense of per­ sonal dignity, a distrust of others outside the immedi­ ate family, a belief in the correctness of male dominance, and a belief in Hellenism.

The sense of personal dignity is portrayed by the characteristic that Greeks call "philotimo." This quality encompasses more than just dignity because it is derived from honor: individual self-esteem, family honor and the honor of Greece. In part, philotimo is felt to be an inherent characteristic of all Greek men by virtue of their being b o m Greek. However, the quality must be upheld by each member of the family through approved 102

social behavior and the fulfillment of family and na­

tional obligations. The behavior of each individual in a

family reflects upon the philotimo of every other member

and a disparaging remark about Greece attacks the philo­

timo of all Greeks.

It is this characteristic of philotimo that pro­

motes Greek Americans to take care of their own who are

in financial difficulty. Although many whom I visited

were in a low income category, they managed their money

carefully and lived in well-kept homes. Only once did I

find a person in the Greek community who accepted welfare.

For the most part, if a man was unemployed, another com­ munity member would assist him in finding work. For a

Greek ablebodied man to be deliberately unemployed and

accepting welfare would be an affront to the honor of the

entire Greek community. Similarly, if a man did not

adequately provide for his family, his philotimo would be

diminished.

The Greek word 11 endrope" denotes shame as well as modesty and embarrassment. In Greece, women are charac­

terized by the endrope and men by philotimo; in the

Columbus Greek community, the endrope of women is not as

apparent. To avoid endrope, however, a Greek may avoid discussing an embarrassment that could reflect poorljr on the philotimo of himself, his family and his community. 103

This is not to say that Greeks are dishonest in their presentation of themselves, only that the truth is some­ times couched in a protective shield.

A strong historical appreciation of the accomplish­ ments of Grecian society provides the basis for a great deal of pride in the Greek heritage, and this is re­ flected in the maintenance of traditional customs and values. Continued immigration from Greece also helps to perpetuate the ideas from the original Greek homeland.

In addition, 53*8^ of the families I visited during the structured interviews reported that at least one member of their nuclear family had made at least one trip to

Greece (and in some cases, the entire family had visited

Greece several times). Finally, the common religious heritage of the members operates to keep the community closely knit and interested in preserving their cultural heritage.

Summary

In this chapter I present a brief general history of Greek immigration into the United States, as well as an ethnographic description of a single urban Greek com­ munity. The historical and cultural characteristics of the Columbus Greek community showed that while it is geo­ graphically, economically and politically well integrated into the larger Columbus population, the Greek community constitutes a viable ethnic group with distinct aspects of a continuing cultural tradition. CHAPTER V

METHODOLOGY

Conduct of the Research.

The research was conducted in the Greater Columbus

Area including the corporate areas of Bexley, Gahanna,

Grandview Heights, Grove City, Reynoldsburg, Upper Ar­ lington, Whitehall and Worthington. Initial contact was made with the Greek community through Father Sarris, priest of the Annunciation Greek Orthodox Church, in July

1976. After several discussions with Father Sarris con­ cerning the research project, I began work on the parish records in October 1976. The period of participant ob­ servation in the community lasted from September 1976 through May 1977. Structured interviews with members of the Greek community were begun in December 1976 and com­ pleted in larch 1977. The data from these interviews were coded on IBM cards and analyzed in March and April

1977.

105 106

Data Collection

Information used in this study was obtained from three major sources: personal and official documents, structured interviews with members of the Greek community, and participant observation within the Greek community.

Documents

Demographic information for the Columbus Greek population was secured from the following written sources:

1. the parish baptism and death records of the Annunciation Greek Orthodox Church, 1933-1962.

2. the vital statistics column listing births, deaths, baptisms, marriages and new community members which appeared in each issue of the "Charioteer" (the monthly 20 page newsbulletin of the Greek community), 1971-1977.

3. United States decennial census information con­ cerning the number of foreign stock (foreign born and native bora of foreign or mixed parentage) in the Columbus Standard Metropoli­ tan Area. This information is located in the Documents Department, State of Ohio Library, Columbus.

4. the Annunciation Greek Orthodox Church member­ ship committee report of 1976.

5. the mailing list of the Annunciation Greek Orthodox Church, October 1976. Official mem­ bership in the church is not a prerequisite for appearing on the mailing list.

Historical information concerning the Columbus

Greek population was obtained from the following docu­ ments: 107

1. the 50th Anniversary Album of the Greek- American Community of Central Ohio, 1912-1962.

2. social, personal and editorial column in the 11 Charioteer," the monthly newsbulletin of the Greek community, 1971-1977.

3. the report "Ethnic and Nationality Groups in the Columbus Area" (1975) published by the Transnational Intellectual Cooperation Program.

4. written family histories and biographies.

Structured Interviews

Demographic, social and cultural data were obtained through the administration of an interview schedule.

This proforma was modified from Halberstein (1973) and

V/einer and lourie (1969)(See Appendix C for a sample interview schedule). Demographic information was ob­ tained from direct questions, while social and cultural data were obtained from open ended questions and observa­ tion of the family interaction patterns and home interior.

Individuals of 102 home units were interviewed.

Interviews were usually conducted in the home, but occasionally (6$) in a business office. The structured interviews provided information on 1,286 persons, both living and deceased, who are or were members of the

Columbus Greek community.

The sample resulted in information on 416 total family units which I calculated to be 62.1$ of the 108

Columbus Greek community members maintaining contact with

the church.1

This sample size compares favorably with demo­

graphic studies of other anthropological populations.

Crawford and Goldstein (1975) obtained information on

of the individuals of Polish Hill, and Freire-ffiaia and

Kreiger (1963) sampled about 33^ of a Jewish isolate in

Brazil.

Individuals to be interviewed were generally selec­ ted at random from the church membership roster. The

exception v/as the purposeful inclusion of eleven families who had resided in the Columbus area for the longest period of time. Nonparticipation in the study was excep­

tionally low: 109 families were asked to participate and

only 7 declined (1 later withdrew information). This

relatively high rate of voluntary participation can be

attributed to several factors. My entry into the com­ munity was facilitated by an announcement briefly des­

cribing the study which v/as placed in the Sunday Church

Bulletin for three consecutive v/eeks prior to the

1. Membership in the church v/as not requisite for appearing on the mailing list of the church. Several individuals who are not church affiliated or v/ho are affiliated with a non-Orthodox Church still receive mailings. Community organizations use the church mailing list to disseminate information to all interested Greek community members. 109 interviews. It was further assisted by an article pre­ senting my personal history, the purpose of the study and an endorsement by a member of the Greek community which appeared in the "Charioteer" (See Appendix D for a copy of the article). The most important factor influ­ encing the high rate of participation, however, seemed to be the community members' profound interest in the his­ tory and trends of their community.

Appointments for the interviews were made by tele­ phone calls. When phoning, I stated my name and that the person being questioned might be familiar with my study either from the Sunday Church Bulletin or the article in the "Charioteer." If the individual did not recognize my name, I indicated that I v/as a doctoral student at Ohio

State University and I gave a name of a member of the

Greek community as a reference. I then explained that the purpose of my study v/as threefold: to determine mi­ gration patterns in the Greek community, to study the maintenance of traditional values and customs, and to detect changes in family patterns over the generations.

I informed each individual that all information would be confidential and that consenting to an interview did not obligate him to ansv/er any question he felt v/as too personal. 110

After amenities were exchanged upon my entering

the home, I obtained informed consent (see Appendix E)

prior to asking pertinent questions. Although I had

taken a Greek language course from the Ohio State Depart­

ment of Continuing Education, I was not sufficiently

fluent in the language to converse with members of the

community who spoke only Greek. However, I did inter­

view only Greek speaking individuals by asking relatives

or close friends to translate.

Demographic questions were administered in a stand­

ard manner to give me a basis for comparison among the

families. Information gathered from these questions was

transcribed onto 3 x 5 index cards so that individuals

would only be counted once and so all information about

an individual (sometimes obtained from several sources)

would be located on the same card.

To obtain social, cultural and historical data, I

conducted in-depth, open-ended interviews. When a person was particularly knowledgeable about a particular topic

(e.g. history of the Columbus Greek community, folk

remedies, medical beliefs) I extended the interview per­

iod and, at times, returned to the home to obtain even more information on that topic. In only 12 cases did the participant keep the interview to the scheduled questions.

Interview notes for social, cultural and historical data Ill were taken in shorthand on interview forms and later transcribed onto note cards for reference to particular subjects according to Murdock's format described in the

Outline of Cultural Materials (1961).

A minor methodological problem arose in scheduling the interviews: members of the community are widely dis­ persed over the greater Columbus area and I was usually unable to schedule consecutive interyiews in the same area of the city. This resulted in some difficulty because of the hazardous driving conditions this parti­ cular winter in Columbus. In a typical day, I was able to schedule 2-3 interviews averaging three hours each.

The longest single interviews were one seven-hour and two six-hour interviews. The shortest interview v/as forty minutes.

Participant Observation

Because of the urban nature of this community and because the members are widely distributed throughout the city of Columbus, I v/as not able to perform the type of participant observation possible when living in and studying a small village. However, I was able to obtain cultural information from attending dances, picnics, lunches, dinners, meetings of organizations, Sunday church services, the yearly Greek festival, and memorial 112

services. In addition, particularly informative periods

were the several afternoons and evenings I spent with

three members of the Greek community (all from different

families) with whom I developed relatively close personal

relationships. The information gathered in this phase

was also coded according to Murdock's format.

Data Analysis

Sources of Error

Prior to discussing the data analysis, I wish to note some possible sources of error in this study. The problems of validity and reliability of demographic data and the accuracy of reconstructed historical configura­ tions have been well discussed by Drake (1972),

Kalberstein (1973) and Hollingsorth (1969). They concur that several sources should be consolidated to supplement

each other and to serve as a cross check. This v/as accomplished by comparing the information obtained from the scheduled interviews with vital statistics documents, primarily parish records and the United States decennial census data.

Each of these three sources of information have limitations. The parish records were not complete for all years of the demographic study. In addition, each 113

birth in the community is not necessarily recorded be­

cause only the baptisms performed in Columbus are noted.

Hence, children dying prior to baptism are not recorded.

Children who were not baptized or were baptized in

another church also are not noted; this is an important

source of underreporting because some families practice

the custom of taking the child to Greece to be baptized, particularly if the parent was an immigrant and his parents remained in Greece. The death records also under­ report actual deaths of community members. The death

records note only those funerals which were attended by the parish priest. Thus, data may be missing if the

individual died and was buried elsewhere.

The United States decennial census is also incom­ plete. The failure of census takers to correctly

enumerate immigrant populations has been noted by Parsons

(1975). In addition, the census only counts foreign born and native bora of mixed or foreign parentage. This practice excludes from consideration grandchildren of immigrants even if these grandchildren are entirely des­

cended from persons of Greek ancestry. Further, this census only counts persons living in the city every tenth year; children who died prior to the age of ten and persons who have entered and left the city within that period may not be detected. The major source of reporting error from the

scheduled interviews is called age or digit preference.

This error, discussed both in demographic and anthropo­

logical literature, is the tendency to assign individuals

to ages ending in a particular digit (Petersen 1975 and

Y/eiss 1973). The most common digit preference is for

years ending in 5 or 0; this is particularly true for

individuals whose actual age is unknown and who are

placed in the nearest likely category. Because this

digit preference was found in my reported data, the cor­

rection suggested by Y/eiss (1973) was performed. He noted that correction for age preference can be made by

pooling the data into 5 year classes with only one pre­

ferred age in each class. Other sources of reporting

error common in other anthropological studies (e.g.

investigator's heaping females into fertile age classes)

were not significant in this investigation because of the

different nature of the population.

Following the method of Cox (1970) I could estimate

the quality of the data obtained in the scheduled inter­

views by comparing the data with the census data. In

general, conflicts between the official sources and the

interviews were minor. The one exception was that of

mortality. My interview data provided considerably less

data on the number of deaths in the community than were 115

reported in the parish records. Because the parish

record listed the marriage status of the deceased indi­

vidual, I could determine that the bias in the interviews

resulted from a low enumeration of single males who had

died. This discrepancy is dealt with in the following

chapter. Other inconsistencies were only of a minor

nature and, in general, the data fit well.

Errors in coding were reduced by the keypunchers'

practice of double checking the punched cards after they

are completed. In addition, I checked the written For­

tran sheets with the computer printout. Checks were also

made for errors in the original coding by observing for

obviously incongruous data (males having miscarriages)

and by checking all data falling at extreme ends. These

errors were found to be quite uncommon.

Methods of Analysis

Demographic data obtained from the structured inter­

view's were transferred in coded form to computer cards,

one per individual. Information was coded on a total of

1,286 individuals in the Columbus Greek community, in­

cluding deceased persons, immigrants and emigrants.

Three computer programs, all in Fortran IV, were utilized in organizing the data: 116

1. A modified version of "the program developed by Keyfitz and Flieger (1971) was used to con­ struct life tables.

2. An aggregation program was developed indepen­ dently to elicit the following information from the data: age and sex distribution by 1, 5 and 10 year periods; total population figures; male and female births by age of mother, by age of father, and by differences in parental ages; and date of immigrant entry into the population.

3. The Ohio State IBM Sort-and-Merge Program.

The first two programs were tested for validity and

are located in Appendix G and ,'H because of their cumber­

some nature. The third program is a standard one and had been pretested for validity, hence no such tests were performed on it. All programs were used with an IBM 790

computer.

Most data were analyzed by decades in determining

trends. However, fertility measures were combined in 20

year generation periods. Although there is inevitable

generation overlap when using these temporal periods,

Lasker (1964) holds that this problem is subordinate to

the total analytical value of the generational model.

The organized data allowed the reconstruction of migration, fertility, mortality and mate selection pat­

terns which will be presented in the following chapter. Summary

In this chapter the conduct of the research was presented. The methods of data analysis and the variety of data collecting techniques used in this study (in­ cluding structured interviews, participant observation and record review) were discussed, finally, sources of error and confounding variables were identified. CHAPTER VI

RESULTS

Population Structure and Movement

Age and Sex Distribution

The combined effects of the vital rates of births, deaths and migrations in a population result in a certain age and sex composition, called the population structure.

The age and sex composition of the Greek community was determined through analysis of the data obtained in the structured interview's. The numbers of persons of each sex were grouped into age cohorts of five year spans to obtain the age-sex structure of the population for the first year of each decade, beginning in 1910. Tables

5 through 12 present the numbers and corresponding per­ centages for each age cohort of males and females and for the total population for the first year of each decade and for 1976.

Three major trends are discernible from these tables. First, the population is getting older. This

118 Table 5 -— Age distribution table: 1910, N = 48.

# OF TOTAL m a l e s FEMALES POPULATION AGE MALES FEMALES # 1° OF COHORT

0-4 4 3 8.3 6.6 14.9 5-9 ' 2 1 4.2 2.1 6.3 10-14 1 3 2.1 6.6 8.7 15-19 2 4 4.2 8.3 12.5 20-24 12 1 25.0 2.1 27.1 25-29 3 0 6.6 0 6.6 30-34 9 1 18.75 2.1 20.8 35-39 0 0 0 0 0 40-44 0 1 0. 2.1 2.1 44-49 1 0 2.1 0 2.1

Total 34 14 70.1# 29.9# Table 6 — Age distribution table: 1920, N = 157.

io OF TOTAL MALES FEMALES POPULATION AGE MALES FEMALES % % OF COHORT

0-4 25 19 15.9 12.1 28.0 5-9 15 8 9.6 5.1 14.7 10-14 5 4 3.2 2.5 5.7 15-19 3 5 1.9 3.2 5.1 20-24 3 12 1.9 7.6 9.5 25-29 10 6 6.4 3.8 10.2 30-34 20 6 12.7 3.8 16.5 35-39 5 0 3.2 0 3.2 40-44 10 1 6.4 0.6 7.0 45-49 1 0 0.6 0 0.6 50-54 0 1 0 0.6 0.6 55-59 1 0 0.6 0 0.6

Total 98 59 62.4$ 37.6% Table 7 — Age distribution table: 1930, N = 262.

1o OF TOTAL MALES FEMALES POPULATION AGE MALES FEMALES ' °/o % OF COHORT

0-4 15 19 5.7 7.3 13.0 5-9 24 18 9.2 6.9 16.1 10-14 25 20 9.5 7.6 17.1 15-19 19 8 7.3 3.1 10.4 20-24 7 8 2.7 3.1 5.8 25-29 4 9 1.5 3.4 4.9 30-34 7 13 2.7 5.0 7.7 35-39 11 8 4.2 3.1 7.3 40-44 21 7 8.0 2.7 10.7 45-49 5 0 1.9 07 1.9 50-54 10 1 3.8 0.4 4.2 55-59 3 0 1.1 0 1.1 60-64 0 1 0 0.4 0.4

Total 151 111 57.6# 42.4$ 121 Table 8 — Age distribution table: 1940, N = 313.

$ OF TOTAL MALES FEMALES POPULATION AGE MALES FEMALES $ $ OF COHORT

0-4 22 17 7.0 5.4 12.4 5-9 9 10 2.9 3.2 6.1 10-14 15 19 4.8 6.1 10.9 15-19 25 21 8.0 . 6.7 14.7 20-24 25 22 8.0 7.0 15.0 25-29 22 8 7.0 2.6 9.6 30-34 7 13 2.2 4.2 6. 4 35-39 6 7 1.9 2.2 4.1 40-44 7 14 2.2 4.5 6.7 45-49 14 8 4.5 2.6 7.1 50-54 9 6 2.9 1.9 4.8 55-59 5 0 1.6 . 0 1.6 60-64 9 1 2.9 0.3 3.2 6 5-69 3 0 1.8 0 1.0 70-74 0 1 0 0.3 0.3

Total 178 135 56,9$ 43.1$ 122 Table 9 — Age distribution table: 1950, N = 454.

# OF TOTAL MALES FEMALES POPULATION AGE MALES FEMALES °/o OF COHORT

0-4 25 30 5.5 6.6 12.1 5-9 22 24 4.8 5.3 10.1 10-14 23 17 5.1 3.7 8.8 15-19 10 12 2.2 2.6 4.8 20-24 24 25 5.3 5.5 10.8 25-29 38 30 8.4 6.6 15.0 30-34 25 23 5.5 5.1 10.6 35-39 26 8 5.7 1.7 7.4 40-44 7 15 1.5 3.3 4.8 45-49 7 8 1.5 1.7 3.2 50-54 7 15 1.5 3.3 4.8 55-59 15 7 3.3 1.5 4.8 60-64 18 6 4.0 1.3 5.3 65-69 3 0 0.7 0 0.7 70-74 2 2 0.4 0.4 0.8 75-79 0 0 0 0 0 80+ 1 1 0i2 Oi 2 0.4

Total 253 201 55.7# 44.3# 123 Table 10 — Age distribution table: I960, N = 696.

1o OF TOTAL MALES FEMALES POPULATION AGE MALES FEMALES 1° OF COHORT

0-4 56 22 8.0 3.2 11.2 5-9 49 33 7.0 4.7 11.7 10-14 25 32 3.6 4.6 8.2 15-19 26 29 3.7 4.2 7.9 20-24 34 22 4.9 3.2 5.6 25-29 17 22 2.4 3.2 8.1 30-34 30 32 4.3 4.6 8.9 35-39 44 33 6.3 4.7 11.0 40-44 27 24 3.9 3.4 7.3 45-49 30 9 4.3 1.3 5.6 50-54 7 14 1.0 2.0 3.0 55-59 7 10 1.0 1.4 2.4 60-64 8 17 1.1 2.4 3.5 65-69 7 6 1.0 0.9 1.9 70-74 14 5 2.0 0.7 2.7 75-79 2 0 0.3. 0 0.3 80+ 2 1 0.3 0.14 0.44

Total 385 311 55. 37& 44.7/o Table 11 - Age distribution table: 1970, N = 950.

$ OP TOTAL MALES FEMALES POPULATION AGE MALES FEMALES $ % OF COHORT

0-4 58 15 6.1 1.6 7.7 5-9 36 26 3.8 2.7 6.5 10-14 61 23 6.4 2.4 8.8 15-19 50 41 5.3 4.3 9.6 20-24 30 51 3.2 5.4 8.6 25-29 43 34 4.5 4.1 8.6 30-34 41 28 4.3 2.9 7:2 35-39 27 33 2.8 3.5 6.3 40-44 33 34 3.5 3.6 7.1 45-49 46 34 4.8 3.6 8.4 50-54 26 27 2.7 2.8 5.5 55-59 29 11 3.1 1.2 4.5 60-64 8 15 0.8 1.6 2.4 65-69 8 10 0.8 1.0 1.8 70-74 8 16 0.8 1.7 2.5 75-79 2 5 0.2 0.5 0.7 804- 8 5 0.8 0.5 1.3

Total 514 436 54.1$ 45.9$ 125 Table 12 — - Age distribution table: 1976, N = 1072.

$ OP TOTAL MALES FEMALES POPULATION AGE MALES FEMALES $ $> OF COHORT

0-4 61 28 5.7 2.6 8.3 5-9 68 18 6.3 1.7 8.0 10-14 40 23 3.7 2.1 5.6 15-19 59 21 5.5 2.0 7.5 20-24 52 42 4.9 4.0 8.9 25-29 44 57 4.1 5.3 9.4 30-34 38 46 3.5 4.3 7.8 35-39 49 ' 28 4.6 2.6 7.2 40-44 33 34 3.1 3.2 6.3 45-49 29 30 2.7 2.8 5.5 50-54 48 41 4.5 3.8 8.3 55-59 28 32 2.6 3.0 5.6 60-64 26 11 2.4 1.0 3.4 65-69 12 15 1.1 1.4 2.5 70-74 8 12 0.7 1.1 1.8 75-79 6 17 0.6 1.6 2.2 80+ 7 9 0.7 0.8 1.5

Total 606 466 56.5$ 43. 5$ 126 127 aging of the population is further revealed by an exami­ nation of the median age:

year median age 1920 13 1930 17 1940 22 1950 26 I960 27 1970 28 1976 30

Second, the proportion of males is decreasing, although the overall percentage of males in the population is al­ ways over 50$. The total male sex ratio has decreased consistently from a high in 1910 of 70.1$ to a low in 1970 of 54.1$. finally, the population is becoming larger: during each decade the population size has increased.

The basis for these trends would seem to be the particular nature of the migration trends as will be seen in future analysis.

Figures 3 through 10 graphically depict the age-sex population structure of the Columbus Greek community for the first year of each decade and for 1976. The popula­ tion pyramids are generally the expansive type, charac­ terized by a broad base. The fact that the lower bars are relatively long indicates that the birth rate and migration rate result in a proportion of children suffi­ cient to maintain the population in the long run, if these children remain within the Greek community. 80+ 80+ 75-79 75-79 70-74 70-74 65-69 65-69 60-64 60-64 55-59 55-59 50-54 50-54 45-49 45-49 40-44 t 40-44 35-39 35-39 30-34 30-34 25-29 25-29 20-24 20-24 15-19 15-19 10-14 10-14 5-9 5-9

0t 4 0-4 To So 50 40 30 20 10 0 T O 20 30 40 50 60 70 MALES FEMALES

Columbus Greek community. Figure 3 — Population pyramid for the 1910 I— ro CO 80+ 80+ 75-79 75-79 70-74 70-74 65-69 65-69 60-64 60—64 55-59 55-59 50-54 50-54 45-49 45-49 40-44 40-44 35-39 35-39 30-34 30-34 25-29 25-29 20-24 20-24 15-19 15-19 10-14 10-14 5-9 5-9 0-4 0-4 7 0 60 50 40 30" 20 10 0 10 20 30 40 50 60 70

MALES FEMALES

Figure 4 — Population pyramid foj? the 1920 Columbus Greek community, H rv> vo 80+ 80+ 75-79 75-79 70-74 70-74 65-69 65-69 60-64 60-64 55-59 55-59 50-54 50-54 45-49 45-49 40-44 40-44 35-39 35-39 30-34 30-34 25-29 25-29 20-24 20-24 15-19 15-19 10-14 10-14 5-9 5-9 0-4 0-4 70 60 50 40 30 20 10 0 10 20 30 40 50 60 70

MALES FEMALES l Figure 5 — Population pyramid for the 1930 Columbus Greek community.

o 80+ 80+ 75-79 75-79 70-74 70-74 65-69 65-69 60-64 60-64 55-59 55-59 50-54 50-54 45-49 45-49 40-44 40-44 35-39 35-39 30-34 30-34 25-29 25-29 20-24 20-24 15-19 15-19 10-14 10-14 5-9 5-9 0-4 0-4 70 60 50 40 30 20 10 0 10 20 30 40 50 60" ~ W

MALES FEMALES

Figure 6 — Population pyramid for tjie 1940 Columbus Greek community. Uj H 80+ D 80+ 75-79 75-79 70-74 70-74 65-69 65-69 P 60-64 60-64 55-59 55-59 S. 1 50-54 50-54 45-49 45-49 40-44 40-44 35-39 35-39 30-34 30-34 25-29 25-29 20-24 20-24 15-19 15-19 10-1.4 10-14 5-9 5-9 0-4 0-4

70 60 50 40 30 20 10 0 10 20 30 40 50 "50 70"

MALES FEMALES

Figure 7 — Population pyramid for the 1950 Columbus Greek community. H u> no 80+ 80+ 75-79 75-79 70-74 70-74 65-69 65-69 60-64 60-64 55-59 55-59 50-54 50-54 45-49 45-49 40-44 40-44 35-39 35-39 30-34 30-34 25-29 25-29 20-24 20-24 15-19 15-19 10-14 10-14 5-9 5-9 0-4 0-4 70 60 50 40 30 20 10 0 10 20 30 40 50 60 70

MALES FEMALES

Figure 8 — Population pyramid for the I960 Columbus Greek community. H Lu Oj 80+ 80+ 75-79 75-79 70-74 70-74 65-69 65-69 60-64 60-64 55-59 55-59 50-54 50-54 45-49 45-49 40-44 40-44 35-39 35-39 30-34 C 30-34 25-29 25-29 20-24 20-24 15-19 15-19 10-14 10-14 5-9 5-9 0-4 0-4 .70 60 50 40 30 20 10 0 10 20 30 40 50 60 70

MALES FEMALES

Figure 9 — Population pyramid for the 1970 Columbus Greek community. H u> 4^ 75-79 75-79 70-74 70-74 65—69 65-69 60-64 60-64 55-59 55-59 50-54 50-54 45-49 45-49 40-44 40-44 35-39 35-39 30-34 30-34 25-29 25-29 20-24 20-24 15-19 15-19 10-14 10-14

60 50 40 30 20 10 0 10 2 0 30 40 50 60

MALES FEMALES

Figure 10 — Population pyramid for the 1976 Columbus Greek community. \-> Co v n 136

The same trends seen in Tables 5-12 are visually even clearer. Comparing the population pyramids, we can easily recognize that the total population size is in­ creasing and that older age categories are tending to have larger proportions of the population in them. The decreasing proportion of males in the population, however, is more evident from the tables.

The higher proportion of males in the population is partially a result of the migration pattern of the Greeks, as will be seen in the migration analysis. However, it is also partially a result of a high secondary sex ratio.

The sex ratio, it will be remembered, is the proportion of males to females X 100 at the time of birth. For the

Columbus Greek population, the total births are 447 males to 278 females, which results in a sex ratio of 160.7.

This compares to the 1966 United States Caucasian sex ratio of 105.3 and the 1966 Greek sex ratio of 106.8

(Keyfitz and Flieger 1972).

Although the Columbus Greek sex ratio is obviously higher than either the ratio for the Caucasian population of the United States or the population of Greece, it is not possible from simple inspection to determine if this difference is significant. This lack of certainty re­ sults from the fact that ratios for the United States and for Greece are determined from very large sample sizes. 137 Using Visaria's (1967) method, we can test to determine if the Columbus Greek sex ratio is significantly differ­

ent from the expected. According to Visaria, the 95$ confidence limits for sex ratios at birth are a function of the sample size and he calculated them as follows!

95$ confidence limits for Number of observed sex ratio at birth of: live births 104 107_____

100 155.0-70.0 159.7-72.1 1000 117.8-91.9 121.2-94.5 10000 108.2-100.0 111.3-102.9

Hence, with a high sex ratio of 107 there is a 95$ probability that the upper sex ratio limit will be 121.2 if the sample size is 1000 or that the upper limit would be 159.7 if the sample size is 100. Since my sample size

(725) falls between 100 and 1000, the upper limit of the

Columbus Greek secondary sex ratio should fall between

121.2 and 159.7 if it is to remain within the 95$ confi­ dence limits. However, the sex ratio for the Columbus

Greek population is 160.7 and thus falls outside the 95$ confidence limits. This indicates that even given the relatively small sample size, there is a significant deviation in the secondary sex ratio of the Columbus

Greek population.

In addition to the chance of sampling error (which is always a possibility unless the total population is examined), numerous other factors have been postulated 138 for deviations from expected secondary sex ratios. These other factors were briefly discussed in the theoretical chapter. I tested the most common hypotheses for second­ ary sex ratio deviations:

1. Probability of a male child increases with an increase in the difference between ages of -parents. For the total male births in the Columbus Greek population, the mean parental age difference (father's age minus mother's age) was 7.435S. For the total female births, the mean difference was 6.9606. Using student's t test,

I calculated that this difference was not significant at a .05 level (t value: 0.9325).

2. Probability of a male child increases with in­ creasing birth order. Using a Chi-square Goodness of Fit test, I found no evidence at a .05 level of significance to reject the null hypothesis that male births are inde- p pendent of birth order (X value: 7.14175).

3. Probability of a male child increases as the age of the father increases. This hypothesis was not supported at a .05 level of significance when subjected to the student's t test (t value: -0.69727).

4. Probability that younger females are more likely to have male children. I determined that the mean age of mothers of male children was less than the mean age of mothers of female children (27.19395 snd 28.07388 139 respectively). Using a student's t test, I determined that this was significant at the .05 level of confidence

(t value: -1.8922; the critical region was - -1.64; thus the data fell within the critical region).

In summary, the only hypothesis which was signifi­ cantly associated with the high male sex ratio was the probability that younger females are more likely to have male children.

Migration Analysis

Greek immigration into Columbus began in 1898 when the first Greek individual permanently settled in Frank­ lin County. Migrants into the Columbus community have come both from Greece and from other areas in the United

States. In correct demographic terminology, those per­ sons entering Columbus from Greece are called immigrants and those persons entering from other areas of the United

States are called in-migrants. These two groups will be considered both separately and in combination for analy­ tical purposes. When I am speaking of the two groups in combination, I shall use the term "migrant."

The total number of migrants into the Columbus

Greek community is depicted graphically by decade in

Figure 11. From this chart we can see that the total number of migrants increased from the last 19th century 140

,130 ' l 2 5 120 115 110 105 100 95 90 w 85 EH | 80 « __ g 75 s 70 o 65 Ph 60 w | 55 a 50 45 40 35 30 25 ,20 15' 10 5 0- efgiu 1901- 19I1- 19*21- 1931- 1941- 1951-1961- 900 1910 1920 1930 1940 1950 I960 1970

-e 11 __ Total migration into Columbus 1900-1970. 141 decade until a time close to 1920 when a downward trend began. This decrease was a result of the strict immi­ grant quota laws enacted in the second decade of this century. The downward trend ended during the 1930-40 decade because of the increase in immigration after World

War II and in-migration from other areas of the United

States. Total migration into the Columbus Greek commun­ ity has increased steadily through the decade 1960-70.

Differences by sex of the total number of migrants into the Columbus Greek community are depicted in Figure 12.

From this graph we can determine that male/female dif­ ferences have not been large; however, female peaks generally follow those of the males.

Figures 11 and 12 depict gross data concerning num­ ber of migrants entering Columbus. A more refined mea­ sure of migration is the migration rate, calculated as

total migration into Columbus Greek community.. mid-decade Columbus Greek community population

The rates of migration in and out of Columbus and the net migration rate are shown for each decade in Table 13.

Here we see that the pattern of migration into the Colum­ bus population is roughly the same as that depicted in

Figure 11 until the decade of the 1940's. Although the total number of migrants has increased with each success­ ive decade since 1940, the rate of migration into the males females

22 20

16

V 12 10

VO O rl in vo O rl in VO O H in vo O rl in vo O H in vo O H in vo O H its VO O H VO mo o o O H rl H H CM CVI CM CM ro r o m m ^ v j - ^ in in in in vo vo vo vo t"- E'­ oo cn cn cn cncn cn cr> cn cn cn cn cn.cn cn cn cn cn cn cn cn cn en cn cn cn cn cn cn cn cn

rl rl rH rH rH rl H rl rl rH rH rH rH rl rH rl H r ! rl rl rl rl rH rH rH rH rl H rl rH rH rH 142

Total migration into the Columbus Greek community by sex Table 13 — Total migration rate into the Columbus Greek community*.

RATE OE RATE OF NET DECADE MIGRATION.IK MIGRATION OUT MIGRATION

1891-1900 100# 0 +100#

1901-1910 94.3# 0 • + 94.3#

1911-1920 47.3 # 1 2 .3# + 45.0#

1921-1930 13.8# 4.0# + 9.8#

1931-1940 8.2# 3.1# + 5.1#

1941-1950 15.1# 4.0# + 11.1#

1951-1960 14.5# 1.0# + 13.5#

1961-1970 15.5# 1.5# + 14.0# 144

Columbus Greek community has remained close to 15$ since then. The reason that the rate has remained relatively constant even though the total number of migrants is in­ creasing is that the total population size has increased proportionately.

The rate of migration away from the Columbus Greek community (also seen in Table 13) has always been sub­ stantially lower than migration into the population.

However, it should be noted that the rate of out-migration is likely to have been underestimated since there was no method to detect total family units leaving Columbus.

Migrants, on the whole, have tended to be drawn from younger age categories. For the decades 1891-1930, the 5 year age cohort representing the major migrating group was that of the 15-19 year class. Since 1930, how­ ever, migrants in the 20-24 year class have predominated.

An interesting trend in the past six years has been an increase in the proportion of migrants over 40 years of age. I have interpreted this latter trend to be the result of established Greek families bringing their parents to live with or near them.

Total migration into the Columbus Greek community has been the result of the entry of two categories of migrants: immigrants from Greece and in-migrants of Greek descent born in other parts of the United States. A 145

comparison of these two groups is shown in Table 14. As seen in this table, the percentage of immigrants from

Greece was highest early in this century and it sharply decreased since 1920-30. Since that time, migrants into the Columbus Greek population have been drawn almost equally from Greece and from other areas of the United

States. When all years are combined, the total number of immigrants is considerably greater than the number of in-migrants (59.1$ and 40.9$ respectively).

The two categories also differ considerably in their male/female ratios. In-migrants are represented by nearly equal numbers of males and females, 99 and 94 or

51.3$ respectively. Immigrants from Greece, however, are much more heavily weighted by males: 164 males to 105 females, or 61.0$ and 39.0$ respectively. Thus, in terms of the Columbus data, it seems that within the United

States, males and females of Greek ancestry seem nearly equally mobile, while males from Greece are much more likely than females to immigrate.

Immigrants have not come equally from all parts of

Greece, figure 13 is a map of Greece indicating pro­ vinces and notable islands. Table 15 depicts the five major areas from which Greek immigrants have originated.

It shows that in every decade, the greatest number of immigrants come from the area of the Peloponnesus. 146 Table 14 — Comparison of in-migration to immigration.

IN-MIGRATION IMMIGRATION DECADE (from other U.S.) (from Greece) r # # # male female 1° male female /

1891-1900 0 0 0 3 0 100

1901-1910 0 0 0 29 6 100

1911-1920 0 1 2.0 28 21 98.0

1921-1930 9 3 38.7 9 10 61.3

1931-1940 3 7 41.7 9 5 58.3

1941-1950 19 14 54.1 18 10 49.5

1951-1960 23 27 57.5 22 15 42.5

1961-1970 28 34 49.2 32 32 50.8

1971-1976 17 8 45.5 14 16 54.5

Total 99 94 164 105

Total / for All years 40.9/ 59.1/o MAC tOONIA

Turkey

a c h a ia

Arcadia 'i arcolij '&}?

l a c Oh i a %

THE REGIONS OF GREECE 'RHO0HO3 Agean

50 M ilts

I- 1 Figure 13 — Map of Greece. ^ Table 15 — / immigration from 5 major areas in Greece.

DECADE PELOPONNESUS THESSALY SMERNA OTHERAITOLIA N to 1900 67.0 io 0 0 33.0/ 0 3

1901-1910 88.6/0 0 5.7 3.4 3.4 35

1911-1920 67.0 4.0 14.0 8.0 8.0 50

1921-1930 65.0 10.0 20.0 0.5 0 20

1931-1940 46.6 0 6.7 46.6 13.3 15

1941-1950 33.3 25.9 7.4 33.0 0 27

1951-1960 41.9 11.6 7.0 34.8 4.7 43

1961-1970 41.4 11.4 1.4 45.7 7.1 70

1971-1976 20.6 0 2.9 64.7 11.8 34 148 149 Further, when immigration data from all provinces and major islands are combined, as in Table 16, we see that two provinces in the Peloponnesus account for 45.8$ of the total Greek immigration into Columbus. Hence, there has been a definite selection in terms of geographic , areas of emigration. As a result, many families in Col­ umbus are related through persons living in Greece.

It is also interesting that the majority of immi­ grants came from rural areas of Greece. It has only been since 1950 that any appreciable immigration has origi­ nated from the urban areas of Athens or Seloniki. This, however, is consistent with the pattern of in-migration within Greece; movement has been very heavy only from the rural to the urban areas.

Carriage Patterns

Tlarital Status

The marital status by decade of birth of the indi­ vidual is depicted in Table 17 for males and Table 18 for females. The statuses are coded either according to the present condition of the individual or the condition at time of death.

Two major patterns emerge from an analysis of this data. First, in considering the data for persons born _ 150 Table- 16 — Total migration from provinces and major islands in Greece for period 1890-1976.

PROVINCE 1°

Chalkidike 5.7 Thrace 1.0 Illyria 0 Epiros 0.3 Thessaly 8.1 W. Lorkis 0.3 Phokis 0.3 Aitolia 6.1 A r k a m a n i a 0 Biotia 0 Attica (including Athens) 6.1 Euboia 1.7 Elis 1.7 Achaia 1.7 Peloponnessus - Argolis 2.0 Arcadia 26.3 Messinia 1.7 _Laconia (Sparta) 19.5 S m e m a 6.3 Crete 1.3 Rhodes 0.3 Samos 0.3 Chios 4.7 Corfu 0 Cepholonia 3.0 Limnos 1.0 Sporades 0 Agean 0.6 Cyclades 0.6 Karpathos 0.6 Ikaria 1.7 Table 17 — Male marital status by decade of birth.

DECADE OF c? twot t? MARRIED SEPARATED DIVORCED REMARRIED WIDOWED N dirtii SINGLE

1871-1830 11. 8/ 76.595 0 0 5.9/ 5.9 95 17 1881-1390 11.1 66.7 0 0 5.6 16.7 36 1891-1900 2.3 86.4 0 0 4.6 6.8 44 1901-1910 17.9 75.0 0 3.6 3.6 0 28 1911-1920 19.1 73.5 0 2.9 0 4.4 68 1921-1930 9.9 80.2 0 5.5 3.3 1.1 91 1931-1940 20.0 71.3 1.3 3.8 3.8 0 80 1941-1950 30.5 59.8 0 7.3 1.2 1.2 82 1951-1960 87.4 12.6 0 0 0 0 119 1961-1970 100.0 0 0 0 0 0 100 1971-1976 100.0 0 0 0 0 0 84

Total 548

Composite data on persons at least 37 years old:

13.795 75.8/o 0.295 3.0/ 3 .3/ 3.8/ 364 Table 18 — Female marital status by decade of birth.

DECADE OF qT,1f,r,, MARRIED SEPARATED DIVORCED REMARRIED WIDOWEDN BIETII SINGIE

1881-1890 0 10.0/ 0 0 10. 0/ 80.0/ 10 1891-1900 0 36.1 0 0 2.8 61.1 36 1901-1910 2.7 ' 37.8 0 0 5.4 54.1 37 1911-1920 7.3 65.6 0 0 1.8 25.5 55 1921-1930 2.6 77.9 0 9.1 1.3 9.1 77 1931-1940 3.2 81.0 1.6 6.3 4.8 3.2 63 1941-1950 14.6 79.2 0 6.3 0 1.0 96 1951-1960 62.2 36.5 0 1.4 0 0 74 1961-1970 100.0 0 0 0 0 0 42 1971-1976 100.0 0 0 0 0 0 30 Total 520 Composite data on persons at least 37 years old:

3.2/ 62.9/ : 0.495 3.9/ 3.2/ 26.5/ 278 152 153 prior to 1940, we find that many more males than females remain single (13.7$ for males; 3*2$ for females).

Further, the data concerning the number of single males is an underestimate because the total number of single males in the population is underenumerated as will be shown in the analysis of mortality.

Second, there is a higher percentage of females who are in a divorced, separated or v/idowed status than there are males in divorced, separated or widower status.

The slightly younger age at death of males is only a par­ tial answer to this disparity. More important is the practice for males to remarry and thus reenter the

"married" status. Seventeen males have remarried in con­ trast to only nine remarried females. This disparity is further heightened when we consider that there are many more females who are eligible to remarry.

Age at First Marriage

A summary of the data for the age at first marriage is shown by decade according to the year of birth of the individual in Table 19 for females and Table 20 for males.

Males in the Columbus Greek population have, on the average, married later than females in all time periods.

Only two women have married younger males, and the difference in their ages was not greater than 18 months. Table 19 — Age at first marriage for Columbus Greek females.

YEAR MEDIAN OF BIRTH NUMBER MEAN RANGE (MODE) < 2 TT.

1891-1900 34 21.33 14-34 21 27.28 5.22 (17)

1901-1910 36 25.22 15-62 23 131.89 11.48 (25)

1911-1920 50 23.78 14-47 21 51.03 7.14 (18)

1921-1930 71 23.38 16-40 22 21.75 4.66 (22)

1931-1940 56 23.41 18-37 21 19.63 4.43 (20)

1941-1950 81 22.52 15-33 22 9.88 3.14 (23)

1951-1960 25 19.96 17-24 19 4.21 2.05 (20)

1961-1970 0 0 0 0 0 0

1971-1976 0 0 0 0 0 0

H VJ1 -P* Table 20 — Age at first marriage for Columbus Greek males and differences in means between males and females.

YEAR MEDIAN DIFFERENCE IN OF BIRTH NUMBER MEAN RANGE (MODE) T 1 ^r MEANS (if - %)

1871-1880 13 34.77 17-42 35 37.86 6 .15 (35) 1881-1890 33 33.18 19-53 31 63.72 7.98 (31) 1891-1900 41 33.07 21-68 32 23.07 4.80 11.63

(33)\ — ' — * / 1901-1910 21 31.90 22-48 30 54.19 7.36 6.68

(40)> • v / 1911-1920 55 30.13 21-47 29 35.89 5.99 6.35 (30) 1921-1930 81 28.09 19-40 26 236.80 15.39 4.71

(25)\ ✓ / 1931-1940 60 28.17 20-39 28 18.21 4.27 4.76 (29) 1941-1950 47 25.09 19-31 23 16.25 4.32 2.57 (24) 1951-1960 13 21.54 19-25 20 25.6 5.06 1.58 (21) 1961-1970. .0 0 0 0 0 0 0 156

The difference in the mean age at marriage between males and females has decreased from the decade beginning

1901 to the decade beginning 1931 (a. mean age difference from 11.63 to 4.76). Persons born after 1940 were not considered in this calculation because they would ob­ viously bias the result; they would have an earlier mean age at marriage as many of them are still single).

The decreasing difference in mean age can be attri­ buted to a significant trend among the males toward ear­ lier ages at marriage. The mean age at first marriage for males was highest in the decade beginning 1871 and. steadily decreased through the decade ending in 1940

(mean ages were 34.77 and 28.17 respectively). By using the analysis of variance test, I determined that the downward trend in age at first marriage was significant for males at a .05 level (P statistic: 2.938). There was no significant trend discemable for the female popula­ tion (P statistic: 1.458).

Congruence in Spouses' Place of Origin

Data were available for a total of 371 persons in which the birthplace of both spouses was known. Table

21 compares the birthplaces of marriage partners by the decade of birth of the female partner. Table 21 — Place of birth: female and spouse by decade of female birth.

PERCENTAGES FEMALE BIRTHPLACE 1 1 1 2 2 2 3 3 3 t o t a : MALE BIRTHPLACE 1 2 3 1 2 3 1 2 3 #

1881-1890 0 0 0 0 0 0 0 11.0 89.0 9 1891-1900 0 0 0 0 0 2.8 0 11.0 ■ 86.2 36 1901-1910 0 0 18.3 0 0 8.3 2.8 0 81.0 36 1911-1920 17.6 12.0 17.6 2.0 9.8 9.8 0 0 31.4 51 1921-1930 32.4 14.1 2.8 18.3 8.5 7.0 1.4 1.4 14.1 71 1931-1940 20.0 16.7 3.3 10.0 16.7 18.3 3.3 3.3 8.3 60 1941-1950 25.6 15.9 8.5 6.1 3.7 7.3 4.9 2.4 25.6 82 1951-1960 38.5 3.8 11.5 7.7 7.7 0 15.4 0 15.4 26 1961-1976 0 0 0 0 0 0 0 0 0 0

Total 371

N = 75 40 30 27 26 31 12 6 124 371

Total fo 20.2 10.8 8.1 7.3 7.0 8.4 3.2 1.6 33.4 = 1001o 157 158

In all time periods, the most frequent pairing for marriage partners' birthplaces was "both from Greece"

(33.4$). This pairing was highest (89/0 in the first decade for which we have data (1881-1890) and decreases to a low (8.3$) in the decade beginning in 1931* With increased immigration, pairing has risen but has never again exceeded other ratios in a given decade.

The second most frequent pairing (20.2$) when all data are totalled is the one in which both spouses are born in Columbus. Because there was no female birth in

Columbus prior to the decade beginning in 1911, there obviously are no data prior to that date. This pairing has fluctuated from a low of 17.6$ in the first possible decade to a high of 38.5$ in the decade beginning in

1951, the one for which we have the latest data.

A total of 39.4$ of pairings occur between partners who do not have the same place of origin. These pairings are comprised of a total of 6 possible categories. Thus, there seems to be geographical endogamy in that persons born in Greece tend to marry mates from Greece, and per­ sons born in Columbus tend to marry mates from Columbus.

An interesting characteristic that was noted is that females from Greece less often (4.8$) married non-

Greeks than did males (16.5$). This will be reintroduced in the discussion. 159

Greek Ancestry Endogamy

Table 22 depicts matings of persons characterized as Pull, Mixed or Non-Greek by the decade of birth of the female spouse. Of the 376 marriages for which the an­

cestry of both spouses was known, a total of 278 or 73.9$ have been between persons both having Pull Greek ancestry.

This pairing reached a peak in the decade ending in 1910 and has steadily decreased since then to a low of 48.1$ in the decade of wife's birth ending in I960.

Among those members of the community of Pull or

Mixed ancestry who married Non-Greek spouses, the majo­ rity were male. Thus, males more often tended to marry out of the community than did females. This may suggest a lower submission of the males to the endogamous rule of the community; it may also reflect a lower proportion of eligible Pu.ll or Llixed Greek females.

Table 23 compares the data concerning congruence in spouse's place of birth with congruence in proportion

Greek. Again, marriages are arranged by decade according to the wife's birthyear. Prom Table 23 it is clear that the percentage of marriages of persons b o m in the same

geographical area is less than the proportion of mar­ riages in which both spouses have Pull Greek ancestry.

Tims, we may infer that cultural endogamy is a more im­ portant factor in selecting a mate than is geographical Table 22 — Mating in the Columbus Greek community by decade of female's birth

FEMALE'S FULL GREEK FULL GREEK FULL GREEK MIXED GREEK MIXED GREEK BIRTH X X X X X DECADE FULL GREEK MIXED GREEK NON GREEK MIXED GREEK NON GREEK N

1891-1900 88. 6# 11.4# 0 0 0 10

1901-1910 97.2 2.7 0 0 0 35

1911-1920 84.3 0 13.7 0 2.0 36

1921-1930 71.6 9.5 16.2 0 2.7 74

1931-1940 70.5 11.5 16.4 1.6 0 61

1941-1950 61.0 13.4 24.4 1.2 0 82

1951-1960 48.1 3.7 14.8 18.5 0 27

1961-1976 0 0 0 0 0 0 160 161 Table 23 — Comparison of ethnic vs. geographical endo- . gamy by decade of female's birth.

FEMALE1S f MARRIAGES WITH % MARRIAGES IN BIRTH CONGRUENCE IN WHICH BOTH ARE .DECADE PLACE OF ORIGIN FULL GREEK

1881-1890 89.0$ IOO.O76

1981-1900 86.0 89.0

1901-1910 81.0 97.0

1911-1920 58.8 84.0

1921-1930 55.0 71.6

1931-1940 44.7 70.5

1941-1950 54.9 61.0 162 propinquity of birth.

Fertility Patterns

Age of Menarche

Patterns of fertility are in part dependent upon the fecundity of the females of the population, which in turn is partly determined by the age of menarche. Table

24 summarizes the menarcheal data for 142 females for whom information was known. The mean ages at menarche were calculated according to the woman's year of birth and grouped by 20 year cohorts. Three females, one each from the first three cohorts, never began menstrual per­ iods. These females were excluded from calculation.

On the average, the age of menarche has occurred at increasingly earlier ages. Using analysis of variance,

I found that the decrease in the mean age of menarche was significant at the .05 level of confidence (F statistic:

17.593)- Only the first four cohorts were used in cal­ culating the mean age at menarche because many females in the fifth cohort have not yet reached the critical age period.

Tanner (1973) has described this same trend for fe­ males in general throughout the United States as a part of his secular growth trend. He attributes this decrease Table 24 — Age at raenarche of females in the Columbus Greek community.

FEMALE'S BIRTH MEAN AGE AT MEDIAN DECADE N MENARCHE (MODE) RANGE T 2 V*

1881-1900 9 14.78 14+ 13-16 .94 .97 (15)

1901-1920 20 13.75 13 12-17 2.62 1.62 (13)

1921-1940 50 12.4 12- 10-16 1.63 1.28 (12)

1941-1960 56 11.98 12- 10-16 1.69 1.3 (12)

1961-1970 7 12.14 12- 10-15 1.48 1.22 (12) 163 164 in mean age of menarche to better nutrition and social

conditions. Heterosis has also been postulated as a fac­

tor decreasing the age of menarche. Neither of these hypotheses were testable from my data, however.

Rates of Fertility

Table 25 compares the crude birth rate of women in

the Columbus Greek community with that of all women in

Columbus and all women in Ohio. The data are arranged by

decade according to the date of birth of the child. The

Columbus (total) and Ohio data were obtained from the

Division of Vital Statistics, Ohio Department of Health.

Because the health department listed the birth rate for

each year, I had to combine data for the decade and ob­ tain a mean for the ten year period. For the Greek popu­ lation, the total number of births in a ten year period was divided by the mid-decade population; the rate was then calculated/1000 population for consistency in com­ parison with the Columbus (total) and Ohio data.

The much higher crude birth rates of the Columbus

Greek population (sometimes 2-4 times that of the total

Columbus and Ohio populations) during the first three decades is primarily a reflection of the age distribution of the population. It will be remembered that the early

Greek community was a very young community. Hence, most 165 Table 25 — Crude "birth rates.

BIRTHS/1000 POPULATION

YEAR OP COLUMBUS GREEK ALL ALL BIRTH POPULATION COLUTffiUS OHIO

1901-1910 30.0 17.5 21.8

1911-1920 64.4 18.1 20.6

1921-1930 35.3 19.6 19.6

1931-1940 19.7 16.2 14.9

1941-1950 25.3 21.5 21.7 1951-1960 26.2 27.0 25.2

1961-1970 16.3 19.7 17.5

1971-1976 18.4 18.0 15.7 166 members of the communitj’’ were either in fertile years or were children. All three categories of populations demon­ strated a significant decrease during the decade begin­ ning in 1930, and this reflects the general trend in the

United States during the period of the depression. Since that time, the Columbus Greek population's birth rate has been lower than or nearly equal to that of the total

Columbus population. This is a reflection both of an increasingly older population as well as a decrease in actual fertility/women in the Columbus Greek community, as will be shown shortly.

Table 26 gives the fertility ratio (number of child­ ren aged 0-4/number of females over age 14) of the Colum­ bus Greek population by decade according to the year of birth of the child. The drastic fluctuation from a high ratio of 1428.6/1000 women for the decade beginning in

1901 to a low' ratio of 226/1000 women for the decade ending in 1970 is a reflection of the pattern of migra­ tion. In the first part of the century, the majority of women in the Columbus Greek community were of childbear­ ing age. A drastic decrease in this ratio occurred from the decade beginning 1901 through the decade ending in

1940. Since that time, there has been a much more gra­ dual decrease in the fertility ratio. 167 Table 26 — Fertility rates of women in the Columbus Greek community.

1900-1910 1428.6/1000 women

1911-1920 1230.4/1000 women

1921-1930 956.7/1000 women

1931-1940 325.5/1000 women

1941-1950 366.5/1000 women

1951-1960 398.2/1000 women

1961-1970 226.0/1000 women

1971-1976 228.3/1000 women 163 Age-specific birth, rates are shown in Table 27.

The data are organized by the decade of birth of the child to show the births by age of mother. From inspec­ tion of the table we see the trend toward an increase in the age of the mother. However, as these are only gross data and not standardized for differing numbers of women in each age cohort, this table will not be examined fur­ ther. We will now consider more accurate indicators of the fertility pattern.

Table 28 depicts the number of livebirths of 505 women for whom complete reproductive histories were known. These data were organized according to 20 year cohorts by the date of the female's birth. By inspection we see a consistent trend of decreasing number of live- births/female in each successive 20 year cohort. The mean number of livebirths decreased from a high of 3.98/ female in the cohort beginning in 1881 to a low of 2.27/ female in the cohort ending in 1940. In relation to this, the range has also decreased from 12 in the first cohort to 6 in the third cohort. Using analysis of variance,

I found that this decrease in number of livebirths was significant at the .05 level of confidence (F statistic:

19.325). Only the first three cohorts were used in the calculations because the fourth cohort has not completed their reproductive years. oo O0 -0 -O CTi CT> vn vn 4^ -P^ CD CD K) ro M H VJl M O VJ 1 o cn O CJ1 O VJ1 O vn O vn O VJ1 O vn O I I AGE OP t-3 + 1 1 1 1 1 1 1 I 1 1 » I I I I VD 4* COHORT 00 -4 -4 CTi vn vn 4* 4^» CD CD ro ro H h O' 4=» VD -P* VD VD 4=» VD -P> VD 4> vd -r> «) -r M 4^ 0) 1901- ro O OOO OO O OOO O H o ro ro o o o o 1910 -4

w H H H 1911- H- O O O O Co CT« O OO to o o o o 1920 o o o o o o cP & V) o ’ H H 1921- *< o o o o o o cn -4 Co o o o O 1930 p otl (D O H H 1931- H, o o o o o o o o o ro 4^ vn C D 0 0 o o o o o 1940 B o rP fcf (t> H ro to 1941- 4 o o o o o o O O ro H Co H O H O O O O 1950

cr\ ro 1951- o o o o o o O O O M VD vn Co -4 H O O O O 1960

M Vo CD 4=» 1961- o o o o o o O H O VJ1 U> H 4^ O Co O O O O 1970

P-* CT» VD H* vn ro 1971- o o o o o o o o o H -4 q> O CD o o o o 1976 Table 28 — Number of livebirths/female.

YEAR OF

MOTHER'S MEDIAN CM V BIRTH NMEAN (MODE) RANGE

1881-1900 53 3.98 3.5 0-12 6.25 2,5 (4)

1901-1920 90 2.53 2 0-7 2.79 1.67 (2)

1921-1940 135 2.27 2 0-6 1.79 1.34 (2)

1941-1960 164 .994 .5 0-4 1.25 1.12 (0)

1961-1976 63 ------170 171 The percentage of married viomen never having child­ ren, a rough indicator of sterility in the population, has remained relatively stable throughout the history of the population. In the first cohort, 5 of 46 married women (10.9$) had no children; in the second cohort, 11 of 87 married women (12.6$) had no children; and in the third cohort, 15 of 53 married women (11$) had no child­ ren. ,

In no case did an unmarried women give birth and raise the child within the Columbus Greek community.

Although very occasionally an unwed woman would leave

Columbus "for a certain time," in no case did the woman return with a child. Hence, the rate of illegitimacy, while impossible to measure accurately, appears to be exceptionally low.

Reproductive Wastage

Data concerning reproductive wastage were obtained during the structured interviews. Information concerning the number of miscarriages of 226 women is presented in

Table 29; information concerning the number of still­ births for 310 women is presented in Table 30. In both tables, the data is organized into four 20 year cohorts by the date of the woman's birth. The difference in the sample sizes of the women for miscarriages and Table 29 — Rate of miscarriage by year of mother's birth.

DECADE OF MEDIAN ^ 2 MOTHER'S BIRTH NMEAN (MODE) RANGE

1881-1900 26 .808 0 0-3 1.0415 1.021 (0)

1901-1920 43 .6977 0 0-6 1.42 1.19 (0)

1921-1940 66 .3485 0 0-3 .415 .644 (0)

1941-1960 91 .132 0 0-3 .282 .531 (0) 172 Table 30 — Rate of stillbirth by year of mother’s birth.

DECADE OE MOTHER'S MEDIAN BIRTH N MEAN (MODE) RANGE t 2 T

1881-1900 34 .412 0 0-2 .371 .61 (0 )

1901-1920 59 .153 0 0-2 .2005 .448 (0)

1921-1940 85 .071 0 0-1 . 0664 .258 (0)

1941-1960 132 .0227 0 0-1 .0224 .15 (0) 174 stillbirths is the result of children being able to re­

port the number of their mother’s stillbirths, although

they usually did not knov; if their mother had suffered

spontaneous abortions. Data on miscarriages categorized

as "unknown" were not used in calculations.

Both miscarriage and stillbirth rates have consis­

tently decreased in the Columbus Greek population since

the community was founded. In the first cohort (women

b o m 1881-1900) , 11 of a possible 26 (42.37°) women suf­

fered at least one miscarriage and 12 of a possible 34

(35*3?6) had at least one pregnancy that ended in still­ birth. This is in great contrast to the third cohort

in which only 7 of 91 women (7 .67°) had miscarriages and

3 of 132 (2 .376) had stillbirths.

An inspection of the mean rates of miscarriage and stillbirth also confirms this trend. Miscarriages have decreased from a mean in the first cohort of .81 to that of .13 in the third cohort. Stillbirths have like­ wise decreased from .41 to .0227* Using analysis of variance, I found that the decrease in both stillbirths and miscarriages was significant at a .05 level of confi­ dence (F statistics: 13*645 and 7*9156 respectively).

There were no induced abortions reported for the first cohort; in the second cohort one woman was re­ ported to have obtained at least one abortion (2.376 of 175 fecund females); in the third cohort, 4 women from a possible 61 (6.6$) had obtained at least one abortion, and 1 of 61 (1.6$) had obtained more than one; in the fourth cohort, whose reproductive history is not yet com­ plete, 3 of 83 women (3.6$) have obtained at least one abortion and 2 of 83 (2.4$) have had more than one.

Because of limited data, no trends are discemable.

Childsnacing

There are several methods available to observe childspacing. One important measure is the time between marriage and the birth of the first child. Table 31 presents data concerning this measure according to the decade of birth of the female spouse. In addition to noting the number of years of marriage prior to the birth of the first child, this table also gives the mean age of females at the birth of their first child. As presented in this table, the data show no discernible pattern which relates to the mother's decade of birth.

This table does, however, demonstrate two notable features of the Columbus Greek population. First, the time lag- between marriage and birth of the first child is relatively long (2.25 years' was the minimum mean and

4.37 years was the maximum mean). Second, the mean age of the woman at the birth of.her first child is far 176 Table 31 — Mean age at marriage and mean number of years before birth of first child by year of woman's birth.

MEAN # YEARS • MEAN AGE OF D E C A D E OF AFTER MARRIAGE M O T H E R AT Y/OMAN' S MEAN AGE AT BEFORE BIRTH BIRTH OF BIRTH MARRIAGE OF FIRST CHILD FIRST CHILD N

1881-1890 24.37 + 2.25 = 26.62 8

1891-1900 21.17 + 2.67 = 23.84 30

1901-1910 23.0 + 4.37 = 27.37 27

1911-1920 22.4 + 2.6 = 25.0 37

1921-1930 23.3 + 2.6 - 25.9 •60

1931-1940 22.8 + 3.4 = 26.2 46

1941-1950 21.6 + 3.1 — 24.7 58 177 beyond the mean age of menarche. Thus, the decrease in age of menarche will not significantly influence the fer­ tility of the women in this population.

I devised a second measure of childspacing which I call the Index of Birthing Years. It is calculated as

______number of children - 1______age of oldest child - age of youngest child for each woman. This index gives a measure of the rela­ tive compactness of years of actual childbearing for a female. The numerator is so devised to exclude women having only one child. If the total number of children remains constant, but the time span between oldest and youngest child increases, the ratio will decrease. If the time span between oldest and youngest child remains constant and the number of children increases, the ratio will increase. When the number of children for women of different cohorts is known, this can be an interesting and informative index.

The mean index was calculated for fertile females in the Columbus Greek population according to the decade of their births and is presented in Figure 14. Because we know that the mean number of children born to women in the Columbus Greek community has decreased, we would initially anticipate that the index may have also de­ creased for each cohort. However, by inspection we see 0.78

in vo in HO cncn H rH

(.46) ■M" in HO ■M" cn cn cn i—I rH i—I

cn cn cn rH O 'M' rH ro HrH ) (.4603)

421 (. HO on cm cncn rH rH rH

HO HCM cr.cn rH rH rH (.427)

YEAR OF MOTHER*S BIRTH OH HO cncn H H

HO C Pi O rH rH rH OO C n

HO rHrH oo cn oo oo oo oo (.3535) (.199)

Ho 0-00 rHI—I oo oo oo 20 35' 10

oiivh m m Figure 14 — Mean ratios of.Index of Birthing Years. 179 that the index has, in fact, increased. There has been a consistently rising trend within this population. The conclusion, then, is that the total years in which fe­ males have children has been considerably shortened since the first cohort, and that this decrease in childbirthing years has become increasingly shorter since that time.

Patterns of Birth Control

Table 32 depicts methods of birth control used by women in the Columbus Greek community, grouped according to the 20 year cohort of their birth. A number of inter­ esting features concerning the community are shown here.

The percentage of women in each cohort not using any measures of birth control has consistently decreased for

each 20 year cohort, and for the women born 1941-1960, only 10.3$ of the married v/omen are not using any mea­ sures of birth control.

The preferred method of birth control has changed through the years according to what is technologically available and community pattern. In Greece, the decision to use a birth control method is primarily the responsi­ bility of the male (by use of condom or v/ithdrawal).

This pattern was the one most prevalent for the first three cohorts (if birth control was used) but it has decreased for the fourth cohort and birth control pills H HH H al 3 — ehd o brh control birth of Methods — 32Table * VD v o V O 0 0 DECADE OP S •£> ro O 0 0 0 H t— 1 H H MOTHER'S I 1 | | c+ 1 1 1 1 CD H H H H BIRTH • ft VO VOVO VO O'* ro O pi tl 0 O 0 O 0 Pi <1 4 CD H- H 3 O Oil ►d L*J VJI VO H CD CO 4 * O S! Pi O • 3 CD Pi CD O P Pi CD H H vo VJI 0 1 O O'* ro 0 e •• NONE Oo 3 0 c+ ■£> H CT\ H ro 0 BIRTH CONTROL p • O• H ro H vo PILLS H c+ CD VJI H ro 0 O • ft • IUD 3* H VO vo 3 H- *Q 3 ro vo VJI 0 CD • • • RHYTHM CQ O'* VO VO

O Hj H r—1 ro 00 VJI 0 CONDOMS/ • • ft O' WITHDRAWAL H- CO VJI vo 4 c+ 3 - 0 -0 VJI 0 0 • • ft DIAPHRAGM 0 vo 3 c+ 4 0 -J vo 0 0 H • • STERILIZATION - 0 -J (FEMALE) 3* P P* ro 0 VO vo 0 =

0 ro ro VJI 0 - 0 ^ 1 0 0 UNKNOWN 3 • • • - 0 C O O'*

081 1 81 have become the method of choice.

An interesting characteristic was found when making this table: 20.6$ of the second cohort, 27.8$ of the third cohort, and 7.7$ of the fourth cohort reported that they did not use birth control methods because they were either sterile or subfecund (indicated by the fact that they had at least one child, but had tried without suc­ cess to have more).

Table 33 presents patterns in the method of infant feeding used by women in the Columbus Greek community, according to the mother's decade of birth. Although post partum lactation was not reported by any female as a method of birth control, it is so used in many cultures, and will be considered here for that reason. In this population, breast feeding has been the major method of infant feeding for women in each of the 20 year cohorts.

In addition, relatively few women who desired to breast feed were unable to do so (7.4$ of the entire 80 year group).

Mortality Patterns

Mortality Rates

Table 34 presents the crude death rate for the

Columbus Greek population by decades since the founding Table 33 — Methods of infant feeding by decade of mother's birth.

DECADE OF # WANTED BUT # STARTED WITH MOTHER'S io io UNABLE TO BREAST FEEDING, BIRTH N BREAST BOTTLE COMBINATION BREAST FEED DIDN'T LIKE IT

1881-1900 28 92.9 3.6 3.6 0 0

1901-1920 50 84.0 2.0 8.0 6.0 0

1921-1940 51 41.2 19.6 19.6 13.7 5.9

1941-1960 34 52.9 20.6 11.8 5.9 8.8

1961-1976 0 0 0 0 0 0

Total 163 65 .6 11.7 11.7 7.4 3.7 182 183

Table 34 — Crude death rates.

YEAR OF DEATH GREEKS COLUMBUS OHIO

1901-1910 0 14.4 13.2

1911-1920 3.8 15.1 13.8

1921-1930 2.7 13.9 11.7

1931-1940 3.4 13.6 10.9

1941-1950 4.6 12.6 10.9

1951-1960 4.0 9.9 9.9

1961-1970 3.5 9.0 9.4

1971-1976 3.6 8.9 9.4 of the community. It also compares these rates with those of Columbus (total) and Ohio. In general, these rates are exceptionally low. In part, the low rate results from the population being relatively young during most time periods. However, there is a source of error which contributes to this low rate. This error is the result of the underenumeration of single males in the

Columbus Greek population. I was able to determine this source of error by comparing my data on mortality with the church death records for selected years. For the decade in which the parish data seemed most complete

(1951-1960), I found a total mortality rate of 4.9 deaths/

1000 population. Because the marital status of the de­ ceased individual was listed in the parish records, I was able to determine that this error of underestimation is drawn almost entirely from the presence and death of undetected single males in the population. Because the parish records for all years were not available, I was not able to determine if this was a good estimate of error for all decades considered. However, I have no reason to believe that it is not.

Data concerning age-specific deaths are presented according to sex in Tables 35 and 36* These particular data are not very illuminating because of the nature of the migrant population: in the early years, there were OO Oo -3 -4 cn cn VI VI -r^ -t> Oo Oo IV IV H H VJI H o (-3 VI o VI O VI o VI o V o VI O VI 0 V 0 1 1 + 1 1 1 1 I 1 1 I 1 1 1 1 1 1 1 VD 4^ AGE & oo -4 -4 cn cn VJI VI 4^ Oo Oo IV rv H H H *=■ VD VD 4* VD 4^ VD -£» VD 4^ VD 4=* VO 4i> <0 1871- oo o o O O o o o o OOOO O O O O O O o 1880 v i

1881- t-J o , o O O o o o o O O O O O O OOOO o h -T . 1890 {« H (D 1891- o O O o o o o O O O O OO O O O O o Pi o 1900 ro s. 1901- J3* o o o O o o o o O O O O O O o O OO o 1910 cn o* :1911- - t o o o O o o o o O O o H O O o O O IV o . 1920 CM ro .1921- o o o O o H o o o O o O OO o H O ro H 1930

1931- o o o O o H H o H o o O O o H O O IV o 1940 \ 1941- o o H Oo -4 IV HH o HH O O o OOO o IV . 1950

1951- o o H rv IV VD o H o H O O O HO OO H o 1960

1961- H vn 4* 4=> IV o o rv o H H O o O O O ' O H H 1970 H oo 1971- VJI Oo tVOIVHHHlVl-'OOO o H O O o IV H 1976 al 3 — eae ets y age by deaths Female — 36lable 0 0 OO —0 -o cn cn VJ1 VJI 4=* 4=* O o OO ro IV) M H VJI HO VJI o VJI o VJI o VJI ' o VJI O VJI o VJI o VJI O 1 1 AGE + 1 1 1 1 l 1 1 1 1 1 1 i 1 i 1 VD 4 ^ CO -0 -VI cn cn VJI vn 4^ 4 i* Oo Oo ro IV) V-1 H 41* VD VD -f* vo 4 i* VD 4i» VD 41* VD 4 s* VD 4^ 1871- o o o o o o O o O OOO o OO O o O O 1880

1881- o o o o o o O o O O O O o O O O o O O 1890

1891- o o o o o o o o O OOO o o O o o O o 1900

1901- o o o o o o o o O OO O o o O o o O o 1910

1911- o o o o o o o o O O O O o o O o o H o 1920

1921- o o o o o o o o O O O O o o O o H O o 1930

1931- o o o o o o o o H O H H o o o o o O o 1940 1941- o o o o o o o H O O O O o o o o o O o 1950

1951- H o o H o H o O O o o o o o H O o 1960

1961- o M H to o ro o o o O O o o o o o O O o 1970 H 1971- cnOo o H o H o o o HH O O o o o o o o O 1976 187 no persons in the older age categories which were then available as a possible death. The mean age at death is presented in Table 37. Prom this we see that the mean age has consistently increased for each decade. Inter­ pretation of this table is also difficult, however. The increase in the mean age at death is probably a reflec­ tion of several of the following factors: an increasing­ ly older population (ultimately giving us deaths in older age categories), a decrease in infant mortality, in­ creased longevity from lower mortality during middles- cence. One notable feature of these tables, however, is that there is a greater proportion of male than female child deaths, even when the sex ratio difference is taken into consideration.

Another source of error must be considered when dealing with the mortality data. It is probable that children who died soon after birth, or perhaps within the first year of life, were remembered as stillbirths

(this especially seemed to be true if a sibling rather than the mother of the deceased infant was the person interviewed). The degree of error arising from this source, however, was impossible to accurately calculate.

The mortality information of prime importance to physical anthropologists usually concerns mortality which occurs prior to the reproductive years. This measure is 188

Table 37 — Mean age at death.

MEAN AGE MEAN AGE DECADE OF AT DEATH AT DEATH DEATH MALES N FEMALES N

1911-1920 12.3 3 2.0 1

1921-1930 19.5 4 7.0 1

1931-1940 34.1 7 38.0 3 1941-1950 53.8 20 51.0 1

1951-1960 57.3 18 57.5 6

1961-1970 64.2 22 66.2 5

Note: Stillbirths not counted. 189 used in the calculation of Crow's Index of Total Selec­

tion. Table 38 presents data concerning this index ac­

cording to the birthdate of the individual, grouped into

20 year cohorts (males and females being considered to-

gather and stillbirths being included). From an inspec­

tion of the table, we see that the percentage of each

cohort not reaching reproductive age (here calculated at

1 5 ) has decreased for each successive cohort.

Causes of Death

Because the parish records did not give cause of

death, the only source for this information was the

scheduled interviews. Tables 39 and 40 depict causes of

death by decade of birth for males and females respec­

tively. For both males and females, the leading causes

of death, in decreasing order of frequency, were as

follows:

1 . heart attack 2. cancer 3. accident 4. stroke 5. pneumonia 6. liver disease 7. diabetes 8. asthma 9. other These data seem to be fairly reliable indicators of

adult causes of death. However, during the interviews, I

found that childhood causes of death were often unknown Table 38 — $ of individuals who fail to survive to reproductive age.

f COHORT NOT SAMPLE SIZE SAMPLE SIZE REACHING AGE 15 BIRTHS & MIGRANTS BIRTHS & GENERATION BIRTHDATE BIRTHS (0-15 YEARS) BIRTHS MIGRANTS

I 1881-1900 Insufficient Data

II 1901-1920 90 113 18.9$ 15.095

III 1921-19.40 . 146 194 10.3 7.7

IV 1941-1960 261 334 3.4 2.7 * V 1960-1976 245 318 3.3 2.5

* not a 20 year cohort

Note: Stillbirths are included. Table 39 — Causes of death (when known) for males by year of birth.

M I— - 0 B YEAR OF s CANCER ATTACK HEART ACCIDENT STROKE LIVER DISEASE ASTHMA OTHER BIRTH N Ph DIABETES

1871-1880 11 72.7$ 9.196 9.1/ 0 9 .1/0 0 0 0 0 1881-1890 21 4.8 23.8 0 9.5 9.5 0 4.8 0 4.8 1891-1900 27 40.7 14.8 11.1 18.5 0 0 0 3.7 7.4 1901-1910 8 25.0 25.0 12.5 12.5 0 12.5 0 0 12.5 1911-1920 8 25.0 0 37.5 0 37.5 0 0 0 0 1921-1930 4 25.0 0 0 0 0 0 0 0 75.0 1931-1940 2 0 0 0 0 100.0 0 0 0 0 1941-1950 2 0 0 50.0 0 0 0 0 0 50.0 1951-1960 0 0 0 0 0 00 0 0 0 0 1961-1970 0 0 0 0 0 0 0 0 0 0 1971-1976 0 0 0 0 0 0 0 0 0 0

Total 83 41.0/ 1 4 .5/0 1 0 .8/0 9 .6/0 9.6/ 1.2/ 1.2/ 1 .2/0 10.8/ Table 40 — Causes of death (when known) for females by year of birth.

EH CO W M P h W CO EH EH O R «t w eg <4 O H O K W w « YEAR OF EH O « W 1 > CO <3 EH O EH H H CO EH BIRTH N gS! O «aJ CO f4 r n o

1881-1890 5 60.0/ 0 0 20.0/ 0 20.0/ 0 0 0 1891-1900 7 43.0 0 14.3 14. 3 0 0 14.3 14.3 0 1901-1910 4 75.0 25.0 0 0 0 0 0 0 0 1911-1920 3 33.3 0 33.3 0 33.3 0 0 0 0 1921-1930 0 0 0 0 0 0 0 0 0 0 1931-1940 1 0 100.0 0 0 0 0 0 0 0 1941-1950 0 0 0 0 0 0 0 0 0 0 1951-1960 0 0 0 0 0 0 0 0 0 0 1961-1970 0 0 0 0 0 0 0 0 0 0 1971-1976 0 0 0 0 0 0 0 0 0 0

Total 20 50.0/ 10. 0/ 10. 0/. 10. 0/ 5. 0/ 5.0/ 5.0/ 5.0/ 0 193 (25.9$). This error is compounded by the error previous­ ly discussed of categorizing early childhood deaths as stillbirths. Hence, this table is probably only useful when considering adult deaths.

Life Table

Using a modified version of the life table model

(LIFE) of Eeyfitz and Plieger (1971), I constructed an abridged, synthetic cohort life table for each sex and these are presented for the decade 1961-1970 in Tables

41 and 42. Briefly, each column in the table is des­ cribed as follows:

PP : the total population falling within the speci­ fied age category*

DD : the total number of deaths occurring within the specified age categoryt

Q(X) : the probability of dying for an individual of exact age x before reaching age x + n (n is 1 for the first age group, 4 for the second, and 5 for all remaining age categories up to age 80; the last age category includes all per­ sons over the age of 85).

L(X) : the number surviving to exact age x, out of 100,000 b o m . This is also the probability that a child just b o m will survive at least to exact age x, multiplied by 100,000 to re­ move the decimal.

D(X) : the number of individuals dying between ages x and x + n out of 100,000 b o m . This is also the probability that the child will die be­ tween the exact ages of x and x + n. 194 Table 41 — life table for Columbus Greek males.

AGE PP DD QUO l(x) DU) 11 (X)

0 99 1 0.010009 100000 1001 99086 1 399 1 0.009963 98999 986 393531 5 544 1 0.009149 98013 897 437822 10 539 1 0.009243 97116 898 483384 15 425 1 0.011714 96219 1127 478318 20 427 1 0.011641 95091 1107 472677 25 438 1 0.011357 93984 1067 267293 30 357 1 0.013960 92917 1297 461620 35 377 2 0.026188 91620 2399 452253 40 435 2 0.022715 89221 2027 440786 45 363 1 0.013724 87194 1197 433250 50 255 2 0.038732 85997- 3331 421927 55 164 1 0.029982 82667 2479 . 407147 60 117 1 0.042167 80188 3381 393221 65 124 2 0.078158 76807 6003 372187 70 100 6 0.262016 70804 18552 309195 75 85 5 0.257870 52252 13474 228756 80 28 5 0.624726 38778 24225 131922 85 8 1 1.000000 14552 14552 116418

AGE M(X) A (X) TT (X) R(X) E(x) e e QO

0 0.010101 0.087 7050737 0.0000 70.508 0.010101 1 0.002506 1.500 6951701 0.0000 70.220 0.002506 5 0.001838 2.500 6558171 0.0000 66.911 0.001838 10 0.001857 2.553 6070349 0.0161 62.506 0.001855 15 0.002356 2.539 5586965 0.0254 58.065 0.002353 20 0.002342 2.439 5108647 0.0000 53.724 0.002342 25 0.002284 2.537 4635970 0.0117 49.327 0.002283 30 0.002810 2.714 4168677 0.0149 44.864 0.002801 35 0.005305 2.563 3707058 0.0000 40.461 0.005305 40 0.004598 2.376 3254805 0.0000 36.480 0.004598 45 0.002762 2.727 2814020 0.0393 32.273 0.002755 50 0.007894 2.580 2380771 0.0400 27.684 0.007843 55 0.006087 2.504 1958845 0.0400 23.696 0.006098 60 0.008599 2.717 1551699 0.0288 19.351 0.008547 65 0.016129 3.026 1158478 . 0.0000 15.083 0.016129 70 0.060000 2.584 786292 0.0000 11.105 0.060000 75 0.053902 2.588 477097 0.0351 9.131 0.058824 80 0.183635 2.442 248341 0.0400 6.404 0.178571 85 0.057897 8.000 116418 0.0000 8.000 0.125000 Table .42 — life table for Columbus Greek females. 195

AGE PP DD Q(X) L(X) D(X) 11(X)

0 42 1 0.023316 100000 2332 97926 1 176 1 0.022409 97668 2189 385202 5 293 1 0.016920 95480 1616 473360 10 434 1 0.011452 93864 1075 466486 15 509 1 0.009776 92789 907 . 461676 20 ■ 432 1 0.011539 91882 1060 456851 25 337 1 0.014768 90322 1341 450834 30 310 1 0.015999 85481 1432 443789 35 374 I 0.013280 83049 1169 437257 40 356 i 0.012876 86880 1119 • 431648 45 308 i 0.016164 85761 1386 425470 50 241 i 0.020630 84375 1741 417714 55 179 1 0.027384 82634 2304 408352 60 185 3 0.077918 80330 6259 385976 65 163 1 0.029405 74071 2178 365753 70 99 3 0.143402 71893 10310 335645 75 49 2 0.197744’ 61583 11562' 281093 80 10 1 0.405863 50021 20302 ' 199838 35 8 1 1.000000 29720 29720 237756

AGE M(X) A(X) TT (X) R(X) E(X) IvlTiT (X )

0 0.023809 0.110 7162621 0.0000 71.626 0.023810 1 0.005682 1.500 7064696 0.0000 '72.333 0.005682 5 0.003413 2.500 6679494 0.0000 69.957 0.003413 10 0.002304 2.363 6206134 0.0000 66.118 0.002304 15 0.001965 2.496 5739648 0.0000 61.857 0.001965 20 0.002321 2.585 5277973 0.0291 57.443 0.002315 25 0.002975 2.558 4821123 0.0380 53.083 0.002967 30 0.003226 2.475 4370239 0.0000 48.841 0.003226 35 0.002674 2.444 3926501 0.0000 44.594 0.002674 40 0.002592 2.540 3489244 0.0069 40.162 0.002591 45 0.003258 2.593 3057597 0.0357 35.652 0.003247 50 0.004167 2.610 2632127 0.0400 31.196 0.004149 55 0.005643 2.908 2214413 0.0283 26.793 0.005587 60 0.016217 2.496 1806061 0.0000 22.433 0.016216 65 0.005955 2.357 1420085 0.0391 19.172 0.005952 70 0.030716 2.690 1054332 0.0400 14.665 0.030303 75 0.041132 2.680 718637 0.0400 11.670 0.040816 '30 0.101592 2.524 437594 0.0400 8.748 0.100000 35 0.053428' ' 8.000 '237756 0.0000' '8.000' '0.125000 196

LL(X) : the total years lived between ages x and x + n/100,000 bom.

M(X) : the age specific death rate for the interval x to x + n.

A(X) : the mean years lived in an interval by those dying during it.

TT(X) : the total years lived beyond age x/100,000 born.

R(X) : the increase from an annual cohort to the next as estimated from the observed age distribu­ tion by r = .1. Note: V/here the quantity is negative, the pro­ gram substitutes zero, and zero is also used in the first three age groups. Higher values indicate higher birth rates of that cohort.

E(X) : the expectation of life at age x. This is the average number of years lived subsequently to age x by those reaching age x.

I'ffi(X) : the observed age specific death rate for the interval x to x + n.

Keyfitz and Pleiger's LIFE program was developed for use in populations in which all age cohorts had a death rate greater than zero. As previously discussed, the Greek population had a low reported death rate and, as a result, some age cohorts did not have a death rate greater than zero. Thus, Keyfitz and Fleiger's program could not be used without modification.

Several modifications were tested: combining male and female data, setting M(X) equal to .01 if the death rate was zero; setting M(X) equal to .001 if the death rate was zero; and setting the value for MM(X) at .02. 197 The modified program which, was finally used seems to he the most satisfactory because it has the closest fit to the actual data. It instructs the computer to consider a decade as one year, and if no deaths occur in an age category to fabricate one death. The result of this modification is only a slight underestimation of life expectancy. Because there were more age categories in the female life table that had no deaths, the female life expectancy data are slightly more underestimated than that for the males. The computer program for this modi­ fied life table is presented in Appendix F. These life tables compare favorably with ones for Greece and the

United States found in Appendix I.

We can see by inspection, however, that the life expectancy values of the Columbus Greek population are more similar to the population of Greece than that of the United States in two respects: first, the difference between males and females is small in both the Columbus

Greek population (l.l years) and the population in

Greece (3.85 years) as compared to the United States

(7.24 years). Second, male life expectancy values are higher both in the populations from Greece and the Greek

Columbus community (70.65 and 70.5) than in the United

States population (66,98). Summary

The findings reported in this chapter describe the

demographic characteristics of the Columbus Greek popu­ lation, This information is important not only because it is new demographic data, but also because it will be used in the next chapter to examine the potential for microevolution within the Columbus Greek community. CHAPTER VII

DISCUSSION

One of the three major aims of this study was methodological: the development of a computer program for the determination of demographic characteristics in a specific population. This program is located in

Appendix G. The other two aims were substantive: to determine the population dynamics and history of the

Greek urban immigrant community of Columbus, Ohio, and secondly, to examine cultural influences on demographic vital rates and to elucidate how these rates govern the potential and operative microvevolution in one community.

By inference, it should then be possible to understand the cultural influences on the microevolution of a spe­ cific population.

Effects of Social and Cultural Factors

on the Population Structure

Social and cultural factors influence population structure through their effect on the demographic vital

199 200 rates of migration, mortality and fertility. Each of these rates and the cultural factors patterning them will be considered separately below.

Effect on Migration Patterns

Eor demographic purposes in anthropology, migration rate is an important parameter because it determines maximum gene flow. However, the age and sex composition of the migrant group are more significant than the gross rate in determining the population structure. In this respect, cultural characteristics of major interest are not only those which promote migration, but those which promote differential migration in terms of age and sex.

Nearly all early Greek immigrants to Columbus came seeking a higher standard of living than existed in

Greece. A sustained economic crisis in the late 19th and early 20th centuries prompted this emigration, In the early years, the high male/female sex ratio and the immigrants' age distribution were the result of the defi­ nite migratory selection preference for young males. For several reasons, listed below, it was young males who first migrated.

The pattern of inheritance in Greece has long been the equal distribution of the parents' property to all the children (Friedl 1962, 1963; Levy 1963). While daughters received their portion in the form of material

goods at the time of their marriage through the dowry

system, sons were legally entitled to equal portions of

farm and grazing lands. However, equal partition of the

family's farm resulted in land holdings too small to sup­

port a family. One solution to this problem was to send

"surplus sons" to other areas of the world, particularly

the United States. As levy (1963:121) described, "The

system of equal inheritance of property and villagers'

values associated with a preference for ... city life led

to a movement of young men out of the rural community."

Priedi (1962, 1963) found that among villagers the poten­

tial for satisfaction and prestige was greater in the

cities than in the villages. She noted that urban life

is preferred over village not because of an anticipated

increase in the standard of living, but because urban

life was perceived as more exciting and prestigious.

Thus, when sons left the village it was not banishment,

but an adventure.

The eldest son usually stayed in the village to

become the executor of the land when his father "retired,"

and the youngest son was given the responsibility of

caring for his parents in their old age (Peristiany 1966).

Consequently, the middle sons usually emigrated to the

United States. These young men were frequently sponsored 202

by a relative (often an uncle) from the same village.

In this way, persons from the same geographical area in

Greece were reunited in the United States. This pattern

of sponsorship, known as the "padrone system," is found

in various forms in other Mediterranean and Southeastern

European countries. However, the exploitation of young

Greek males did not seem to be as great as in other immi­

grant groups having this system of sponsorship, and the

sponsor did not achieve the political or social dominance

seen in the Italians and other such immigrant groups.

Because the Greek economy was depressed for several

decades, many young men also migrated to the United

States to better the economic condition of their families.

Large numbers of young Greek men sent the greater portion

of their earnings back to their families in Greece, not

only for the support of their families, but to contribute

to their sisters' dowries. In Greece, males tradition­

ally do not marry until all of their sisters have done

so, and an appropriate dowry was essential for a woman's

marriage. Thus, for males wishing to marry, it was in

their self-interest to contribute to their sisters' dow­

ries. In addition, the philotimo of the family and,

hence, of every member, was enhanced if the sister "mar­

ried well." 203 In some cases, the desire of young males to escape military service in the Turkish army was a factor pro­ moting migration. Less often, males emigrated to avoid conscription in the Greek army.

The shift from a highly male dominated migration flow toward one with increasing numbers of females reflec­ ted the lag period in which males became established in the United States. Only after they were financially secure did males bring their wives to the United States.

Women, in general, did not emigrate from Greece unaccom­ panied by males; they arrived after their fathers or for an arranged marriage. When a single Greek woman entered the Columbus community, she lived with a Greek family until her marriage.

This pattern of female isolation is typical in the villages of Greece (Campbell 1964). In order to protect the family's philotimo, male members guarded the chastity of the women. Females did not intermingle with males outside the family largely because of the endrope which would result from the loss of their virginity.

In addition, Greek women did not migrate to the

United States in search of jobs to supplement the family income as did some immigrant women, such as the Irish.

It is the duty of Greek males to provide for the women, and it is considered improper for women to work in 204 occupations outside the home. This emphasis on the woman's staying within the home results not only from the desire to protect the family from shame, but just as im­ portantly from the woman's realizing herself in marriage and motherhood. Campbell (1964) found that the highest and most enobling vocation to which a Greek woman can aspire is motherhood.

Migration into the urban area of Columbus was part of the general trend of Greek immigrants to settle in urban centers of the United States. This urban settle­ ment pattern was the result of several factors, including the high value placed on urban living, the desire to be with other members of the Greek community, the need for sending funds back to Greece, and the lack of available farmland in the United States by the time of Greek immi­ gration.

The decreased migrations from Greece, as well as from other parts of southeastern Europe, after 1920, re­ flect the social climate of the United States. Noting the infline of too many "undesirable" foreign elements, former immigrants feared for jobs and safety. More esta­ blished Americans pressured Congress to pass strict immi­ grant quota lav/s. The drastic drop in the rate of immi­ gration into Columbus after 1920 reflects these lav/s.

The increased migration in later years reflects the more 205 liberal refugee policy and the repeal of the national quota acts.

Effects on Patterns of Mortality

Cultural influences on the mortality pattern were less discemable than were the influences on migration.

In part, this is because the mortality data gathered were incomplete. The data reported were not sufficient to allow conclusions to be drawn concerning differential mortality for sex and age categories. However, some population patterns are detectable.

The age pattern of migration determined that the population would be "young" and continued immigration of a "young" population has contributed to a low death rate compared to the United States population in general. Al­ though immigrant populations usually have higher than

United States average mortality rates (Bullough and

Bullough 1972), the Greek population did not. Compared to the Polish Hill community of Pittsburgh, another urban immigrant population spanning approximately the same time period, the Greek community had only about one fourth to one half the deaths for any generational group (Crawford and Goldstein 1975). This lower mortality rate may be attributed to several factors. Members of the Columbus Greek 206 population reported that the community had a history of seeking good medical care. Early in the century, a Greek immigrant graduated from the Ohio State College of Medi­ cine. Greek immigrants who were unable to speak English were able to go to this physician and seek formal medical care. Prior to the arrival of this physician, the com­ munity utilized the services of an Albanian doctor fluent in Greek. Thus, the population did not experience the significant language problems of many immigrant groups seeking health care in a new country.

In addition, education and professional status are highly valued among the Greek people. As a result, the fear of the professional was not as great as among other immigrant groups (Clark 1970). Finally, the rapid upward mobility of the members of the community allowed them to afford formal medical care.

Patterns concerning causes of death are difficult to determine because of the dearth of usable data. One interesting feature was discovered, however, For the

Columbus Greek population, the four leading causes of death are, in descending order:

1. heart disease 2. cancer 3. accident 4. cerebrovascular disease.

Smith and Zopf (1976) list the leading causes of death for the entire population of the United States as follows

1. heart disease 2. cancer 3. cerebrovascular disease.

For the population of Greece, Smith and Zopf (1976) found the leading causes to be:

1. cancer 2. cerebrovascular disease 3. miscellaneous conditions.

The fact that heart disease is the most frequent cause of death for both the Columbus Greek population and the United States general population, and that it is not listed as any of the three leading causes of death for the population of Greece imply that life patterns and environment are important for the epidemiology of the

Columbus Greek community. While the data are too limited to allow conclusive statements, it is probable that the shift from a rural to an urban environment, and from in­ tensive farm life to more sedentary but tension intensive business occupations, contributed to the increase in coronary disease.

Effects on Fertility Patterns

Social and cultural factors have had many direct and indirect influences on fertility patterns of the

Columbus Greek community. The discussion of these fac­ tors will be facilitated by the use of the analytical 208 framework of Davis and Blake (1956) discussed at length in Chapter III.

The mean fertility rates for women of each twenty year cohort were smaller at all ages than were the mean rates for United States women in general (Petersen 1975).

Because European immigrant populations have historically tended to have higher fertility rates than resident

United States groups (Hutchinson 1956), the lower ferti­ lity rates found among women of the Columbus Greek com­ munity are especially notable.

Davis and Blake (1956) categorized factors influ­ encing fertility as intercourse, conception or gestation variables. For the Columbus Greek community, the most significant factors contributing to the decreased ferti­ lity rate seem to be those which affect conception. This differs from the patterns in Greece, where the most sig­ nificant factors are associated with gestation.

In both the European and Columbus Greek populations, the limitation of family size receives heavy emphasis.

Friedl (1958), Valisios (I960) and Blum and Blum (1965) have all noted the trend in Greece for smaller families which has been present since at least the turn of the century. In large part, this lower fertility has been viewed as the result of the desire of parents to provide adequately for their children and to have them educated 209 so they would achieve professional status (Friedl 1962,

1963). Tsoukalis (1976) has pointed out that the propen­ sity toward higher education in Greece can be considered as established fact. To support this position, he notes the readiness of poor peasant families to undergo great economic sacrifices to insure their childrens' higher education.

As discussed in Chapter IV, limitation of family size has long been important to Greek peasants. Safilios-

Rothchild (1969) found that in Greece, control of concep­ tion is primarily left to the male; if conception occurs, the female limits family size through abortion. Sup­ porting evidence comes from Blum and Blum (1965) who studied village women in Greece. They found that while birth control is an important concern among village women, knowledge of modern contraceptives is not evident, and induced abortion is the only method of birth control used by most village women.

While the desire to limit family size in order to adequately care for and educate the children is also seen in the Columbus Greek community, the method of limiting fertility has changed from control of gestation variables to control of conception variables. Bor the Columbus population born after the turn of the century, the major­ ity of women have practiced birth control. For the 210 groups b o m after 1941, the method of choice has been birth control pills.

Thus, while the primary aim of limiting family size to properly care for and educate the children has re­ mained the same for both the Columbus and European Greek populations, the means used to achieve this aim have changed. This trend may be seen as the result of in­ creased knowledge and availability of contraceptive me­ thods for Columbus women. In addition, the increased independence and self-determination among Columbus Greek women also means that wives more often have the oppor­ tunity to determine when pregnancy will occur.

Because of the emphasis on family planning within the Greek community, variables which otherwise might have served to limit the number of offspring probably have had little effect on the total fertility rates. For example, late marriage is a prominent factor in limiting family size in many populations where little or no birth con­ trol measures are used, such as the Amish (Cross and

McKusick 1970) or the Alpine Swiss (Friedl and Ellis

1976).

Periods of imposed celibacy are also unlikely influences on fertility rates. Priests, but not bishops and higher church officials, are allowed to marry and have children. However, because there is only one priest 211 and no bishop in the community, this pattern has not affected the fertility rate. In addition, ritual times of abstinence such as the forty day post-partum period, and religious fasting days are relatively few, so that within the period of a year, these would not importantly affect the number of a woman's fertile days.

In many societies, the significant lowering of the age of menarche found in the Columbus Greek community might have increased the fertility rate of the popula­ tion. However, because the age of the mother when the first child was b o m is considerably greater than the age of menarche, this biological trend had no discemable effect on fertility patterns of the Greek community.

One factor which may have influenced the low ferti­ lity rate was the customary pattern of celibacy for those persons (particularly women) who had not married. Be­ cause of the loss of philotimo which would occur for the family if an unmarried woman became pregnant, daughters were carefully chaperoned ■until they were wed. The higher than average number of unmarried males (compared to the United States average), resulting from the lack of a suitable partner, may also have contributed to the lower number of children within the community.

In summary, it is most likely that the conscious parental desire to limit family size contributed most 212

significantly to the lowered fertility rate.

Effect ' on Mate Selection

The proportion of single males in the Columbus

Greek community was higher than the proportion for fe­ males in every decade by date of birth. This follows the

general historical trend in Greece. For example, Hajnal

(19^5) found that for Greece in 1965, 9$ of the males,

but only 4$ of the females, in the age group 45-49 had never married. Two reasons for this pattern in Greece

are the higher male sex ratio, which can account for 1$

difference, but more importantly, the much stronger

social pressure on females to marry.

In the Columbus Greek population, the proportion

of males born in the decade beginning in 1921 who re­ mained single (20.1$) was higher than the United States

average (15.4$). In contrast to this, a lower proportion

of Greek females (7.3$) than United States females in

general (13.4$) remained single (Smith and Zopf 1976).

This pattern has been consistent for all age groups.

Thus, the number of males of Greek heritage remaining

single has always been higher than the national average,

while the number of females remaining single has been lower than the national average. 213

Several social factors are implicated in this pat­ tern. First, it is necessary for a male to defer mar­ riage until he is able to establish an independent liveli­ hood adequate to support a family. In addition, for immigrant males with unwed sisters in Greece, their need to provide their sisters' dowries further deferred their age of marriage. Another important factor cited by near­ ly all eligible single males that were interviewed was the lack of a suitable spouse. These men usually desired a wife of Orthodox religion and Greek heritage. While there have always been fewer Greek females in Columbus than males, this differential was highest in the early decades of the Columbus Greek community.

Although these factors cannot be wholly separated, there is a distinction between the desire for a spouse

of the Greek Orthodox faith and a spouse of Greek heri­ tage. For the first generation of immigrants, the latter

seemed to be the most important factor in selecting a marriage partner, but members of more recent generations

seem more willing to accept a non-Greek than a non-

Orthodox spouse. In general, however, the belief in the

common cultural heritage, strengthened by common tradi­ tion, language and religion, has constituted a barrier to

exogamy. 214

For females, a trend was not discemable for age at first marriage; for males, however, there was a signi­ ficant decrease in the mean age at first marriage. While this pattern parallels the general trend in the United

States, it is exagerrated for males. For example, the

United States median age at marriage for males has dropped from 26.1 to 20.3 during the period 1890-1950

(Smith and Zopf 1976), while in that same time period, the median age at marriage for Columbus Greek males has dropped from 31 to 23.

In addition to factors operating in the general

United States population, social changes in the Columbus

Greek community have contributed to the lower male age at marriage. The upwardly mobile occupational trend within the Columbus Greek community has allowed males to obtain well-paying jobs at earlier ages than in previous genera­ tions. In addition, males have fewer financial obliga­ tions to their family of orientation because the dowry system is almost extinct and parents are financially more secure in their retirement years.

A high proportion of the marriages in all decades were endogamous both for place of birth and for propor­ tion of Greek ancestry. However, the data indicated that endogamy for ethnic heritage was a more important factor in selecting a mate than was geographical propinquity of 215 birth. An additional finding is that males tended more often to marry persons from a different geographical region than did females (16.5$ and 4.8$ respectively).

In part, this reflects the higher proportion of Greek males present in this country, but it is also consistent with the circum-ftiediterranean value system which allows males greater social freedom.

Microevolutionary Implications

of the Changing Population Structure

The microevolutionary forces of natural selection, genetic drift, gene flow and mutation determine the gene­ tic composition of a population. The first three of these microevolutionary forces are discernible from demo­ graphic data. In this section.vital rates, as determined in Chapter VI, will be utilized to infer the pattern and extent of microevolutionary forces operating in the Col­ umbus Greek community. These forces will be noted pri­ marily for the extant population, although historical trends will be discerned where possible.

Natural Selection

Natural selection is the evolutionary process through which gene frequencies are changed as the result of differences between individuals in Darwinian fitness. 216

It occurs through the differential transmission of genes to the succeeding generation. This variance in trans­ mission may result either from differential fertility or differential mortality.

Crow (1958) devised an index which examines the maximum amount of selection which can occur through dif­ ferential mortality and fertility. This Index of Total

Selection is a measure of the maximum amount of evolution by selection that could occur in a population each gener­ ation. It also indicates whether differential fertility or mortality is the more important variable in the deter­ mination of the selection potential.

The index of selection potential from differential mortality (lm ) is given as

where p-, is the probability of death prior to reproduc­ tive age p is the probability of surviving from birth to reproductive age.

I for the Columbus Greek generations is shown in Table

43.

The component from differential fertility is calcu­ lated as

2 where is the variance in the offspring of the sur­ vivors 217

Table 43 — Selection potential from differential mor­ tality (lm) for Columbus Greek population.

GENERATION BIRTHDATE p a P s m

I 1881-1900 Insufficient data

II 1901-1920 .189 .811 .233

III 1921-1940 .103 .897 .115

IV 1941-1960 .034 .966 .035

V* 1961-1976 .033 .967 .034

* not a 20 year cohort 218 — 2 X is the square of the mean. & for the Columbus Greek generations is shown in Table

44.

The Index of Total Selection (I) is given as

The Index of Total Selection for the Columbus Greek generations are given in Table 45.

for the Columbus Greek population, only two genera­ tions (II and III) have complete data for both the calcu­ lation of fertility and prereproductive mortality.

Crow's Index for Total Selection decreased from .771 for the generation b o m 1901-1920 to .503 for the generation b o m 1921-1940. This results from three factors: a de­ crease in the birth rate, a reduction in the variance in the number of children b o m to each woman, and a decrease in the probability of death prior to reproductive age.

This pattern is consistent with Kirk's (1968) finding that opportunity for selection has decreased in the

United States as a whole.

Spuhler (1962) postulated the existence of corre­ lations between Index of Total Selection and the techno­ logical and economic levels of human populations. He found trends for increased selection through differential fertility and decreased selection through prereproductive 219

Table 44 — Selection potential from differential fer­ tility (lf) for Columbus Greek population.

GENERATION BIRTHDATEbf S 2 * s2

I 1881-1900 6.25 15.84 .395

II 1901-1920 2.79 6.40 .436

III 1921-1940 1.79 5.15 .348 * IV 1941-1960 1.25 0.988 1.265 ■** V 1961-1976 __ __

* total reproductive history not yet complete

** insufficient data because of young age; also not a 20 year cohort 220

Table 45 — Index of Total Selection for the Columbus Greek community.

GENERATION BIRTHDATE Im If \ P s ) \ fJ 1

* I 1881-1900 .395 — —

II 1901-1920 .233 .436 .536 .771

III 1921-1940 .115 .348 .338 .503

IV 1941-1960 .034 1.265 1.31 1.344 V 1961-1976 ****

* insufficient data 221 mortality in populations having increasing levels of technology. The Columbus Greek data is consistent with

Spuhler's hypothesis. In addition, the selection poten­ tial from differential mortality was lower for all gener­ ations than was the selection potential from differential fertility.

In samples from 64 populations, Spuhler (1973) found empirical values of I ranging from a minimum value of 0.23 to a maximum of 3.69. Table 46 compares Crow's

Index for the Columbus Greek population with Indices calculated for other populations.

Comparing the Index for Total Selection for the

Columbus Greek population and that of Polish Hill (Craw­ ford and Goldstein 1975) demonstrates the necessity for more population studies before generalizations can be made. Both populations are urban immigrant populations which span approximately the same time period. However, the selection potential is considerably different for corresponding generations in the two populations, as can be seen in table 47.

Both populations demonstrate the pattern of de­ creasing Im , I^, and, consequently, total selection.

However, the potential for selection in the Polish Hill community is greater at all times than in the Columbus Greek community. This greater selection potential among 222 Table 46 — Tlie Index of Total Selection for various human nonulations.

POPULATIONPERIOD 1™m *f

Columbus Greeks 1976 .115 .348 .503 Hutterites (Spuhler 1976) 1950 .053 .167 .229 Xavante (Spuhler 1976) 1964 .493 .168 .743

Polish Hill CO r- (Crawford and 1969 .14 • 1.03 Goldstein 1975)

Tlaxcala (Halberstein and 1970 .59 .35 1.14 Crawford 1972)

U.S. Nonwhite (Spuhler 1976) 1964 .050 1.410 1.460 Cuanalan, Mexico 1972 1.47 .28 2.16 (Halberstein 1 223 Table 47 — A comparison of Crow's Index of_Selection between the Pittsburgh Polish Hill and the Columbus Greek communities.

POLISH HILL COLUMBUS GREEK

GENERATION: 1906-1925 1926-1945 1901-1920 1921-1941

1.33 0.14 0.23 0.12

0.89 0.78 0.46 0.35

IT: 3.39 1.03 0.77 0. 50 224 the Polish Hill immigrants is the result of their greater prereproductive mortality as well as their greater mean and variance in number of offspring.

In summary, the demographic characteristics of the

Columbus Greek community suggest that natural selection could have operated at only a moderately low level com­ pared with other human populations. In addition, the necessity of learning more about the microevolutionary processes operating in ostensibly similar populations has been demonstrated.

Genetic Drift

Genetic drift results from random fluctuations in gene frequencies between generations as a consequence of sampling error. Meiosis and fertilization are the bio­ logical bases of random drift in gene frequencies. The two alleles occupying each autosomal locus in the ferti­ lized egg are a sample of the four genes at that locus in the two parents. In small populations, gene frequencies have a high probability of fluctuating from generation to generation because of this sampling process (Spuhler

1973). In small populations, the magnitude, but not the direction, of genetic drift is determinate. Lasker and

Kaplan (i960) devised a measure for estimating the 225 potential for drift to occur in a population. This mea­ sure, the coefficient of breeding isolation, is calcu­ lated by multiplying the effective size of the breeding population (N )'by the effective immigration rate. The smaller this index of isolation, the greater the likeli­ hood that random genetic drift has been a relevant micro- evolutionary force in that population.

Effective size of the breeding population: To calculate the effective size of the breeding population for the

Columbus Greek community, it was first necessary to cal­ culate the total breeding population (N). Following

Lasker and Kaplan (1964), N was determined for the Colum­ bus Greek population by counting all the persons within reproductive years (taken to be 19-44). Freire-Maia

(1974) estimated that N would represent roughly 357° of the total population. For the Columbus population, N was calculated as 423/1072 or 39-5$ of the population, a figure slightly higher than Freire-Maia's estimate.

Because a number of factors may bias the effective­ ness of this estimate, corrections of the breeding size may be made to find the effective breeding size (Ne).

For the Columbus Greek community, two corrections were necessary: one for differential fertility and the other for unequal numbers of sexes. 226

The correction for differential fertility is cal­ culated as N - 4N :-_2_ e “ ^ 2 + 2 k where W is the number of parents in the population 2 is the variance in the number of gametes con­ tributed to the next generation (Wright 1938).

The correction for unequal number of sexes was also determined by Wright (1938) and is given as

N 4NfNm

- npnq where N^. is the number of breeding females I\Tm is the number of breeding males.

When these corrections were made for the Columbus

Greek population, the effective breeding size of the popu­ lation was 304/1072 or 28.4$ of the population. Lasker estimates that the effective breeding size of a popula­ tion is about 29^ of the total population size. Thus, the Columbus data is quite close to Lasker’s estimate.

Calculation of genetic drift: After calculating the effective breeding size, it is possible to determine the potential for the magnitude of genetic drift by calcu­ lating the coefficient of breeding isolation by the method of Lasker and Kaplan (i960):

Dp = (I)(He) where D is the potential for genetic drift, given as the p coefficient of bre.eding isolation I is the effective immigration rate 227 is the effective size of the breeding popu­ lation.

For the Columbus Greek population, the effective size of the breeding population was calculated above as

304; the effective immigration rate taken from Table

13 is 14.2$. The product of these two variables is the coefficient of breeding isolation, a measure of the po­ tential for genetic drift in the population. For the

Columbus Greek population, this coefficient equals 43.2.

Lasker and Ivaplan (1964) postulate that genetic drift might be expected to have a considerable effect on the genetic mierodifferentiation of a population with a coefficient of 5 or less, but it would have little effect in a population with a coefficient greater than 50. The

Columbus Greek coefficient of 43.2 indicates that genetic drift may have a slight to moderate potential for differ­ entiating the population, but the effect was probably small.

For comparison with the Greek population of Colum­ bus, the coefficients of breeding isolation for several other populations are given in Table 48. From this table, the special importance of small population size in deter­ mining the potential for drift may be seen. 228

Table 48 — Coefficients of breeding isolation of various human populations.

COEFFICIENT OF BREEDING POPULATION POPULATION SIZE N e I ISOLATION

Columbus Greek 1072 304 14.276 43.2

Kippel, Switzerland 450 70 4.5# 5.84 (Priedl and Ellis 1973)

Dunkers, Pennsylvania 350 117 22.0# 25.7 (Lasker I960)

Cunalan, Mexico 2040 735 16.3# 119.8 (Halberstein 1974)

Dinka tribe 13,400 3909 11. 0# 430.0 (Roberts 1956)

Tlaxcala, Mexico 15,000 4350 18. 8# 815.63 (Halberstein and Crawford 1972) 229

Gene Flow

Gene flow refers to recurrent introduction of genes into a population by outbreeding (Spuhler 1959). As

Lasker (i960) aptly suggests, genetic drift and gene flow are two sides of the same coin because they reflect the converse but linked concepts of isolation and migration.

Lasker demonstrated that drift cannot be studied in iso­ lation because gene flow will stabilize the stochastic processes; that is, it will offset the effects of gene­ tic drift. Gene flow leads to an increase in the genetic variability within populations and a decrease in the genetic variability between populations; thus, gene flow tends to make populations more alike, as opposed to genetic drift, which tends to make populations more heterogenous.

Lamb (1975) has shown that gene flow may be mea­ sured by the degree of admixture occurring in a popula­ tion, which is calculated as follows:

number of immigrant spouses number of local b o m spouses in each generation.

As we would anticipate in a migrant population with a continuous inflow of immigrants, the rate of admixture

(and consequently gene flow) is high. In the first gener­ ation of the Columbus Greek community, the rate of gene flow was lOOfi because there were no available Columbus born spouses of Greek heritage living in the Greek com­

munity. After the community became established, and

the offpsring forming the second adult generation came of

marriageable age, the rate of admixture dropped rapidly.

Most recently, the rate of admixture for Columbus born

adults within the Greek community has decreased to ap­

proximately 50$. However, this figure underestimates the

potential gene flow for the next generation because it

does not count breeding couples who were married in

Greece. In the past 25 years, approximately 20$ of the

marriages in the Columbus Greek community have occurred

between persons both born in Greece. Thus, in a migrant

population, not only the admixture rate, but the total

marriage pattern must be considered because the children

of the marriage partners both born in Greece will contri­

bute to the gene pool in the next generation.

Inbreeding

A final concept to be discussed is not a mechanism

of microevolution, but it is important in population gene­

tics. This concept, inbreeding, is linked to the two

previously discussed concepts of genetic drift and gene

flow because it also reflects the extent of isolation, migration and admixture. 231

Consanguinity refers to a relationship between two

individuals sharing one or more common biological ances­

tors. Inbreeding is a genetic consequence of the mating

of consanguinous individuals, and, as such, is a depar-' ture from random mating. Inbreeding is important to the population anthropologist not because it induces changes

in the gene frequencies, but because it tends to increase the proportion of homozygotes. Thus, it allows rare recessive genes to become phenotypically more apparent.

In general, the isolation of a small population increases inbreeding levels, while the effect of gene flow is to decrease inbreeding levels. In other words, inbreeding is likely to occur most often in the same populations in which the probability for genetic drift is high and the amount of gene flow is low.

Two major methods are available for calculating the level of inbreeding. The first is through the use of isonymy (concordance of marital surnames), a method de­ veloped by Crow and Monge (1965). This approach esti­ mates total population inbreeding coefficients by mea­ suring the frequency of marriages between persons of identical surnames. Any increase over the randomly ex­ pected frequency of isonymous matings is viewed to result from consanguinous marriages. The observed value of the proportion of isonymous matings is divided by 4 to give 232 the inbreeding value for the population.

For the Columbus Greek population, there were four isonymous marriages. However, I determined from inter­ view data that none of the isonymous marriages occurred between consanguinous individuals. Thus, the use of isonymy to determine a coefficient of inbreeding in mi­ grant populations seems of doubtful value at best, and could be highly misleading.

A more accurate indicator of the level of inbreed­ ing within a migrant population comes from the analysis of consanguinity between marriage partners for whom pedi­ gree data is available. Malecot (1948) devised a measure of population inbreeding using pedigrees. With this method, the individual inbreeding coefficient (F) is cal­ culated for each member of the population; then the population coefficient of inbreeding (f) is calculated as the arithmetic mean of the individual inbreeding co­ efficients:

f•f —- i1? - — -jr 2- •

Each individual F is calculated on the basis of the fol­ lowing:

Relationship F Value first cousin 1/8 or 0.0625 second cousin 1/64 or 0.015625 second and -t cousin 1/128 or 0.00781 third cousin 1/256 or 0.00391 fourth cousin 1/1024 or 0.00098 233

For the Columbus Greek population, the following consan­ guinous marriages were reported from a total of 364 marriages:

Relationship Number of Marriages first cousin 0 second cousin 1 second and -g cousin 1 third cousin 3 fourth cousin 2

The sum of the individual F values divided by the number of marriages examined was .03314/364 = .000102.

Reid (1973) found no record of a human population in which the inbreeding coefficient is greater than 0.05, and he found that most human populations have inbreeding coefficients below 0.005. Table 49 compares the coeffi­ cient of inbreeding of the Columbus Greek population with those of other selected populations.

The Columbus Greek population falls within the same range as the general Catholic population within the

United States; both groups have religious proscriptions against marriages closer than third degree (second cou­ sin) (Freire-Maia 1969)• For the Columbus Catholic popu­ lation, however, Freire-Maia found the coefficient of inbreeding to be zero among 1237 marriages. Hence, while the Columbus Greek population has a coefficient of in- breeding within the range of that of the general popula­ tion of United States Catholics, the Greek population has 234 Table 49 — Inbreeding coefficients (f) of various human populations.

Populations vd-th f 0.00001

Netherlands (Reid 1973) Panama (Friere-Maia 1968) Roman Catholic, Columbus Ohio (Friere-Maia 1963)

Populations with f between 0.00001 and 0.0001

U.S. Roman Catholic (Friere-Maia 1968) Greek Orthodox, Columbus Ohio (this study)

Populations with f between 0.0001 and 0.001

French Canadians (Freire-Maia 1968) Roman Catholic, Cuba (Freire-Maia 1968)

Populations with f between 0.001 and 0.01

Mormons, United States (Reid 1973) Ramah Navajo (Reid 1973)

Populations with f between 0.01 and 0.03

Hutterites, United'States (Mange 1964) Dunkers, Pennsylvania (Glass 1952) a greater coefficient of inbreeding than among Columbus

Catholics. However, this level of inbreeding is far less than that for other religious isolates in the United

States such as Dunkers, Hutterites and Mormons.

It is also possible that the coefficient of in- breeding was slightly underestimated for the Columbus

Greek population because many individuals had ancestors from the same geographical region of Greece. Usually, pedigree information for these ancestors was not avail­ able. However, the degree of relationship between mar­ riage partners would probably not be closer than 4th cousin, and the P value for that level of consanguinity is very low. Hence, this additional inbreeding would have little effect on the total "f" value of the popula­ tion.

Summary

In this chapter I examined the effects of social and cultural factors on the vital rates and found them to be important. In addition, I discussed microevolu­ tionary implications of the historical changes in the population structure of the Columbus Greek community. CHAPTER VIII

SUMMARY AND CONCLUSIONS

Findings of the Study

The three substantive aims of this study were to describe the demographic characteristics of a specific urban Greek immigrant community, to determine the poten­ tial for microevolution, and to examine by inference the ways in which cultural factors influence microevolution.

The findings of this study relevant to each of these three aims will be summarized separately below.

Demographic Characteristics of the Columbus Greek

Community Population Structure

1. The population is getting older: the median age has increased from 18 in 1920 to 30 in 1976.

2. The proportion of males in the population is greater than 50$ in all time periods, but this proportion has consistently decreased through time.

3. The population is becoming larger and there has been an increase in population size during each decade; this 236 237 increase is attributed both to births and continuous in-

migration.

4. The proportion of children is sufficiently large to

maintain the population if these children remain within

the Greek community.

Fertility Patterns:

1. Birth rates have decreased significantly and are now

low compared with national standards.

2. The rate of stillbirth and miscarriage has decreased

significantly; the abortion rate has remained low.

3. The rate of sterility has remained relatively con­

stant and is moderate (about 11% of marriages).

4. Family planning has been important since the begin­

ning of the century; the most frequently used methods

of birth control have changed with technological advances

in the field of planned parenthood. Presently, a major­

ity of women use birth control pills.

5. There is a significantly high secondary sex ratio,

the cause of which remained unknown.

6. The age of menarche has decreased significantly.

Mortality Patterns :

1. Death rates were low compared to the general United

States population, even accounting for incomplete data. 2. The mean age at death has consistently decreased for each 10 year cohort.

3. Prereproductive age mortality has decreased for each successive cohort.

4. life expectancy values of the Columbus Greek popula­ tion are more similar to the population of Greece than that of the United States in two respects: first, the difference between life expectancy of males and females is small in both the Columbus Greek population and the population in Greece as compared to the United States in general. Second, male life expectancy values are higher both in the populations from Greece and the Columbus

Greek community than in the United States general popu­ lation.

5. The three leading causes of death in descending order are heart attack, cancer and accident.

Migration:

1. Greek immigration into Columbus begain in 1898 and the rate increased until the early 1920's. The downward trend ended during the decade of the 1930's as a result of increased immigration to Columbus from the rest of the country, and also increased immigration as a result of relaxed immigration laws. 239

2. Migrants are drawn from the younger age categories.

For the decades 1891-1930, the 5 year cohort representing

the major migrating group was that of the 15-19 year

class; since 1930, migrants in the 20-24 year class have

predominated.

3. In-migrants are represented by nearly equal numbers

of males and females. However, there have been 50$ more

male than female immigrants from Greece.

4. The majority of immigrants into Columbus came from

the Peloponnesus, primarily from the provinces of Laconia

and Arcadia.

Marriage Patterns;

1. In considering data for persons born prior to 1940,

we find that many more males (13.7$) than females (3«2$)

remain single.

2. On the whole, males have married later than females

in all time periods. There has been a significant de­

crease in the mean age at marriage for males; there was no significant discernable trend for females.

3. Cultural endogamy had a higher correlation with mate

selection than did geographical propinquity of birth.

4. Males tend to remarry more often than females. 240

Potential for Microevolution Within the Columbus Greek

Community

The potential for microevolution to have occurred

in this population can be best examined by noting the

potential for genetic change due to each of the forces of microevolution.

Natural selection: The demographic characteristics of

the Corumbus Greek community suggest that natural selec­

tion could have operated at only a moderately low level

compared with other human populations. Low mortality and

fertility rates and a low variance in the number of off­

spring all contribute to the low potential for natural

selection. Following the general pattern for industrial­

ized populations, however, the Columbus Greek population

did exhibit a trend in which the potential for selection

from differential fertiltiy was more significant than

that due to mortality.

Gene flow: As we anticipated in an immigrant population with a continuous flow of ..immigrants, the admixture rate

was high, averaging over 50$ in all generations. The homogenizing effect of gene flow that might be expected

if the immigrants were randomly selected is not as high because the immigrants came from a single country. 241

However, as the immigrants came from a number of villages

in Greece, we anticipate the homogenizing effect of gene

flow to be less than that derived from a random universe

of immigrants, but more than if the immigrants all came from the same community.

Genetic drift: In calculating the potential for genetic drift in the Columbus Greek population, we first calcu­ lated the effective breeding size of the population.

This was estimated to be within lfo of Lasker’s estimate of the effective breeding size of a population.

Calculation of the coefficient of breeding isola­ tion allowed us to see that in the Columbus Greek popula­ tion, genetic, drift had a slight to moderate potential for differentiating the population. Although the effec­ tive breeding size was sufficiently low to allow for a large degree of drift, the immigration rate was great enough that only low to moderate microdifferentiation from drift was likely to result.

Inbreeding levels: Inbreeding does not affect the gene frequencies of a population, but only the phenotypic expression of the genes by allowing the more frequent appearance of rare recessives. Hence, it is not actually a force of microevolution, but it is of interest to 242 population anthropologists. The inbreeding level of the

Columbus Greek population was greater than that for the

Columbus Catholic population, but much lower than that for other religious isolates in the United States such as the Dunkers, Hutterites and Mormons. The inbreeding rate in the Columbus Greek population was relatively low com­ pared v/ith other national rates.

Inference of Cultural Influences on Forces of Micro­ evolution

Several cultural factors both directly and indi­ rectly influenced the potential for microevolution in the

Columbus Greek population. These factors were discussed in Chapter VII in terms of their influence on the popu­ lation structure and demographic vital rates. Cultural influences on the forces of microevolution can now be inferred.

1. The desire to provide material goods and education for their children was a primary factor in the popula­ tion's low birth rate. In addition, later age at mar­ riage and strict premarital celibacy contributed to the low birth rates. The mortality rate was also low because, for a variety of reasons, the population traditionally sought good medical care. The combination of low birth and mortality rates resulted in a moderately low 243 potential for natural selection.

2. Religious proscription directly retarded the level of inbreeding.

3. While there is a strong cultural preference for mates to be of Greek heritage and of the Orthodox faith, the influx of immigrants has allowed a wider choice of Greek mates than just those born in the Columbus area. The pattern of preferred mate selection based on cultural endogamy rather than geographic propinquity (for place of birth) contributed to a high rate of gene flow.

4. The continuous inflow of immigrants retarded the extent to which genetic drift could have operated.

Summary

The Greek community is politically, geographically and economically well integrated within the larger Colum­ bus population. However, it constitutes a viable ethnic group with distinct aspects of a continuing cultural tradition. While the Greek Orthodox Church has been the most consolidating influence, traditional values, family relationships, language and forms of recreation have con­ tributed to the reproductive isolation of the population.

This pattern is likely to be maintained because the older urban Greek immigrants are making conscious efforts to preserve their traditional heritage, there is a 244

continuing influx of migrants from Greece, and the exist­

ence of a very strong religious organization are all fac­

tors contributing to the continuation of the distinct

community.

The demographic history of the Columbus Greek popu­ lation, however, is not of a closed population. The his­

torical and present demographic dynamics of the community have provided the parameters for the operation of several microevolutionary processes. Natural selection and

genetic drift potentially have occurred only to a low to moderate degree; gene flow has occurred at relatively high rates. Thus, the major microevolutionary force

operative in the Columbus Greek community has probably been gene flow. As gene flow usually acts to stabilize

gene frequencies in populations, I conclude that there has probably not been extensive microdifferentiation within this urban immigrant population.

Implications for Future Research

This study does not pretend to explain everything

about the relationship between biology and culture in reference to the community's population structure or to

its microevolution. However, it is a beginning in the formulation of generalizations concerning industrialized populations. The following are suggestions for future research based on the findings of this study:

1. This study could be greatly enhanced by a follow-up study of the same population in which quantitative physiological data are used to examine allelic frequencies and to test if the calculated microevolution of the popu­ lation is substantiated. This follow-up could ideally be performed concommitantly with the thalassemia screening program.

2. The implications of the study of the microevolution of an immigrant community suggest that there also may be general microevolutionary patterns found in communities of emigration. A promising line of investigation would be to examine the effect of large scale migration on the villages of origin.

3. Another topic which has been neglected in the litera­ ture is the examination of the reciprocal relationships between culture and microevolution. The present study examined the influence of cultural factors on the micro­ evolution of a population; a project investigating the converse would further integrate the subdisciplines of cultural and physical anthropology. The proposed re­ search would investigate the extent to which population structure influences cultural practices (e.g. how does the biased sex ratio favor assimilation of an immigrant population into the larger population). 246

4. Because the potential for microdifferentiation varied considerably with the scant comparable data on urban industrialized groups, I strongly suggest that other studies of such populations be performed. Until such studies are completed, generalizations concerning micro­ evolution in urban industrialized populations are not possible. APPENDIX A

At times it is difficulat to state whether differ­ ences in sex ratios between populations are meaningful.

One factor, the sample size, becomes especially important in this determination. If we know, for example, that one population has a sex ratio of 101 and another the ratio of 104, we can only determine through calculation if there is a meaningful difference between these ratios.

One method used to determine "meaningful differences" is to calculate whether the ratios fall within a confidence interval determined by a given degree of confidence (e.g.

0.95). This method is as follows:

- males ■P “ males + females

The standard error of p is a description of the distri­ bution of p; it is an estimate of the standard deviation and is calculated as

S E 11 ~P ( 1 — P ) • p - V males + females

The confidence interval for p (at 957°) is calculated as

247 p + 1.96(SEp) which, is

•n + 1 96 '/__ p(l - p) • p - \ males + females

From these calculations, it is obvious that as the sample size (males + females) increases, the standard error decreases. APPENDIX B

In more theoretical works, the same equation is usually seen in the notation of integral calculus:

This says the same thing as the summation equation given m the body of this paper (li m e = 1) only more pre- cisely. Instead of taking the intervals of time (x) in large units (days or years) the intervals are made in- finitesimally small (i.e. d ). Hence, the value of r obtained will be very precise. In practice, however, the summation equation is ordinarily used because the data can only be retrieved in the larger units of time

(Wilson and Bossert 1971).

249 APPENDIX C

INTERVIEW SCHEDULE

Although it is confronted by continuing accultura­ tion pressures and is economically and politically well integrated into the larger urban society, the Greek Community of Columbus is attempting to preserve many facets of the traditional Greek way of life.

In order to determine the way in which these traditional values are being maintained, you will be asked the following questions:

1. Who resides in your house?

2. Why settle in Columbus? - did you have friends or relatives here previously? - occupational history

3. Previous family address - reasons for moving

4. Previous family name

5. Do you know other members of the Greek community in your neighborhood? - amount of interaction with them

6. Participation in religious activities (church attend­ ance, special services, church organizations)

7. language retention (bilingual; children attend Greek language school)

8. Major social activities (what and writh whom)

9. Communication with friends and relatives in Greece (frequency, method) - return visits 250 251 10. Maintaining traditional customs (marriages, festi­ vals, ciiristenings, etc.)

11. Peelings of marrying within the church (do you want your children to?) - do children retain your values and traditions? 12. What folklore is told to children? 13. Do you know of any Greek beliefs or superstitions?

14. Frequency of preparation of traditional Greek foods

15. Use of traditional medicine (home remedies, etc.)

16. V alue s

17. Any problems encountered as a result of following any of these traditional customs? MARRIAGE ID £ NAME i DATE 'p l a c e RESIDENCE ;NAT OCCUP ED INC ' AGE SPOUSE ORIGIN I

U KJ>

O i J--- I O H 'A £D CO REPRODUCTION DEATH AOM LB "IF DEAD RW 1st" DN BC" 'B'A'jE PLACE CAUSE ~ ILLNESS ADD MED r 1-3te l f • .1____ - • r i i i » i --- I

/ -

IV) VJ1 i. _i ___1------IV) APPENDIX D

ANNOUNCEMENT OF RESEARCH

From THE CHARIOTEER, Volume 7:16 (1977) ANTHROPOLOGY STUDY CONDUCTED

by Diana Synadinos Having to slush through snow every day to keep appointments would discourage most of us, but Toni Relmer finds it invigorating. Having grown up in Iowa where winters are nuch heav­ ier, she was delighted with Ohio's recent snowy, cold spell. Who is Toni Reiner and why are some of us getting phone calls fron her asking if she might interview us? The explanation is interesting. B o m in 1946 in Perry, Iowa, she grew up in that small community. Her mother was the school nurse and everybody knew everyone el3e. After high school, she got into an Army pro­ gram to study nursing. She completed the program with a B.S. and served in this country for . 3 years. She then re-entered college to pursue a Master's degree in nursing. She married Steve Reimer in 1968. Steve was also from her home town of Perry. His fa­ ther was the history teacher in the high school there and there were many similarities in both backgrounds of Steve and Toni. Steve is now a professor of economics and accounting at OSU and that is what originally brought them to Columbus in July of 1972. Toni enrolled in graduate school at OSU in the Department of Anthropology. Why the de­ parture from nursing to anthropology? Well, it's not exactly a departure. Toni's nursing experience brought some interesting observations to light, one of them being that "ethnic" patients in a hospital staffed by middle class white Americans are often misunderstood. This led her to look into the possibilities of studying an ethnic minority group in depth so that she could take what she has learned and instruct a nursing staff in methods that will bet­ ter open understanding between patient and nurse. Anthropology seemed the most likely avenue and the main theme of her doctoral disserta­ tion will be the Creek community of Columbus, Ohio. To date, there have been no anthropolo­ gical studies done on urban Creek groups( 0o the field is untapped. 5he chose the Greek community because she felt it is a body of people chat is still somewhat Intact and still holding onto Old World customs and religious practices. The nature of the questions she asks generally deals with just how Creek we remain aft­ er migrating to this country, and moreoever, how much we have succeeded in handing it to our American born children, etc. It is a most interesting study and her results and data should be a very valuable collection for our church library. She has found everyone to be very cooperative and open, but to any who might be wary of her questions, we assure you she 1b legitimate! No names are used in her reports and infor­ mation is kept to herself. She spends nearly all of her time on this project reading back issues of the "Orthodox Observer” , histories, stories, articles and anything that will help her to better understand what it means to be Greek. Some interviews run late at night, but she is very fortunate in having a supportive husband who is quite willing to warm up his own supper and not bring pressure on her during this busy period in her life. No matter how involved in work, she and Steve play volleyball twice a week. She loves to cook and also plays flute to relax. Her musical tastes run to classical and easy listen­ ing. They both love plants. She concerns herself more with Indoor plants while he does the vegetable and flower gardening around their Grandview home. Both are also avid readers. She hopes to have over 100 samples from which to compile her data and if she calls you, please give her your time graciously. She is a lovely and personable gal who is winning our hearts!

253 APPENDIX E

THE OHIO STATE UNIVERSITY

Population Study of an Urban Greek Community:

Informant's Consent Form

I, ______, consent to be interviewed by Toni Reimer with regard to information for the study of the population history of the Greek community of Columbus, Ohio. I am aware that the information I provide will remain anonymous. I recognize that I will be asked ques­ tions regarding my life history and that of other members of my family. I understand that some of these questions will be of a personal nature (for example, methods of birth control). I also recognize that I may refuse at any time to give out information and may decline to ans­ wer any or all questions. No guarantee has been given me concerning the results of this study or any benefits I might receive from it.

I understand and consent to these above conditions.

Name ______

Date

254 APPENDIX F

'FORTRAN CODING

Code sheet: IBM Fortran Coding Form

Columns Coded for:

1-4 individual's code number 5-8 individual's father's code number 9-12 individual's mother's code number 13 gender 14-15 month of birth 16-19 year of birth 20-23 year of mother's birth 24-25 place of birth 26 present residence 27-30 year of migration 31 education 32-33 occupation 34-35 age at marriage 36- marital status 37-38 years between marriages 39-42 spouse's identification number 43-44 spouse's place of birth 45 io Greek 46 spouse's °/o Greek 47-48 woman's age at menarche 49-50 woman's number of livebirths 51-52 woman's number of deceased children 53-54 woman's number of stillbirths 55-56 woman's'number of miscarriages 57-. woman's number of abortions 58 woman's method of infant feeding 59 woman's method of birth control 60-62 age at death 63 place of death 64-65 cause of death 78-79 age of father at birth 255 o o o o o o o o o © o 000000000000090 ooooooooooooooooooooooooooooo oooooooooooooooooooooooo oo o o o o o o o o o o o ooooooooooooooo OOOOOOOOOOOOCOOCOOCOOOOOOOOOO OCCCoOOOOOOOOOOOOOOOOOOO 0*3 0305*4-4*4-4 •4 W-4-4 •4 -jcrc- cxcr a* cr-o-Q'y'Q'KT\r'J"j' V1VIVIVIVHJI4* X-X" X* X* •f'X* X" t'.C'VJ WUJl.HUJ'W'jJ WV4'.4MMr>J M r 'jN N N N N t-'H W M W M M H M w O O O O O O O C O v» X^UIM M © •owwou' X'wrowOHjcowo U lX'UlM WO'OCD*4CM»PX»t>irO w O -0CD-4O VlX“ ,*JM w O "0© *4 O* V»X'l>JMwO'OaO*4 '>ViX' WM*— O '0 t»*4 tf‘ V lX 'V i

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COLUMBUS GREET: AGGREGATE DATA PROGRAM

FCRTRAN IV GI RELEASE 2-0 MAIN OATc * 77 i 3 1 13/99/16 DIMENSION I PCP(1001,IDETHI1001,InlRI100),ISblRI 100,2 I ,ISAGEt100,19 COOl *,2>,lSUIRG(lL0,2u,2},lS0tTllJC,19,2),ISim9(lD0,19,2),IYtAR$(IlJ, *1 SC ITA(100,3.2 I,1BIPUI100,191,IU1FA1 100,19),IDET( 100,19 » ) , ICf'CPI 11 i . lCCEThl 11 ) , ICBIRl11 ) , ICM01RI 11) , I OF B I H ( 11 ) ,1DMAGEI 11,2 •0), I OF AGE(11,20),1 OBI MCI 11,20),IOMDfcTI 1 I,20 I,IDFDfcT111,20),YEAKSI »11),ICAG(3CCG,2),DAG(3000,2 I,TDAG(2),TSDAGl2),1DOAGFl11,20) CCC2 DC 9 C0 1=1,ICC CCC3 1FCF(I>=C CCC9 IDt 7H (I )»0 CCC5 I B 1R 1 I )= C CC06 • DC 901 J = 1 , 2 • - ...... ---- etc; 1SB1R(I,J)=0 CCCB DC 902 K = 1, 19 CCC9 1 SAGE(1,K,J ) = 0 CC1C ISCLT(1,K,J )=0 ecu ISBIHCI1,K,JI'O C012 1 SO1FA(I,K,J)=C 001 3 ISOIKCII,2C,J)*0 ecu — ISC ]FA( 1 ,1,J>«0 -...... CC15 1SCIFAI1,2,J)*0 CC16 1 SC IF A( 1,3,J) = C 0017 I B 1 R G ( I » K ) = 0 C0 18 IHIFA(I,K)=0 C0I9 1DLI( I ,K ) = C C020 902 C C M 1 MJE CC21 9 C 1 C C M I M J E 0022 ' — 9C0 C C M I MJE...... - ...... -• ‘ • — — CC2 3 DC 903 1=1,11 0C29 1UPCPII 1=0 CC25 l C CtIM 1 ) = C CO 26 ICB1R(I)=C CC27 I CRB 1 H ( 1 ) = C CC26 ICFB1R1I ) = G CC29 YEARS!I)=0.C C 030 — ------CC 909 J = 1, 20 ------CC31 ICRAGEl1,J)=C CC32 ICFAGEl1,J)=C C033 ICBIRC!I,J)*C CC 39 ICEAGFt1,J) = C CC35 IDRCLT(1,J 1=0 CC36 1UFDE7(I,J)=C C C 3 7 909 C C M IMJt C038 - — 903 C C M imJb ...... ------C 039 DO 906 I=1,3CC0 GC9 0 CC 9 C6 K = l,2 CC91 1CACIi,K)=9S9 C092 LAC(I,KI=999. CC93 9C6 C C M INUE CC99 DC 9C 7 1=1,2 009!) 7CAG( 1 )=0. C C 9 6 -- 9C7 C C M 1 MJE - • • ------CC97 DC 908 K=l,2 CC98 TSCAG(K)«O.C CC99 900 C C M INUE CC50 IMACR*0 CC51 1MAGF =0 CC52 1SRA0R=0 C053 ISRAGF=0

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oS' FORTRAN tV G1 RELEASE 2.0 MAIN DATE * 77131 13/49/16 PAGE C0C3 0111 |FI IAMU-34 • LE, GO TO 117 C 1 U IFlIAMU-35.LE, _ GC __ TO 118 0113 ‘ IF(1AMC-44.LE.0) GC 70 119 0114 1FIIAFC-49.LE.CI GO TO 120 0115 1Ft IAMC-54 ,LE .0 ) GO TO 121 01 16 IF(IAMO-59.LE.0 GO 70 122 cut IF! 1AFU-64.LE.01 GO TO 123 0118 I FI IAFU-69.LE.0) GO TO 124 0119 1F1 lAFU-74.Lt.Cl GO TO 125 0120 IF1 IAH0-79.LE.0I GO TO 126 0121 IF11AFC-B4.LE.0I GO TO 127 0122 GO TO 128 0123 n o P = 1 0124 GO TO 130 0125 111 F =2 C126 GC TC 130 0 12 f 112 F = 3 012 8 GO TO 130 0129 113 F =4 0130 GO TO 130 0131 114 F = 5 0132 GC TO 130 013 3 115 F = 6 0134 GC TO 130 0135 116 F - 7 0136 CC TO 13C 0137 — 117 F = 8 C I 38 GO TG 130 J 139 118 F = S 0140 GC TC 130 0141 119 F = 1 C 0142 GC TO 130 0143 120 P*1 1 0144 GC TO 130 C 14 5 ~ 121 F -12 0146 GO TO 130 014 f 122 F 3 1 3 0148 GC TO 130 0149 123 F 3 1 4 0150 GO TO 130 C 151 124 PUS 0152 GO TO 13C 0153 ---125 H = 16 0154 GC TC 130 0155 126 H = 1 7 C 156 GC TC 130 0157 127 pue 0158 GC TO 130 0159 128 P U S C 160 GO TO 130 0161 ------130 1 F t 1AGF.EC.0) GO TO 131 0162 1FI IAGF-4.IE.'' .01 GO TO 132 C163 1 FI 1ACF-9.LE..0) GO TO 133 0164 1 FI 1A0F-14 .LE:.0) GO TO 134 0165 1FI IAGF-19.LE1.01 GO TO 135 0166 IF t IACF-24 .LE .01 GO TO 136 016/ 1F( 1AGF-29.LE .01 GO TO 137 C 168 IFC 1AGF-34 .LE ,01 GO TO 138 FORTRAN IV Gi RELEASc 2.0 FAIN CATE 77131 13/59/16 PAGE C0C5 ii mia&M2:ti:5l 82 13 HI cmmi IFl IAGF-59.LE.0 GO TO 191 cm IFl |AGF-55.LE.0i GO TO 192 0173 1F( IAGF-59.LE.0 GC TO 193 01 l'. lFtl9GF-69.LE.Cl GO TO 199 Cl 75 IFl I6GF-65.LE.0I GO TO 195 Cl 76 IFl 1AGF-75.LE.01 GO TO 156 C 1 7 7 IFl 1AGF-79.LE.0I GO TO 157 Cl 78 IFl 1AGF-85.LE.0I GO TO 158 Cl 79 GC TC 155 C1E0 131 FF»1 cm GC1 TC 150 0182 132 FF = 2 0183 GC TO 150 0189 133 F F = 3 C 18 5 GC TO 150 0186 135 FF = 5 018 7 GO TO 150 C1 88 135 FF=5 C1B9 GO TO 150 0190 136 FF = 6 G 1 5 I GO TO 150 C152 137 FF-7 0153 CC TO 150 0199 138 FF= E 0155 GO TO 150 ...... J 156 139 FF*S 0157 GO TO 150 C 158 150 FF = 1 0 C1S9 GO TC 150 020 0 151 FF* 11 02C1 GC TC 150 0202 152 FF= 12 0203 GO TO 150 ...... 0209 153 FF = 1 3 C205 GO TC 150 02C6 155 FF* 15 020 7 GC TC 150 0200 155 F F = I 5 02C9 GC TC 150 0210 156 FF- 16 0211 GC TO 150 0212 157 FF*17 0213 GC TO 150 0219 158 FF = 18 0215 GO TC 150 0216 155 FF=19 02 17 GC TC 150 0218 150 ISBIKOI Jr F . K K I M S B l M O N >M,KKM1 0219 I SB 1 FA I J,FF.KK)*ISBIFAIJ,MF,KK)«-1 0220 IF IF—MFi 8 7(88.89 C 22 L 6 7 I SCI FA(J,l,KK)-iSOIFAIJ,l,KK)+l 0222 GC TC 90 0223 88 ISCIFA(J,3,KKI*ISDIFAIJ,3,KKM1 0229 GC TO 90 0225 89 ISC I FA IJ,2,KK)=ISD1FACJ,2,KK)«1 0226 GG TC 90 FORTRAN IV Gl RELEASE 2.0 MAIN DATE 77131 1 3/*9/16 PAGE 0005 0227 90 IFIIFGB.EC.Oj GC TO 02 0220 Ifi 1aijf.eij.o J g c to o2 - 0229 — ICALl l,KK Ir 1 AGF - I AiTC 0230 CAC-I I ,KK ) = ICAGl I .KK| 02 3 I IFlKK.EO.ll BF^BFU. 0232 IFlKK.fcC.21 OF = CF +1. 0233 TCACIKKl'lOAGlKKl+CAGll.KK) 023* 3SCAOlKK)=TSCAOlKKlFDAGll,KKl<'*2 0235 IFIKK.EC.ll 1FAC F =IMAUF♦IAHO 0236 IFlKK.EO.ll IFAGF*IMAGF*1AGF 02 3 7 — IFlKK.EO.ll ISFACM = ISMACMHAM0«*2 0238 IFlKK .EO.l1 ISFAGF=1SNAGF*IAGF»»2 0239 IFIKK.EU.2I IFACF = IFACMHAMO 02*0 IFIKK.EQ.2I IFAGF-IFAGFf IAGF 02*1 IFIKK.E0.2J ISFACF*ISFACHf IAM0#*2 02*2 IF IKK .EO. 2 I 1SFAGF»ISFAGFHAGF**2 02*3 GC 1C 82 02** tl LG R = 2 02*5 GO TO 80 ---- 02*6 62 LGR*3 02*7 CC 1G 60 02*0 63 IGR=* 02*9 GC 10 OO 0250 6* LGR = 5 C 2 5 1 GC 1C 80 0252 65 LGP = 6 C253 GC 10 no ------025* 66 LGP = 7 0255 GL TO 00 0256 67 LGP = 0 C257 CC TO 00 0250 68 LGP = 9 0259 CC 10 00 0260 69 LGP*10 C261 GC 10 00 - • ' 0262 10 LGP*ll C263 GC 10 80 026* 71 LGR = 12 0265 GC 1C 00 C266 12 LGP = 13 0267 GC 1C 80 C260 13 LGR1 1* C269 GC TC 00 ' C270 1* L GR * 15 C271 GC IG 80 0272 15 LGR = 16 02 73 GC 10 00 02 7* 16 LG R * 17 02 75 GC 10 00 0276 IT LGR*18 02 77 ' GC 10 00 0270 78 LGR = 19 02 79 GC 10 80 0280 79 lSeiKOl J,2O,KK) = IS0IHOl J,20,KKH1 0281 80 IFjJ.EQ.il GC TC 90 0282 £2 IFIK-1V0R-IACE.GT.OI GO TO 101 0283 IFIK-1VBR-IACE.EC.0I GO TO 81 028* I SAGE!J,LGR,KKI*1SAGECJ.LGR.KK1*! 262 FORTRAN tv G1 RELEASE 2.0 MAIN DATE » 77131 13/99/16 PAGE OOC6 t iMl t icci£Jloi=|PCFCJ»*l 0267 — 81 1SCETU iLGPfKK) *ISOET(J.LGR.KKI»l 0208 IUETH|Jl=lCfcTH(Jl + 1 G209 101 C C M INUfc 0290 ICO C O M 1NUE C291 ACAGFMGAGI I l/BH C282 ACAGF=TLAG!2l/BF 0 29 3 R FAC F = IF AC P 0299 RFAGFMFAGF C295 RFACMirACF C276 RFAGF=IFAGF 0297 APACM=KFACP/ EM C298 APACI^HFAGF/BM C299 AFACP=RF ACP/EF 0300 AFAGF=RF AGF/EF OJOl DC 105 J M . 1 C 0 0 302 IF1J.LT.5) GC TC 30 0303 1F1J.LT.15) GC TO 31 C 309 1F1J.LT.261 GC IC 32 0305 IF1J.LT.J5) GC 10 33 0306 1F1J.LT.9 5) GC TO 39 0307 IFtJ.LT.55! GC 10 35 0308 IF(J.LT-fc5) GC TC 36 03C9 IF!J.LT.75) GC TO 37 0310 IF1J.LT.85) GG TC 38 031 1 1FIJ.LT.951 GC TC 39 0312 GC 10 90 0313 30 1CPCP11) = I0PCP111*1 POP 1JI 0319 IC0ETH1l!=ICDETHll!*IOETH(J) 0315 U.E1RI) > = I!.eiR< lMlBlRIJ) 0316 ICMIMR(I)=lCPBIR!ll*ISBIRlJil) 0317 1DFBIR11) = ICFBIRtl)*ISEIRIJ»2) 0318 CO 600 K= l tlS 0319 IDPAGEl 1 ,K M ICPAGE 11 .KS USAGE! J,K, 1 I 0320 I OF AGE 1 l,K)MCFAGEll,Kl*ISAGEl J,K,2) 0321 ILL* I MCI t .K 1= ice IPO I 1.K1 ♦ I SBIMUt J,K, UU S B 1 H 0 I J.K.2) 0322 ICB AG F1 1 * K 1 * ICEAGFllfK) U SB I F A1 J .K , 11 ♦ 1 SB I FAl J, K, 21 0323 IOPLETl1,KJ=1CP0ETI1,K HI SUET(J ,K >11 0329 ltFOCTll,K)=IOFCET(l,Kl*lSUETlJ,K,2l C325 6C0 C C M 1NUE 0326 ICE 1M011,201 = 1CUI HOI 1,20)*1SBIMOIJ,20,11M S B 1 M 0 1J ,20,21 0327 YEARS!1 I=9. C328 GC IC 105 0329 31 ICPCP12I=1CPCPI2I*IP0P1Jl 0330 ILCETM12)=1C0EIH12)*1CEIH1J) 0331 ltBtR!21-tCBIRl21*lUlR(Jl . C332 lCPeiRl21=lOPOlRtE)* 1SUIH{J,11 C 3 33 10FB1R12 1= 10F0IR12IHSEIR1 J,2I 0339 DC 601oul K U I. i 1i 97UL C335 ICPAGE12 .K 1= JCPAGE (2.K ) USAGE! J,K, 1 0336 I0FAGE!2iK)=lDFAGt(2rK)*lSAGHJ.Kf2iK)=lDFAGt(2rK)*lSAGHJ.Kf2! C337 1CG1M012■ r n t u r n -i ,K)MCOIPCl2.K)USBIMG(J,K,llUSBIMOtJrK,2)1/ i. trn lu rr 7 if litu lu m l.lf . 0338 ICBa GF1 2 ,K)i K ) = IDEAGF12IDEAGFI 2•Ki K 1 ) +ISB1FA1J.K+ISB1FA1J,K ,1)♦I SB IFAIJ,K,2) C339 ICPCET12,K)=I0P0ET(2,K)USDETI.Klsinyi)FTI7.KI*I9nFT(J.K.Il J,K,ll 0390 ICF0ET12,ICF0ET12,K)«IOFDcT12,K)USOET(J,K,?J 0391 t Cl C C M 1 N U E 0392 IC81MO(2,20) = IDBIMG12.2C)MSB1MOIJ,20il)♦ISBIHO(J ,20,21 IV) CD KjJ i OOQCOOoOQOOOCCOQQQOOCOOCOCOOOOOCOCOOODOCnCCOOOOOOOQCOCOOoO O»/'Wl^Os0'^3^o«c».Tajrn(T:rnm®(i3CDOTCD"^-^~^— c* O' o c* C o* O' a* unjiv/iW'on'-nsflSflvAV/iX' Xs x> x x* Xs x* • o»/> ®«o<^snx wru—o0 'ra-«0"Ji xmrsjr—o»c® *-«a'm-Xujrj^*o >C c«NiO,mx<»s**-oa3a:*»JC'^/'X*u

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592 FORTRAN IV G1 RELEASE 2.0 Ha in CA IE 771 31 13/49/16 PAGE 0009 0459 C4 6C IK(J.ll 0461 IUFC1RI10MICFDIR(10HIS01R{J,2) 0462 DC 009 K = |,19 0463 I OH AGE I 10,6 ) = IOMAGEI 10,KMISAGE(J,K,1I 04 6 4 IDFAGEI I 0 i K I = IUFAGEUO.KI t ISAGEt J .6,21 0465 ICe Il'LH 10, K ) = 10 8 I MO ( 10.K) H SB 1 HOI J.K, 1 Ml SB I HOI J,K,2I 0466 ICEAGF110,KI = IDPAGF(10,KM1SB1FA(J,K,1MISBIFA(J,K,2I 046 7 ICMCETI10,K) = 1CMDETI10,KMJSCET(J,K,1) 0460 IDFCETI LO , K M IDFUETI 1U.KMISDETI J,K,Z> 0469 609 C C M 1NUE " ' 04 fO 108 I HO I10,2CMIC81HC<10 ,20M I SB 1 HOIJ,20,1 MI S B I M G IJ,20,2 I 0471 7 EAR SI 101 = 10. 0472 GC TC 105 0473 . 40 IDPOPII 11 = IDFCPIl11*1 POP!Jl 0474 ICCETHU 1 M lUDETHl 11 M1DETHI J ) 0475 icuIRl i n = ioei p 111 i*i o i r i j ) 0476 I0HBIRI I 1 )= 1 CHOIR 111 Ml SOIRl J, I) C4 77 1DF8JPI 1 1 )= IUFI1JRI 1 1 ) *1 SDIR1 J,2) ...... 04 78 00 610 K = 1 , 19 04 79 IDMAGEI 1 l,K MI O M A G E U I.KM1SAGEI J,K, I) 04 80 1CFAG till, KMIOFAGEIll.KMISAGElJ. K, 2) 0481 1CEIMC(11,KM1CRIMC(11,KMIS01MU( J,K ,1M I SB I MO I J,K,2I 0482 1 C8AGFI 1 1 ,K M IDE AGF II 1 , KMlSBIFAl J,K. I MI SB I FAl J.K, 21 0403 IOMLET(ll,K) = lDMDET(llfKMlSDET(J»K,il 0404 IUF0ETI11,KI = 1DFDE7I11,KMISDET(J,K,2) 0485 ‘610 CCM1NUE 04E6 1CB1M0I 11,20 M10BIH01 11,20 M 1S BI HOI J,20,1 1 US B I MO I J,20,2) C48 7 VEARSI1 I ) = 6 . C480 GO TO 105 0489 105 C C M INUE 0490 WRITE (6.2001 0491 ZCO FCRHAT I 1HI, 45FIRE IHER GREEK POPULATION COLUMBUS OHIO 1977 I 0492 WRITE I6.2C1) 0493 201 FORMAT I////4X,5HYEARS,2X.I7HT0TAL POPULATION ,2X,13HT0TAL DEATHS ‘ A.2X,1JHTOTAL BIRTHS ,2X,l2HMALE BIRTHS ,2X,14HFEMALE BIRTHS I 04 94 00 200 M l , ICC C495 10ATE=IB7g * 1 C496 WRITE I6.Z02) 1CATE,IPCPI1),ICETH11).1BIR1I I,ISEIR1 I ,I),ISBIRII,2) 0497 202 FORMAT (111 ,4X,I4.8X,15,12X,15,10X,|S,10X,14,11X,14) 0498 300 C C M INUE 0499 WRITE (6,203) 05C0 "2C3 FCFMAT (1 HI.4X,30HGREEK HALE AGE DISTRIBUTION I 0501 WRITE (6,204) 0502 204 FORMAT t / / / 1 IX , 5H-0- .IX.5H1-4 ,lX,5HS-9 ,I X,5H10-14,1X,5HI5-19 G,IX,5H20-24,1X.5H25-2 9,IX,5H30-34,IX.5H35-39,IX,5H40-44,IX,5H45-49 F,IX,5H50-5 4,IX,5H55-5 9,1X,5H60-64,IX,5H65-69,IX.5H70-74,1X.5H75-79 A,1X,5H8C-84,1X,5H05» I 0503 DO 201 M l , IOC 0504 IUATE=187b«I 0505 WRITE (6,205) I C ATE , ( I S AG E < I , J , 1 I , J» I, 19 ) 0506 205 FORMAT (lH ,I4,2X,19I6 ) 0507 3C1 CONTINUE 0508 WRITE (6.2CGI C5C9 206 FORMAT I1H1,4X.32HGREEK FEMALE AGE DISTRIBUTION ) 0510 WRITE (6,204) DC 3C2 M l , 100 8111 I0ATE*1E76«I 266 FCRTRAN IV G1 RELEASE 2.0 MAIN DATE = 77131 13/99/16 PAGE CO 10 0513 C519 CRm ! AUE ,Z°5) it'ATt'1ISAGE,J = 1,10) C6SS WRITE! '7,2',6) ' 11 DM AGE I I,J l ,J = l1,20) C6S5 RFI1EI7,2 S 6) U G F A G E ! 1,J ) ,J=l , 10) COSO RR)T E I 7.2SOI ( ICFAGE(1,J ) ,J = 1 1.201 COS 7 WRITEI7.2S6 I (ICHtMUlI,Jl ,J=1.10) C0S8 WRITC(7,2SOI 1 IClllM.OI 1 . J) . J= 1 1,20) C6SS WRITtl7,2S6) (1DM0ETIJ, J), J = 1,,0) C7CO WRITE17.2SOI (lCMOET(IfJ),J3 li,20) C7CI UR11EI7,2S0) I1UF0ET11,Jl,J31,10) C7C2 RR 1 TEI 7,2S6I I10FUET(I ,Jl.J=l1,201 07C3 RK1TEI6.2SO) ICATE , 1UPCP! I 1, 1 CDE TIT I I I , I OB 1R I 1) , 10M8 1R ( I ) , 1DFQ1 R III — • , lYEAPSl I) C 70S WRITE!6,2S3I (IDMAGEtI,JI,J=1.10) 0705 WRITE 10,2S3 I ( 1CHAGE!I,Jl,J=11,201 C7C6 WR1TEI6,2S3I" jICFAGEII,JI,J31,10) C 707 WRITE!6.2S3I IIUFAGEI1,J) ,J=ll,20l C 708 WR1TE(6,2S3| I iceiMCH I , Jl , J3 1, loi C7C9 WR I T E ( 6, 2S 3 I 1 IC B1 HO <1,J),J=li,20) C 710 WR1TEI6.2S3) (1CM0ET1I•J I, J3 I, 1 01 "0711 wR 1T E16 , 2S 3 I U D M 0 E T 1 1 , J I ,J«11,20I C 712 RRITE(6,2S3I (IDFOET1 I,J),J>1,10) C713 RRITl(6,2S3l 1IDFOET(I,J),J-11,201 C71S 5C0 C C M 1 NUE C 7 15 STEP C/16 END 270 APPENDIX H

O.S.U. IBM SORT AND MERGE PROGRAM

// (5000.1500),CLASS=A // EXEC SORT3 ,TIME=(0,10) //S.SORTIN DD * //S.SORTOUT UNIT=SYSDA.SPACE=(CYD,(1,1)),DISP=(NEW,PASS), // DC8=(REDFM=FB,LRECL=80,BLKSIZE=800),DSN=&&S0RT1 //S.SYSIN DD * SORT FIELDS=(20,4,CH,A,9,4?CH,A,16,4,GH,A) //// EXEC FORTRUN,TIME.G0=(,30) //CMP.SYSIN DD * CcYl INTEGER 1(EC) L C C 2 F E '* 1 N C 1 .... Do“ o FC8 tin 1 ,31HSCkT ey sex and yeas cf BISTH ) CCC53 SEAC( 1 ,1 11 ND = 7 ) I CCC61 FLPPAT(SOll) CCC82 FCPPAT([h |fAIltlX,^ll»lX.4lltlXtIljlX*2IlilXiAlltlX» *ii;ix;ii,ii;;ii;tx;2ii;ix,2ii;ix,2ii,ix,2iiax,ii,ix,ii,ixfu,ix,

CCC9 GC yC 3 GC10 7 STCP GCil EiNC

271 APPENDIX I

UNITED STATES 1967 LIPE TABLES (from Keyfitz and Pleiger 1971)

table 2 LIFE TABLE FOR MALES H Age. a n^x LA A lOOOr, K ««, > 0 0.02469 100000 2469 98094 0.02517 6698012 0.00 66.98 0.02517 0 1 0.00382 97531 373 3 89038 0.00096 6599918 0.00 67.67 0.00096 1 5 0.00244 97158 237 4 85199 C.00049 6210880 0.00 63.93 0.00049 5 10 0.00257 96921 250 484082 0.00052 5725601 1 7.06 59.08 0.00051 10 15 0.00735 96672 711 481730 0.00148 5241599 34.69 54.22 0.00146 15 20 0.01001 95961 961 477443 0.00201 4759869 39.76 49.60 0.00201 20 25 0.00951 95000 90 3 472758 0.00191 4282426 25.99 45.08 0.00191 25 30 0.01094 94097 1029 468023 0.00220 3809668 2.33 40.49 C .00220 30 35 0.01547 93067 1440 461970 0.0C312 3341645 0.00 35.91 0.0031 35 40 0.02334 91628 21 39 453179 0.00472 2079676 0.00 31.43 0.00472 40 45 0.03681 89489 3294 439814 0.00749 2426497 6.06 ?7.12 0.00748 45 50 0.05648 86195 5041 419211 0.01202 1986683 9.96 23.05 C.01200 50 55 C.09025 01154 7324 380433 C.01886 15674 72 12.51 19.31 G. 01881 55 60 0.13167 73830 9721 345C40 0.02811 1179039 13.38 15.97 0 .02805 60 65 0.18876 64108 12101 291173 0.04156 833199 13, 38 13.00 C .C4147 65 70 0.26849 52007 13963 225346 0.06196 542025 13.38 10.42 C.06185 70 75 0.34549 38044 13144 156811 0.08382 316680 13.38 8.32 0.08367 75 80 0.45481 24900 11325 95039 0.11916 159869 13.38 6.42 0.11894 80 85 + 1.00000 13575 13575 64829 0.20940 84829 13.38 4. 78 C .20389 85 +

TABLE 3 LIFE TABLE FOR FEMALES Age. x nQx (r n^x n^x rtm x T, 1000^ *x nK Age. x 0 0.01910 100000 1910 98533 0.01939 7422270 0.00 74.22 0.01939 0 1 1 0.00305 98090 299 391488 0.00076 7323737 C.00 74.66 C.00076 1 5 0.00176 97791 172 488523 0.00035 6932249 0.00 70.89 0.00035 5 10 0.00149 97618 146 407752 0.00030 6443726 15.23 66. 01 0.00030 10 15 0.00292 97473 285 486694 0.00059 5955975 25.64 61 . 10 0.00058 15 20 0.00359 97188 349 485093 0.00072 5469281 36.03 56.28 0.00072 20 25 0.00423 96039 410 483219 C.00085 4984168 29.83 51.47 0.00084 25 30 0.00606 96429 585 400782 0.00122 4500969 1.84 46.68 0.00122 30 35 0.00921 95844 863 477163 C.00185 4C20186 0.00 41 .94 0.00105 35 40 0.01363 94961 1294 471793 0.00274 3543024 0.00 37.31 0.00274 40 45 0.02073 93667 1942 463794 0.00419 3071231 £.93 32.79 0.09418 45 50 0.03042 91726 2790 452074 0.00617 2607437 14.47 28.43 0.00616 50 55 0.04458 88935 3964 435335 0.00911 2155363 17.50 24.24 0.00908 55 60 0.06503 84971 5526 411932 0.01341 1720028 24.24 20.24 0.01335 60 65 0. 10384 79445 8249 377794 0.02184 1308096 24.24 16.47 0.02173 65 70 0.15801 71196 11250 329111 0.03418 930302 24.24 13.07 0.03403 70 75 0.23826 59946 14284 265172 0.05387 601191 24.24 10.03 0.05361 75 80 0.36743 . 45662 16778 186422 0.09000 336018 24.24 7.36 0.00961 80 85 + 1.00000 28885 28885 1495 9 7 0.19300 149597 24.24 5.18 0.18661 85 +

272 273

GREECE LIPE TABLES, 1966-68 (from Keyfitz and Pleiger 1971)

t a b l e 2 LIFE TABLE FOR MALES

Ape, x n*7jc A nm x T. lOOOr* h Age, i 0 0-03492 100000 3*92 9725* 0.03591 7064536 8.11 70.65 0.03614 0 1 0.00*77 96508 *60 38*667 0.00120 6967282 8.11 72.19 0.00121 1 5 0.00263 960*0 252 *79608 0.00053 6582595 3.21 68.53 0.00353 5 10 0.00236 95795 226 *78*30 0.000*8 61029BB 3.B6 63. 71 0.00048 10 15 0.00378 95568 361 *76999 0.00076 5624558 8*22 58.85 0.00076 15 20 0.0C557 95207 530 *7*7*7 0.00112 5147558 16. 75 54.07 0.00111 20 25 0.00569 9*677 539 *72053 0.0011* 4672812 6.62 49.35 0.00114 25 30 0.0063* 9*139 597 *69237 0.00127 4200759 0. 00 44. 62 0.00127 30 35 0.00760 935*2 711 *66039 0.00153 3731522 13.89 39.89 0.00152 35 40 0.01211 92030 112* *61568 0.002** 3265483 38. 52 35.18 0.00242 30 45 0.01962 91 706 1600 *5**01 0.00396 2803915 11.76 30.57 0.00395 35 50 0.03221 89907 2896 **2875 0.0065* 2349514 0.00 26.13 0.00554 50 55 0.05283 87011 *597 *2 **1 2 0.01083 1906638 6 .0 9 21.91 0.01082 55 60 0.08*77 82*1* 69B7 395792 0.01765 1482226 27.37 17.99 0.01755 60 65 0.13672 75*27 10313 352629 0.0292* 1086434 27.37 14.40 0.02910 65 70 0.20131 6511* 13109 293867 0 .0 **6 1 733bD4 27. 37 11.27 0.04439 70 75 0.29659 52006 15*2* 222159 0.069*3 439938 27.37 8.46 C .06908 75 BO 0* **869 36582 16*1* 1*2863 0.11*89 217779 27.37 5.95 0.11403 80 85+ *►1. 00000 20168 2016B 7*916 0.26921 74916 27.37 3. 71 0.26617 85 +

t a b l e 3 LIFE TABLE FOR FEMALES

Age, i ng x n^x A nm x Tx 1000rs K A Age. i 0 0.03095 100000 3095 97578 0.03172 7**9622 7 .3 5 7 * . 50 0.03191 0 ] 0.00*35 96905 *22 386387 0.30109 73520** 7.35 75.S7 0.00111 1 5 0.0016* 96*83 17B *81970 0.00037 6965656 2. 70 72.20 0.00037 5 10 0.001*0 96305 135 *81189 0.00028 6*83668 3 .29 67. 32 0.00028 10 15 0.00166 96170 161 *80*18 0.00038 6002*98 5.11 6 2-*2 0.00 036 15 20 0.002*0 95989 230 *79398 0.300*8 5522380 6.68 57.53 0.000*3 20 25 0.00331 95759 317 *76029 0.00066 50*2682 0.00 52. 66 0.00065 25 30 0.00387 95**1 369 *76327 0.00077 *56*653 0 .0 0 *7 . 83 0.00077 30 35 0.005*3 95073 516 *7 *1 *8 0.00109 *088326 18.02 *3 .0 0 0.00109 35 40 0.00775 9*556 733 *71086 0.00156 361*178 39.50 36.22 0 .0015* 40 45 0.01252 93823 1175 *66390 0.03252 31*3092 14.77 33.50 O.D0251 45 50 0.01875 926*9 1737 *59237 0.00378 2676702 0. 00 26. 89 0.00376 50 55 0.03067 90911 2788 **8151 0.00622 2217*65 13.35 24.39 0.00620 55 60 0 .050*6 88123 ***6 *30531 0.31033 176931* 26.8* 20. 08 0.01026 60 65 0.092*2 83677 7733 *00557 0.01931 1338783 2 6 .6 * 16.00 0.0191B 65 70 0.15369 759** 11672 352*32 0.03312 938226 26.6* 12.35 0.03291 70 75 0.26175 6*272 16823 281012 0.05987 58579* 26. B* 9.11 0.05951 75 60 0.41915 *7 * * 9 19668 189761 0 . 10*81 30*782 2 6 .8 * 6. *2 0.10398 80 65+ «>1.00000 27561 27561 115022 0.23961 115022 2 6 .8 * *.17 0.23696 85 + BIBLIOGRAPHY

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