Area classification and types of movers in the Boston SMSA; the use of an information system for the analysis of areas and movers.

AREA CLASSIFICATION AND TYPES OF MOVERS IN THE BOSTON SMSA

The Use of an Information System for the Analysis of Areas and Movers

by

CATHERINE DONAHER A.B. Regis College

(1962)

SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE

DEGREE OF MASTER OF CITY PLANNING

at the

MASSACHUSETTS INSTITUTE OF TECHNOLOGY June 1968

Signature of Author . . ... . . . . . . . . . . . . . . . . . . . . Department of City and Regional Planning

Certified by. . . . ... .-

-Thesis Supervisor

Accepted by. . . .

Head, partment of City and Regional Planning

Archives

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ABSTRACT

AREA CLASSIFICATION AND TYPES OF MOVERS IN THE BOSTON SMSA The Use of an Information System for the Analysis

of Areas and Movers by

CATHERINE DONAHER

Submitted to the Department of City and Regional Planning on June 7, 1968 in partial fulfillment of the requirements for the degree of Master in City Planning.

A classification of areas within the Boston SMSA was constructed using income and occupation variables from the 1960 Census tract data and Households interviewed in 1965 were classified into four types of movers by length of residence and future prospects for moving. The

attitudes and attributes of the four types of households were investi-gated before the Census tract data was mapped onto the survey file. The individual classifications and the comparative analysis yielded

the following results:

1. classification of areas by socio-economic characteristics, rather than by spatial location, yields a coherent and consistent pattern of areas.

2. the type of housing in an area is a good indicator of the type of household to be found in the area.

3. subdividing the stayer mover dichotomy by length of resi-dence is meaningful for explaining motivation for moving. 4. attitudes toward residence are area oriented while reasons

for moving are closely associated with life/career cycle.

5. The use of an information system to coordinate disparate

data sources yields rich descriptive information and the shortcomings lie more with the data sources than with the system.

ACKNOWLEDGEMENTS+ TABLE OF CONTENTS

LIST OF TABLES AND CHARTS CHAPTER I. II. III. IV. V. APPENDICES INTRODUCTION

AREA CLASSIFICATION AND RESIDENTIAL MOBILITY Literature

Ecological Theories and Research Migration Theories and Research AREA CLASSIFICATION AND RESIDENTIAL MOBILITY Empirical Work Data Sources Initial Analysis units of analysis initial classification Area Classification Household Classification Area-to Household Mapping THE USE OF INFORMATION SYSTEMS AND THEIR

CON1RIBUTION TO CITY PLANNING CONCLUSIONS AND SUMMARY

Notes on the ADMINS System List of Census Variables List of UCS Variables BIBLIOGRAPHY 6 9 9 15 20 20 21 21 23 27 40 53 63 70 71 78 80

LIST OF TABLES AND CHARTS

TABLES PAGE

1. Physical Variables by Area Type 34

2. Socio-Economic Variables by

35

Area Type

3. Census Tract Values and Individual

59

Values for Types f Mtevers

4.

Distributions of Types of Mevers 61 Within Types of Areas

CHARTS

1. Negative Attitudes Toward Neighborhood

50

2. Positive Attitudes Toward Neighborhood $1

3. Reasons Fe. Moving

52

h. Co-occurrence of Types of Vovers in 62 Boston Area Census Tracts

MAPS

1. Types of Areas Outside Boston City

38

buted to the preparation of this thesis: Professor James Beshers for his suggestions throughout the preparation; Professor Aaron Fleischer for his comments on the first draft of the paper; Messrs. Stuart McIntosh and David Griffel for their constant support and suggestions

in the use of the ADMINS system; Mr. Donald Dobbins of United Community Services for making the survey data available for use and Mrs. Jan O'Grady for her help in preparing that data.

--

6-CHAPTER I

Introduction

Underlying both the descriptive and analytic aspects of this thesis is the search for greater understanding of the process of change. Changes in cities and their surrounding areas are occurring so rapidly that the monitoring of this change is a challenging task. The changes take two forms: different compositions of the

popula-tion and transformapopula-tion of land from one use to another. These changes are due to mass movements of people and the mass movements are com-prised of the shifts in residence of thousands of individual households in every city. By investigating why shifts in residence take place we can identify characteristics of movers which place them at points

along the continuum of likelihood of moving. Also we want to know how the characteristics of neighborhoods contribute to this distribution. Both of these aspects of migration are not only of interest theoreti-cally to increase understanding of the processes of change but also to the functionaries, planners, organizers, real estate specialists etc. who try to direct the processes through controls.

In this study we focus on household migration as a part of the ecological process which describes the dynamics of the city and on the classification of sub-areas within a metropolitan region to which an ecological description applies. The two lines of investigation are not merely parallel. After analyzing the two data sources separately,

the area data is superimposed onto the household data. Migration does have a direct effect on change within areas and different types of areas provide different pushes and pulls for potential movers.

The.direction of the analysis for this study followed from more than just an interest in the subject treated. A computer information system capable of handling and processing different data sources was available for use. Experience in the use of such a system is essential for an understanding of the problems of information retrieval and the development of urban data systems. A direct confrontation with the difficulties in handling data collected by different agencies, at dif-ferent times, for difdif-ferent purposes helped develop an appreciation of the immensity of the task of improving the state of the art of

social science research. The applicability of the experience gained by this study is far-reaching.

Those involved in seeking solutions to social problems and in im-proving city life are looking for new inputs to inform the decision making process. With new data sources appearing or being coordinated, new ways of handling the data must be employed. One such way is through

the use of sophisticated computer information systems. The tasks of description of process and evaluation of programs are both served by such a system.

In the next chapter several of the theoretical considerations on which the area classification attempt was based are mentioned. It

in-cludes an explanation of previous classification attempts and what they assume and use for data. The ecological background which supports these

-8-classifications is discussed. In addition, a review of several

migration theories and their origin in other disciplines along with a few illustrative research studies are included to provide a background for the analysis of movers in this study.

Chapter three includes the application of the mnlti-file handling computer information system to the problem. Two data formats are used: census population counts and categorical responses to a survey. The method used is based on the application of an information system in a

limited experiment in how a data bank can possibly be used in the processing of different kinds of data.

At the end of the paper a chapter is included on some of the problems and projected uses of data banks and information systems.

CHAPTER II

Area Classification and Residential Mobility: Literature

Ecological Theories and Research

Ecologists (30) assert that there are two basic processes that underlie and organize human life: competition and communication. Competition is the organizing process which connects man to man in the struggle for existence. Communication is the process which ties men into society. "Man as animal is organized competitively in the scheme of nature, but man as social being is organized cooperatively into groups through communication." By this reasoning, two basic types of data in human affairs are envisaged, the ecological and the social. However, the cultural framework in which these processes

occur is not accounted for. Human ecology must consider man in cul-ture not simply man in nacul-ture. To allow empirical verification the body of human ecological theory must use culture as a surrogate for the instinctive mechanisms used in explanations of animal societies from which all human ecology is derived.

MacKenzie (23) defines ecological process as the tendency in time toward special forms of spatial groupings of the units comprising an ecological distribution. Five processes comprise the system he sees: concentration, centralization, segregation, invasion and succession. Concentration is the tendency of an increasing number of persons to

-10-settle in a given area or region; concentration is a "community-making" process. He views segregation as concentrates of population types within the community, but the factors of selection for such concentrates are difficult to identify. Economic factors are usually accepted as the

basic attribute of selection and the agent of selection is land value. However, he makes no distinction between motivating factors and external

conditions. Segregation varies directly with income. Those bounded by economic factors are enclosed in areas of cultural heterogeneity; there is no choice. As one proceeds up the economic scale choices are

widened and an individual chooses an area he 'likest for cultural reasons, cultural homogeneity results.

Invasion is a process of group displacement and implies the en-croachment of one area of segregation upon anther, usually an adjoining area. Succession culminates in a climax condition of an equilibrium between the groups, competition diminishes and stability prevails. How-ever, there is no allowance in this theoretical structure for the dis-tinction between the character of these processes that take place in different sized areas. Applied to a nation the interpretation is dif-ferent from an explanation of how these processes occur within a single urban area. Not only is the scale different but the nature of the pro-cess is not the same. The notions of concentration and segregation are directly applicable within the framework of this study but

invasion-suc-cession have to be modified to be interpreted within the metropolitan area configuration. These processes are more directly applicable to new areas than to areas which are established and are undergoing less startling

While ecological processes represent physical movements, the ecological structure is a geometric confLiguration of spatial units. These spatial units are considered *natural areast and these areas are repatterned by constant growth and the continuance of the pro-cesses. Growth is expressed by the extension of the pattern out-ward in concentric circles or rings that make up the city, and the

growth has been characterized by a combination of the processes enumerated above. The division'of the metropolitan area into con-centric zones has been fruitful in showing how the influence of the city wanes with distance outward and is usually indicated by gradi-ents of the average value of many social variables. This configura-tion of the city has led to investigaconfigura-tions on many levels of the characteristics of these rings in terms of measurable traits. Two directions of approach have appeared in ecological classifications; some have divided an area into spatial sub-units and taken measures on variables within them; others have taken measures initially and shown how they are distributed in one of the ecological patterns.

The latter type of investigation has received considerable atten-tion since Shevsky and Bell (37) published their classificaatten-tion indices. Repeated attempts have been made to establish their method by repli-cating their experiment in different cities. Shevsky and Bell

pro-ceeded on a priori reasoning to determine social dimensions on the basis of which they could measure and classify census tracts into

ag-gregates. Tleir "postulates concerning industial society" are each aspects of the increasing scale of modern society viz. a change in

-12-complexity of organization. These aspects are used to identify the three dominant interrelated trends most descriptive of the changing character of modern society: 1) distribution of skills, 2) the or-ganization of productive socie'ty, 3) the composition of the

popula-tion. From these broad postulates together with the analysis of trends they propose three constructs to be used in the study of social differentiation and stratification. Social rank is a reflec-tion of the changing distribureflec-tion of skills; urbanizareflec-tion is derived from the changing structure of productive activity and segregation measures over population characteristics. On the basis of their constructs Shevsky and Bell formulated two hypotheses for their em-pirical verification of this theory: a) that the three factors are necessary to account for the observed social differences between urban sub-areas and b) that the indexes used to measure the three factors are unidimensional measuring instruments. The major objection to the

classification of areas by their scores on constructs is the inter-pretation of the construct itself. While constructs allow for more parsimonious description in that they replace a large number of vari-ables with a few complex factors, their interpretation is open to question since their component variables lack any theoretical meaning. Also the construction of these constructs arises from matrix algebra which is not tied to any subject matter.

Various techniques can be employed to reduce a number of variables to a few dimensions. Bell performed a factor analysis using these con-structs and &ensus tract data for Los Angeles and San Francisco. For each trend proposed, there is a set of census variables: 1) occupation,

schooling and rent for Social Rank, 2) fertility, women at work and single family dwelling units for Urbanization; 3) racial and national groups in relative isolation for Segregation. His findings support the first hypothesis but are not conclusive about the sufficiency of the indices for classification. In our study the constructs are not identified although many of the same variables appear. One major difference is the Segregation measure. Since we deal with 1960 data,

Segregation is better measured by socio-economic measures than national.origin. In 1940, measures of isolation of national groups was more defensible.

Tryon (43) approached his classification empirically without the theoretical base of Shevsky-Bell. His contention is that dimensions chosen on a priori grounds run the risk of being incomplete of inac-curate. From thirty-three census variables (almost identical with Bell's) he obtains seven initial clusters. From these seven he selects three final clusters which are independent. These clusterswhich he

calls social dimensions are socio-economic independence, a meaure of wealth and social independence, Assimilation refers to the degree of

incorporation of the population into 'middle class' culture. The third dimension differentiates tracts on the degree of familism ex-hibited. This empirical analysis was also performed on the 1940 cen-sus data for the cities of the San Francisco SMSA. There is much

repetition in the results and interpretation of the two approaches which may be considered corroboration of these constructs as valid for

classification. However, each of these approaches used a statistical technique which assumes independence of the variables; yet the notion of independence of variables used in these studies has not been questioned

_114-and evaluation of the procedures has been based on the empirical re-sults of using them. When several replications concur, reliability can be asserted but lack of consistency in the results can be due either to the procedures or to wide variation in the social charac-teristics in different cities. Unless the procedures are tested

rigorously, this approach to area classification cannot be univer-sally accepted.

Clarke (C), also using factor analysis, distinguished between static and dynamic factors arising out of combinations of census-type variables. He was concerned, as we are, with an ecological

description of the Boston area. His source was a transportation sur-vey done in the Boston region in 1963. The static factors he isolated are similar to Bell's and Tryon's factors but his dynamic factors con-cern the movement of populations. He mapped the scores of towns on both stable and dynamic factors to show where change was occurring.

The sub-area descriptions resulting from the approach in this study concur to a great extent with Clarke's findings; yet, the test of contribution to variance was not made here. Obviously, income and occupation account for sufficient variation for the comparison to be sustained.

must be included as a fundamental element comprising that process. In the context of urban areas, migration accounts forresidential change which is an essential element in the ecological process. The sources for migration theories have been provided from behavioral psychology

and elementary economics. Propositions connecting the stimuli a man receives frm his environment with his choices of courses of action have been borrowed from the field of perception. Homans (16) para-digmns this combination:

ECONOMICS PSYCHOLOGY

supply the more valuable the reward the more often the action is performed

demand the higher the cost incurred by an activity the less often it will be performed

In describing the actions performed in a system and the alternative sets of action not performed by a group of actors, Parsons and Shils

(31) support this argument. "The essential phenomena in motivational orientation are cognitive and cathectic discriminations among objects. Cathectic-cognitive orientation in any system of behavior extending through time always entails expectations concerning gratifications or deprivations receivable or attainable from certain objects. Action

involves not merely discriminations and selection between immediately present objects and the directly ensuing striving acceptance or rejection,

-16-but it involves also an orientation to future events with respect to their significance for gratification or deprivation." Beshers applies this idea of orientation to his description of movers in formulating models of movement for persons with different utilities and likeli-hoods for moving. Persons for whom the gratification received by moving is high are likely to move. Those for whom the gratification must be defered because of present circumstances (for example, moving to a large expensive home before income allows) assign a lower utility to such a move and are less likely to move. Another consideration is the relative weights of the cost of moving against the marginal reward of the proposed new place. The distinction made in the classification of households which follows on the basis of length of residence proposes to show how migration is indeed affected by costs of uprooting and overcoming the inertial forces imposed by long residence in one place.

The general migration theories that appear in the literature support this couination of cost and time orientation. Three general theories may be applied in a limited fashion to the migration which occurs within relatively small bounded areas: the Push-Pull socio-economic theory - migration proceeds from less to more prosperous areas;

it results from socio-economic imbalances between communities. Pulls are the rewards and incentives for moving and the pushes are more

closely related to the costs of remaining in the present place of resi-dence. The Size-Distance Gravitational theory - migratory activity arises out of the complex of forces centering around the cost of movement and the number of persons available to move. In this theoretical state-ment the supply-demand ratio of people available to move and the number

of places open introduces an element of competition whose resolution is accomplished by an assessment of costs and willingness to pay. The high bidders have the best competitive position.

The Intervening Opportunities theory - the number of persons going a distance is directly proportional to the number of opportunities at

that distance and indirectly proportional to the number of intervening opportunities. The notion of intervening opportunities is a direct benefit/cost assessment. A future orientation is implied in this stepping-stone movement.

These theories are helpful in explaining the general phenomena of migration. In the following - analysis they will be referred to in

support of the actions of households and also in the mapping of house-hold and area types. To understand the more specific motivation for movement closer attention is paid to the action of individuals

com-prising the movement flows. These are enumerated in the area called Household Classification.

Leslie and Richardson (20) propose a model for the explanation of voluntary residential mobility based on the stage of family in their life-cycle and mobility potential where the usual life-cycle variables, age, household size, are not considered useful in predicting but rather social mobility expectations, perceived class differences, education and house attitudes. These, correlated with mobility intentions, were good predictors. When life-cycle is accepted to be a cause of migration, it is not sufficient to explain location. That is, when faced with the need to move a family or individual has a choice within its financial means of many different locations, representing different kinds of

-18-places. While the reason for moving is stated, the reason for locating can only be inferred from the characteristics of the place moved to. Additional clues to location are provided by work place, information on

the institutional membership, 'location of friends and visiting patterns of migrants and also of the extent of their knowledge of options open to them. However, studies of these social patternings are not usually conducted in concert with migration studies, although it seems that co-ordination of these two kinds

of

information would be mutually supporting. The information system approach used here would facilitate that combina-tion of studies. Since explicit statements about motivacombina-tion for

migra-tion are usually derived from surveys rather than from any other source a few migration studies which investigated why people were moving are included here to show how slight differences in approach can lead to quite different results. Before general statements on motivation for migration can be accepted these differences will have to be recon-ciled either by incorporation into more general theories or by refine-ment into specific laws.

Since the data available was disappointing from the point of view of migration history and direction of movement the only comparisons that we could express were with Whitney and Grigg's and Rossi's findings.

In a study of patterns of mobility of families of college students Whitney and Grigg (45) broke moves into distant and local with the following accounts for the cause of the move:

Distance movers Local movers

90% economic 1%

3% status 90%

3.5% non-status 3%

Ross (34) suggests in a study of movers to and from a Central City Area that movers be classified by direction as well as distance. He generalizes to say that local movers are house-oriented while distance movers are convenience-oriented.

Bell (2) conducted a study in Chicago Suburbs to test his hypothe-sis that people move to the suburbs because they have chosen familism as an important element in their life styles rather than career or consumership. His findings support his hypothesis. Only about 10% of the respondents could be classified as having upward mobility aspira-tions, while 81% indicated that they considered their new locations

'better for children.' Rossi (32) has done the most comprehensive study into the motivation for migration. He studied areas as well as people classified as mobile and stable. According to Rossi the major function of mobility is to be the process by which families adjust their housing to the housing needs that are generated by shifts in their family composition thataccompany life cycle changes. The hous-ing aspects most sensitive to shifts in the family life cycle are those which tie in most closely to this life cycle interpretation.

In summary, we have looked at two areas of interest: classification of areas within metropolitan limits as these relate to and are based on ecological assumptions and at migration theories, their sources in other disciplines and a few of the empirical studies to support or explain these theories. This was included in order to put the following empirical work in some perspective.

-20-CHAPTER III

Area Classification and Residential Mobility: Empirical Work

Data Sources

Two files of information were available for this analysis:

1. A Census tape which contained population counts and medians for over 100 variables for 606 census tracts in the Metropolitan Boston area;

2. A tape of responses of 1341 individuals in 447 census tracts in the Boston SMSA to a questionnaire sponsored by the United Community Services.

Since the two files were to supplement each other only those tracts which appeared in both sets were scrutinized from the census tape. From the 109 original census variables 51 were chosen as relevant for this study. However, age data for the population over 20 was missing and a supplementary file of this data had to be punched from the census publications and mapped onto the master file. From this complete file of frequencies some categories were combined and others remained in their original form. Percentage values on 25 variables were calculated, and these percentage value categories together with original median

valued variables provided the basic input data for census tract analysis. The UCS file contained the responses of individuals to 274 questions. Fifty seven of these were selected for analysis and comparison with the census data, each of these being one category. Many of these were

redundant with census categories, e.g. age, sex, income, occupation and were included to provide a basis for matching, the remainder were supplemental categories which would add information to the match and provide explanations which are usually handled by infrence. This allowed us the latitude either to stop with this explanation or to go

to a highler level inference.

A distinction to be observed here is that the respondents on the two files represent different levels of aggregation. The responses in the UCS file are those of individuals interviewed in a survey while those of the Census file were the totals over all the individuals in the tract. Thus a one-to-many correspondence obtains between the two files.

The UCS file included measures on some variables for more than one member of the household interviewed. A cover interview was used for the selection of the actual respondent, and the responses of this individual were coded as Infrmant responses. The actual respondent was asked both for measures on himself and for the head of household. Since the head of the household is most like to affect moving deci-sions, income, occupation and sex and age of head of household were referenced rather than those of the respondent.

Initial Analysis Units of Analysis

The units of analysis for the first part of the study were the census tract. This was not a decision arising from choice but rather was dictated by the availability of computer readable data aggregated at that level. When one is concerned with the classification of areas

-22-one would choose to have data at the lowest level of aggregation so that clusters or groupings could be arrived at by decisions based on some criteria tested statistically to produce homogeneous areas. There has been extensive discussion of the non-homogeneity of census tracts and their incongruity with "natural areas." The notion of homogeneity has been the criterion for classification of sub-areas within a bounded area and the procedures for establishing whether or not homogeneity exists have varied in the different studies.

Homogeneity is a property of an area such that the distribution of specified population characteristics within that area will be found to exist in the population contained in any segment chosen from within

it. _{(It is recognized that there is a problem here of dealing with a} continuous distribution of attribute possession in a universe of dis-crete items.) _{For this reason the choice of the census tract is not} the best one. Census tracts were not defined on the criteria of homogeneity but the assumption of homogeneity underlies the approach of all classification attempts. That there is an almost inherent dilemma in setting out districts for measurement is understood. Some consistency of definition must be maintained to provide comparability of information over time, but on the other hand, the enumeration of districts in itself, should not be static because of the dynamics of the processes they are subject to.

The assumption of homogeneity in this work is not satisfying but since we have had some satisfactory results we can feel more comfortable knowing that with refined data more conclusive results can be achieved.

Initial Classifications

The analysis for this paper was restricted by the kind of theory

formulated in the fields of social area analysis and migration, the nature of the data available and the method of data analysis. Of

course, other limitations are implicit in that the perspective of one researcher is limited.

The Income and Occupation categories from the Census file were ordered into high medium and low valued intervals. The ADMINS instruc-tion INTERVAL takes as input numerical data and orders the entries from each respondent. The data is partitioned into n percentiles (here n

=

3) and a new category is produced the elements of which are those respondents which fall into each of the requested percentiles. Thus a nominal category is produced from a numerical one. For example, the instruction *Interval PCPROF (percent professional) 33 66 * results

in a new category where the three entries contain those census tracts in the low third, middle third,and upper third respectively, in percent professional among their population. The breakpoints calculated show that 114 tracts have between 1 and 6% professional, 160 tracts have between 6-12% professional and 157 tracts have over 12% professional.

Similar instructions were executed for all the income and occupation

categories yielding a trichotomy on each variable. Access to these

entries is gained by building indexes to them. An index is a pointer

to respondents which have certain specified characteristics. These

indexes can be combined to build complex groups. For example, the area definitions derived from the census data are the results of com-plex indexes built from the income and occupation categories. Simple

indexes were built to income level entries and percentage representa-tion in a given occuparepresenta-tion. These simple indexes were combined in Boolean intersections to yield complex groups representing different social class levels. Boolean intersection is the *and' operation of set theory which references those elements which are common to two given sets.

Subsequent analysis employed these indexes as the column and row entries in tables cross classifying them with other variables of interest. The approach used in the initial analysis of the UCS data was quite different from that used for the census data. Since the variables were nominal no numerical operations could be performed on them without detailed transformations. Before actually beginning the analysis of the data under the ADMINS system an intermediate summary file of marginals is produced, that is, an aggregate frequency for each response to a question. This information allows one to reassess

an analysis plan in response to patterns exhibited in these marginals. The marginals from the UCS file indicated that many variables should be

dropped because of small response. Most of the attitude and perception variables allowed for multiple responses but after perusal of the mar-ginals it was ascertained that in most cases only one response was given. For example, it was possible for a respondent to state five

improvements to his community.1 Although there is no direct indication of ranking of these improvements by the individual, it is assumed that he states them in the order of importance to him. However, only the

1 "Community" and "neighborhood" are used in the questionnaire; here they are extended to census tract.

first response category was large enough to include for detailed analysis. In the other four, more than half of the individuals gave no answer. The same situation occurred for the multiple responses for good things about the neighborhood where three out of seven possi-bilities were used; for bad things about the neighborhood, one out of three were used and for why move, one out of two. Altogether eleven variables were pared after inspection of the marginals.

The initial classification of individuals was accomplished by building complex indexes to them on the basis of their answers about

the length of their residence in the community and their plans for immanent moves. These indexes were then used as the column entries for tables of cross classification with other variables. Since the rows of the tables were nominal categories, indexes were not constructed for simple responses. The specification of the category name informs the system to report the cell entry for each response by each index. The cell entries are intersections of the row and column indexes and give clues for continuing the analysis. Indexes can be built to reproduce these intersections which can then be referenced and themselves be used as row or column specification in order to work through the data

for significant results. This is the procedure which was followed in order to investigate the nature of the groupings of individuals in the UCS file. For example, in the category RUNNERS a number of respondents

indicated dissatisfaction with the composition of the population of their neighborhood. In another table a significant number of RUNNERS indicated that they would move for financial reasons and to improve their physical surroundings. By building complex indexes to these

-26-different cell definitions, higher order intersections were performed to show that these answers were attributable to the same individuals. From this hierarchy of tables it was possible to describe the

charac-teristics of the individuals within each of the four classes.

The next stage of the analysis -involved the parallel analysis of the two files. Because the two files were not designed simultaneously2 nor intended to be mutually compatible, a basis for comparison and mapping had to be provided. Both files included a census tract cate-gory, that is, the unit itself in the census file was the census tract and in the UCS file each individual was located according his present census tract residence. However, in neither file was the actual census tract code used. Rather a numerical code was assigned to each

tract. Since the codes for the respective files were not the same, two cross reference files had to be constructed each relating a code set to census tract codes. Then the mutual occurrence of the census tract codes provided a common reference between the two main files. Using these constructed files as cross references the census variables which had counterparts in the file of individuals were mapped onto the UCS file. The resulting file contained for each individual his own

particular responses and also the characteristics of the census tract in which he is located. This combination allowed for the test of 'fit' of the individual within his surroundings.

2 _{Census in 1960} UCS in 1965

Area Classification

Social theory supports the notion that individuals and families ar-range themselves spatially in a metropolitan area in response to their perceived needs and desires and according to their recognized oppor-tunities. The component activities which manifest these specific needs and desires are termed life styles and populations differentiate within themselves along these lines. Measured along different sets of dimen-sions, a population will be classified into subgroups or types. Obser-vation alone without measurement allows one to conclude that different 'types' of people live in different 'types' of areas. A priori organiz-ing constructs are used to arrange these types into a coherent social structure. At this point measurement enters and an empirical verifica-tion of the proposed classificaverifica-tion is undertaken to determine whether differentiation which is perceived to exist actually does exist.

The assumption on which this classification of tracts within the Boston SMSA is based is that income and occupation are the primary distinguishing variables and that within groups of tracts claimed to be homogeneous on these two measures we will find consistent patterns of other socio-economic and demographic variables. The areas could not be described in terms of these extreme variables unless there was sup-port from other variables in the patterning. That is because other

areas may have similarly high or low values in these particular vari-ables and yet differ in their patterns on other characteristics.

It is reasonable to make this assumption. The division of labor is such that work is parceled out according to varying abilities and

-28-personal qualities of individuals. The evaluation of this work is manifest in the price that is paid for it and the degree of skill or expertise involved. Since this price is effectively income, the work-income combination is a prime determinant of where an individual can and will live. Also people engaged in similar pursuits tend to share values and attitudes. Communication between 'likes' is easier and

tends to reinforcement. Robert Tryon (37) included a third reason for recognizable differentiation, namely that people of a given

occupa-tion group, income and 'culture' are expected, as part of their social role, to live in certain areas.

For the purpose of differentiation in this study, four income groups and six occupation groups were identified. Each of these cate-gories was statistically subdivided into high, middle and low divisions on the basis of percent representation of each category in each census tract. Set operations were performed on the occupation subgroupings to isolate those census tracts where a predominant occupation category pre-vailed. For example, one table which measured the three levels of

representation of professionals against all the low subgroupings within the occupational structure showed a significant number of tracts with a high representation in professional and managerial population and a

low representation in laborer, as might be expected. All possible combinations of categories and subgroupings were calculated and signi-ficance levels computed. The clerical category proved to be a swing

grouping showing a high middle classification with all other occupa-tions. Since this group did not distinguish well it was not used for further classification. The remaining occupational categories were

combined in Boolean intersections with the income categories to produce the definition of areas. Four distinct area groupings were drawn on the basis of these criteria accounting for 325 of the tracts. A fifth classification group of residuals, not identifiable on the income-occupation breakdown, was included.- Although the tract tape included 606 tracts, 129 of these were not included because they did not appear in the UCS data set (also they lie outside the Boston SMSA).

Results from this classification showed the following patterning of variables. The four identifiable groups of tracts were named:

UPPERS - those 112 tracts with a high percentage of professional and managerial population and a high percentage of high

income persons (income over $10,000)

It was expected that another category of what I would call aspiring uppers would emerge characterized also by a high percentage of profes-sionals and managers but with lower income. These people would be younger and starting their professional careers. However, of the 67

tracts where these characteristics appeared 65 were already classified as uppers. (It was decided after inspection of the supplementary vari-ables that a tract would be included in the highest category which described it.) This can be explained in that the life styles of these

two groups are very similar - they are only in different life cycle stages which need not preclude close association and since census tracts are not wholly homogeneous, some of the variation within can be ac-counted for by differences in cost and size of housing.

MIDDLES - tracts where a high percentage of skilled workers earned $7,000-$10,000. Of the 90 tracts which

-30--resulted from this intersection, 22 were also in-cluded in the upper category, so the remaining 68 tracts comprise this group.

WORKERS - (lower middle class) is characterised by a high percentage of semi-skilled workers who are in the $3,000-$7,000 income category. Only 2 of the 91

tracts so classified were included in the next highest group.

LOWERS - are those where a high percentage of laborers are intersected with tracts showing a high percentage in the poverty income category (under $3,000). The first calculation shows 110 such tracts, however,

54 of these were also classified as working class. A fifth catch-all category of tracts was named:

RESIDUALS - those tracts of interest not included above.

The redundancies in definition show an interesting split. There is a much stronger line between the MIDDLE group and the WORKERS than was expected. Their intersection contained only two census tracts. This split ilustrates the ecological processes of concentration and

segregation. The segregation is enforced by the pattern of the residual areas.

Both the absolute number of tracts and the percent of the total represented by each group show again the advantage of choice for the upper groups (Table 1). Although the tracts are not units of equal size, the disparities in size contribute to the advantages of the well-to-do

a few smaller areas characterized by higher density. The variety of locations open to the rich supports the differentiation of cultural types within the upper groups so that choice of a location is also a choice of association. For the lower groups cultural heterogeneity is imposed by the obviously limited choices.

As in all other classification attempts, the effort here was directed at maximizing the between-group variation and minimizing the within-group variation. Here the hypothesis is stated in terms of social structure and is measured by structural variables. Inferences to

pattern-ing follow the social structure. Structure is defined to be a pattern at one time which persists over time. In order to manifest this struc-ture the values of the variables within the groups of the classification must cluster around a value which appropriately describes the group. Otherwise it cannot be a measure of the social structure (or else the

classification is inaccurate). Social characteristics have a persis-tent pattern among themselves and so have a persispersis-tent spatial distri-bution. However. the pattern of this distribution may change, the relationships remain constant. This reflects MacKenzie's proposition that groups have a tendency in time to spatial groupings. Means of values of other variables over the subgroupings were calculated to

exhibit the between group differences and to help derive some defini-tion for the residual category. The variables can be sorted into physical (and/or' house-related) and socio-economic (see below). The demographic variable of age distribution showed so little variability between groups that it was not included.

DISCRIMINATING AND SUPPLEMENTARY VARIABLES

Physical (House Related) Socio-economic 1. median value of owner occupied homes 1. percent high income

(over $10,000) 2. percent owner occupants 2. percent middle income

($7000-10,000)

3, percent single family homes 3. percent lower middle income ($3000-7000)

4. percent 2-4 family homes 4. percent low income (under $3000)

'5. percent homes with 5+ units 5. percent professionals

6. median rent 6. percent managers

7. percent skilled workers 8. semi-skilled workers

9. percent laborers The differences between the means of the variables (Tables 1 and. 2) are great enough to support the classification and are consistent with social theory throughout. The composition of the housing available in each type of area is a good discriminant and the amount of home-owner-ship is directly related to the number of single family and 2-4 unit homes, except in the lower area. It is well known that absentee land-lords own substantial holdings in low income areas. Middle and Working class use ownership of income-producing property as a means for mobility to better areas or to single family homes. The types of housing which are found in the lower groups discriminate better between them than any value measure. Multi-family homes are more predominant in the lowest

type of area, whereas 2-4 family homes are more common in the working class area.

Among the socio-economic variables the interesting observations are the 'what else' occurrences over and above the variables on which the original cuts were made. The discriminating variables account for

but the off-diagonal or contiguous categories are interesting. It was expected that no jumps would occur and that we would approximate a

continuous distribution as we proceeded from one group of areas to the next. This assumes that people are located on a socio-economic

con-tinuum. However, in the occupational groupings a marked split is observed between those represented in the upper tracts and those in the lower

three. There is a strong white-collar blue-collar dichotomy. Some of this distinction may be accounted for by the absence of the category of clerical workers. Since this variable was not helpful in discriminating it was not carried through. Perhaps this was an unpardonable omission. The occupational distributions support more closely the basis for the classification than do the income distributions. Occupation is often used as a surrogate for life style and if the proposition that persons separate themselves according to life style preferences is true, then

-34-TABLE 1

PHYSICAL VARIABLES BY AREA TYPES

number of tracts 112 % of total tractsi (.2)4) a -1. 2.

3.

4.

6.

UPPERS MIDDLES WORKERS LO'WERS

68

(.14)

89

(.19)

$20666

$114198

$8293

.72

.74

.16

.09

.64

.39

.04

.30

.17

.65

.16

$64

$60

54

(.11)

RESIDUALS

152

(.32)

$8138

$12887

.24

-17

.50

.32

$47

.38

.39

.43

.20

TABLE 2

SOCIO-ECONOMIC VARIABLES BY AREA TYPE

number of tracts % of total tracts 1.

2.

3.

6.

5.

6.

7.

8.

UPPERS MIDDLES WORKERS LOWERS RESIDUALS

112

(.24)

.35

.34

.26

.o6 4.19

.16

.13

.07

68

(.14)

.15

.29

.46

.08 .09

.07

.22

.15

89

54

(.19)

(.11)

.09

.18

.54

.17

-04

.0)4

.17

.22

.02

.04

.07

152

(.32)

.16

.22

h5

.13

.08

.o6

.10

.09

.09

.16

.28

-05

.03

.12

.17

.o8 .02

9.

-36-The groupings as defined for this paper are mapped (see Maps 1 and 2) for comparison of these results against the usual ring and sec-tor groupings. As mentioned above, the basis for aggregating in this analysis is socio-economic and not geographic. Allaman (A) in his Massachusetts Institute of Technology Masters Thesis proceeded on a

geographic basis to divide this same study area into rings and sectors 'and then investigated the pattern of occupation distributions within

these area groupings. He also compared the pattern of the rings and sectors to the pattern of variables in the area as a whole. Within each area he computed the averages of percent distribution of occupa-tions to show their central tendency. He concluded that there are dif-ferences between the geographically defined areas but also there are significant variations in the distributions within each area which are not manifest in his results. Our approach responded to this conclusion and rather than continue on the assumption of geographic differentiation derived a spatial patterning from the social patterning. The results do indeed indicate the within-area variations, especially within the sectors. The outermost ring of the area conforms with both Allaman's

results and Clarke's (C) findings of high factor scores for his income-occupation factor concentrated in the western part of the metropolitan area. In fact, the patterning resulting from the differentiating tech-nique used in this paper is very similar to the patterning found by Clarke for his Static Factor 2 - Income-Occupation, throughout the area. An attempt was made to perform a pseudo-regression on the supplemental

'Pseudo-regression,' in that a correlation matrix was not used but rather differentiating values of the variables were combined and tracts measured on them individually and cumulatively. Because of the mechan-ism used to discriminate in the ADMINS system the results were incon-clusive and so are not included here.

That there is corroboration on some of the results from this ap-'proach _{with those where other hypotheses directed the technique applied,}

is again a restatement of the interdependence of the processes within the urban system. A methodological implication is that there may be more than one 'correct' operational definition of a concept, depending on certain theoretic assumptions. Substantively, the results correspond quite accurately with the ecological divisions based on segregation and concentration.

-38-MAP 1

Types of Areas Outside Boston City

Inse B; _{Iynn City}

1; C- Malden and Medford

Types of Arcas Outside Boston City Inser B; lgnn City Malden Medford Insert D-Walthan

IN

S~Go"

-39-KAP 2 Types of Areas Boston City g0 Isert A ownm m* m Pm a

PESMIDDLES WORKERS LOWERS RESIDUALS

Household Classification

The census data provided inputs in the form of counts and medians over tracts. ADMINS handled these categories as numerical data. In the UCS survey the inputs are categorical and the summarization pro-cedures for categorical data are different from the summarization procedures for numerical data. The analysis of the UCS survey pro-vided a test for these procedures.

Few studies use individual households as the units for residential mobility analysis. Rather they depend on the measures of mobility of aggregates from the census. Availability of data is probably the

reason. However, census data can only give socio-economic descriptions of flows which is helpful for large area analysis, but cannot isolate

reasons for the flows nor attitude nor expectation, which is another way of characterizing the flow. Residential mobility is the compounded resultant of thousands of individual residence shifts. Looked at from the point of view of the individual household, moves can yield a valu-able set of data concerning the social psychological factors underlying

residential mobility.

Rossi (35) speaks of inclinations toward mobility as a continuum along which we will find people who are on the point of moving, those who expect to move sometime in the future and those who are planning never to move from their present residence. How are these types

dis-tinguished from each other? In order to answer this question two ap-proaches are taken; one, a look at the characteristics of the household itself, and also at its attitudes about its living situation. These will

be considered under the general headings of attributes and attitudes of households.

The variables which measure movement were used to classify indi-viduals. Four groups were isolated on the basis of their answers to two questions: How long have you lived in this community? Do you ex-pect to move in the next two years?l

How long here?

less than more than

5 years 5 years

yes RUNNERS CHANGERS

Expect (110) (138)

to

move? no STAYERS SEWTLERS

(206) (737)

RUNNERS: were those who had lived in the area for less than 5 years and who planned to move within the next 2 years CHANGERS: had lived more than 5 years in the area but were

planning to move out within the next 2 years

STAYERS: had recently moved into the area and did not antici-pate another imminent move

SETTLERS: were those who had lived in their neighborhood for a long time and planned to remain there.

These categories were used throughout the analysis of individuals, and at a later stage the Stayer and Settler categories were sub-classi-fied using a third question about remote plans: Do you plan to live in

1 _{Actual mobility in this study is in part established and in part} pro-jected. There is no possibility of closing the gap between what is expected to happen and what actually does happen without a follow-up

this house indefinitely? Those who indicated that they *might move some-time' were scrutinized for anticipated reasons and these were compared with the reasons given by the group as a whole. Note though that this

is a house related question and the answers corresponding were also house related. Within this data set both attitude variables and attri-bute variables for each household are provided. From the analysis of these variables we can be explicit in interpretation rather than rely on inference.

Charts 1-3 indicate differences found between the groups on the attitude variables. By reading down the columns we can see the simi-larities between groups, the kind of attitudes shared by both movers and non-movers. Across the rows we can read the between group differ-ences. Answers referred to the social situation, physical condition and provision of services within the areas. (Open ended questions were asked and respondents interpreted them differently.) The assumption made here is that the attitude stated indicates that aspect of housing/ location which is most pertinent to the type of respondent. In describ-ing the patterns of responses, the four classes of movers/non movers will be referred to as representing movers 'from' (Runners and Changers) and movers 'to' (Settlers and Stayers) where the Settlers are a special case of movers 'to'. This approach departs from the usual stayer-mover distinction and explains more of the variation among movers than that usual dichotomy. We will also demonstrate that helpful information can be ganed if we measure frequency of movement. Reasons for moving are closely associated with attitude toward neighborhood, but neighborhood conditions explain only a part of the motivations for moving. Reasons

for moving also arise from the life cycle of the family. Of course, attitude and attribute variables are closely related. Leslie and Richardson (20) ignored life-cycle or attribute variables in their proposed model for predicting mobility and supplied instead,

per-ceived class differences and house attitudes and social mobility expectations. Although our variables are not in perfect congruence with theirs a correspondence exists. Perceived class differences are

included in the category of social attitudes and house attitudes ap-pear in the category of physical aspects rebting to property condi-tions. House attitudes have both family-cycle and social implicacondi-tions. Specifically, as families increase in size, their attitudes toward

their housing changes either because of its size, type or location. When correcting for the expansion of the family, a household may or may not also correct for better social conditions, depending on present income and expected future income. Improved social conditions usually imply a status change. Beshers (3) accounts for household composition also in status related moves. Families with daughters will maximize on social activities while those with sons will seek good educational facilities.

Chart 1 displays the type of responses to the two questions relat-ing to negative aspects of the neighborhood. The answers to the ques-tion on bad things about the neighborhood and desired improvements were combined in one chart since they reinforce each other. Although all four groups have complaints about the physical aspects of their location, the specifics of the complaints are related to length of residence. The cell entries for the attitude charts can be explained in terms of the

the movers *from' will correct the disadvantages of their present place by their move while maintaining its assets. Their maximum solu-tion will be to maximally overcome the bad aspects and minimally compro-mise on the good aspects. For the movers 'to' we will assume that

their satisf4ing trade-off is exhibited in their statements about good and bad aspects of their residence. The clustering of complaints shows that the Changers and Settlers have similar problems. Both of these groups have lived over five years in their present Community and their

complaints reflect their acquaintance with disadvantages that are not directly observable. Especially noticeable is the complaint of the Changers about the social aspects of their neighborhood. They would prefer other neighbors either because people moving into the area are undesirable or because they have bettered themselves and prefer

associ-ates of 'their own kind.' Both groups indicate dissatisfaction with recreational and entertainment facilities. For the Settlers this may be associated with the inconvenience of their location and for Changers with the complaints about child-raising. Settlers who have had a chance

to participate in local functions see a need for improvement in local government. Usually participation follows acquaintance with neighbors and desire to control to some extent decisions which serve personal and community interests. Settlers have a vested interest since they have made a commitment over many years.

.-1 ,

-the Runners. Runners have a limited commitment to -their residence place. Their complaints are directly observable and refer to the physical condition of the housing they inhabit. Since they have only made a stopover at their present residency they have little chance to probe into other aspects.

Comparison of the Stayers with the movers 'from' helps explain both the notion of pushes and pulls and of satisficing.. The pull of the desirable people in their new location is in direct response to the push of the undesirable people whom the Changers complain about. But the inconvenience of their new location was a compromise for the Stayers. Movers *from' have enjoyed the convenience of their present location. Stayers are willing to lose on the side of convenience in order to satisfy social aspects considered more important to them. Since they plan to stay in their new location for a considerable period, inconven-ience will probably be measured by longer commuting time and distance to work and shopping. Schnore (3 ) projects this trend one step fur-ther in stating that transportation may well allow for reduced migra-tion. Settlers also indicate inconvenient location and a willingness to endure it, reinforcing the trend to commuting.

By extending the comparison shown in Charts 1 and 2 of the Stayers who have just completed a move and the movers *from? who are about to

move, we can cite another trend: a commitment to familism or a child-centered life is indicated in the trade-off scheme. Convenience for parents is sacrificed for a location considered better for child-raising.

If the 'from' 'to' dichotomy is considered to be complementary then the complaint of the 'froms' about the condition of property will be