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
JUN 2 7 1968
Room 14-0551
ITL *rre
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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 investigated 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 residence 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.
TABLE OF CONTENTS
ABSTRACT
ACKNOWLEDGEMENTS+
TABLE OF CONTENTS
LIST OF TABLES AND CHARTS
CHAPTER
INTRODUCTION
6
AREA CLASSIFICATION AND RESIDENTIAL MOBILITY
Literature
9
I.
II.
Ecological Theories and Research
Migration Theories and Research
AREA CLASSIFICATION AND RESIDENTIAL MOBILITY
Empirical Work
III.
IV.
V.
9
15
20
Data Sources
20
Initial Analysis
units of analysis
classification
initial
21
21
23
Area Classification
27
Household Classification
40
Area-to Household Mapping
53
THE USE OF INFORMATION SYSTEMS AND THEIR
CON1RIBUTION TO CITY PLANNING
63
CONCLUSIONS AND SUMMARY
70
Notes on the ADMINS System
List of Census Variables
List of UCS Variables
71
78
80
APPENDICES
BIBLIOGRAPHY
LIST OF TABLES AND CHARTS
PAGE
TABLES
1.
Physical Variables by Area
2.
Socio-Economic Variables by
Area
Type
34
35
Type
3.
Census Tract Values and Individual
Values for Types f Mtevers
59
4.
Distributions of Types of Mevers
Within Types of Areas
61
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
Boston Area Census Tracts
62
1.
Types of Areas Outside Boston City
38
2.
Types of Areas Within Boston City
39
CHARTS
MAPS
ACKNOWLEDGEMENTS
The author wishes to thank the following persons who have contributed 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 transformation of land from one use to another.
These changes
are due to mass movements of people and the mass movements are comprised 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 theoretically 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.
not merely parallel.
The two lines of investigation are
After analyzing the two data sources separately,
-7-
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 different times, for different 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 improving 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.
-9-
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.
men into society.
Communication is the process which ties
"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 nature.
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-
concentration is
a "community-making"
settle in
a given area or region;
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.
economic factors are enclosed in
Those bounded by
areas of cultural heterogeneity;
there
As one proceeds up the economic scale choices are
is no choice.
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,
area.
Succession culminates in
between the groups,
usually an adjoining
a climax condition of an equilibrium
competition diminishes and stability prevails.
How-
ever, there is no allowance in this theoretical structure for the distinction 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-succession 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
modifications.
-ll-
While ecological processes represent physical movements,
ecological structure is
the
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 processes.
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 gradients of the average value of many social variables.
This configura-
tion of the city has led to investigations 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 attention since Shevsky and Bell (37) published their classification indices.
Repeated attempts have been made to establish their method by replicating 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 aggregates.
Tleir "postulates concerning industial society" are each
aspects of the increasing scale of modern society viz. a change in
the range and intensity of funtions, differentiation of function and
-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 population.
From these broad postulates together with the analysis of
trends they propose three constructs to be used in
social differentiation and stratification.
the study of
Social rank is
a reflec-
tion of the changing distribution of skills; urbanization 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 ema) that the three factors are
pirical verification of this theory:
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 interpretation of the construct itself.
While constructs allow for more
parsimonious description in that they replace a large number of variables 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.
structs and
Bell performed a factor analysis using these con-
&ensus tract data for Los Angeles and San Francisco.
each trend proposed, there is a set of census variables:
1)
For
occupation,
-l3-
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.
difference is the Segregation measure.
One major
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 inaccurate.
From thirty-three census variables (almost identical with
Bell's) he obtains seven initial clusters.
three final clusters which are independent.
From these seven he selects
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 exhibited.
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 results 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 characteristics in different cities.
Unless the procedures are tested
rigorously, this approach to area classification cannot be universally accepted.
Clarke (C), also using factor analysis, distinguished between
static and dynamic factors arising out of combinations of censustype variables.
He was concerned,
description of the Boston area.
as we are, with an ecological
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 concern 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,
of contribution to variance was not made here.
Obviously,
the test
income and
occupation account for sufficient variation for the comparison to be
sustained.
Migration Theories and Research
If ecology is considered as a description of process then migration
must be included as a fundamental element comprising that process.
In
migration accounts forresidential change
the context of urban areas,
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 likelihoods 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 residence.
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
-17-
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
hold and area types.
the mapping of house-
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
social mobility expectations,
house attitudes.
predictors.
is
predicting but rather
perceived class differences,
education and
These, correlated with mobility intentions, were good
When life-cycle is accepted to be a cause of migration, it
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 coordination of these two kinds
of
information would be mutually supporting.
The information system approach used here would facilitate that combination of studies.
Since explicit statements about motivation 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 reconciled either by incorporation into more general theories or by refinement 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
90%
3%
3.5%
3.5%
economic
status
non-status
dissatisfaction
Local movers
1%
90%
3%
6%
-19-
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
consumership.
their life styles rather than career or
His findings support his hypothesis.
Only about 10% of
the respondents could be classified as having upward mobility aspirawhile 81% indicated that they considered their new locations
tions,
'better
for children.'
Rossi (32)
has done the most comprehensive
study into the motivation for migration.
people classified as mobile and stable.
function of mobility is
He studied areas as well as
According to Rossi the major
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
work in some perspective.
order to put the following empirical
-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
-21-
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 decisions, 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 discrete 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.
-23-
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.
entries is gained by building indexes to them.
Access to these
An index is a pointer
to respondents which have certain specified characteristics.
indexes can be combined to build complex groups.
For example,
These
the
area definitions derived from the census data are the results of complex indexes built from the income and occupation categories.
Simple
indexes were built to income level entries and percentage representation in a given occupation.
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 marginals it was ascertained that in most cases only one response was
given.
For example, it was possible for a respondent to state five
1
improvements to his community.
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.
-25
first
response category was large enough to include for detailed
analysis.
no answer.
In the other four, more than half of the individuals gave
The same situation occurred for the multiple responses
for good things about the neighborhood where three out of seven possibilities 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
immanent moves.
the community and their plans for
These indexes were then used as the column entries for
tables of cross classification with other variables.
the tables were nominal categories,
simple responses.
Since the rows of
indexes were not constructed for
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 characteristics of the individuals within each of the four classes.
The next stage of the analysis -involved the parallel analysis of
the two files.
2
Because the two files were not designed simultaneously
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
UCS file.
the file
of individuals were mapped onto the
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
-27-
Area Classification
Social theory supports the notion that individuals and families arrange themselves spatially in a metropolitan area in response to their
perceived needs and desires and according to their recognized opportunities.
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 classification 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 support from other variables in the patterning.
That is
because other
areas may have similarly high or low values in these particular variables and yet differ in their patterns on other characteristics.
It
is
is
reasonable to make this assumption.
such that work is
The division of labor
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 occupation group, income and 'culture' are expected, as part of their social
to live in certain areas.
role,
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 prevailed.
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 significance levels computed.
The clerical category proved to be a swing
grouping showing a high middle classification with all other occupations.
Since this group did not distinguish well it was not used for
further classification.
The remaining occupational categories were
-29-
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.
classification group of residuals,
occupation breakdown,
606 tracts,
A fifth
not identifiable on the income-
was included.-
Although the tract tape included
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 professionals 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 accounted 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 included 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
(see maps 1 and 2).
The two lower groups find themselves confined to
-31-
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.
ing follow the social structure.
Inferences to pattern-
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 persistent spatial distribution.
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 definition for the residual category.
physical (and/or' house-related)
The variables can be sorted into
and socio-economic (see below).
demographic variable of age distribution showed so little
between groups that it
was not included.
The
variability
DISCRIMINATING AND SUPPLEMENTARY VARIABLES
Physical (House Related)
Socio-economic
1.
median value of owner occupied homes
1.
2.
percent owner occupants
2.
3,
percent single family homes
3.
4.
percent 2-4 family homes
4.
5.
6.
7.
8.
9.
'5. percent homes with 5+ units
6. median rent
percent high income
(over $10,000)
percent middle income
($7000-10,000)
percent lower middle income
($3000-7000)
percent low income
(under $3000)
percent professionals
percent managers
percent skilled workers
semi-skilled workers
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-ownership 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.
type of area,
Multi-family homes are more predominant in the lowest
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
strong representation in
the two categories but the *rubbing elbows'
phenomena can be seen by including other variables (Table 2).
The
original cuts exhibit themselves here as is necessary for consistency
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
the results here serve as further confirmation.
-34-
TABLE 1
PHYSICAL VARIABLES BY AREA TYPES
UPPERS
112
number of tracts
% of total tractsi (.2)4)
a
RESIDUALS
WORKERS
LO'WERS
89
54
(.14)
(.19)
(.11)
$114198
$8293
$8138
.64
.30
.24
.38
.17
-17
.39
MIDDLES
68
152
(.32)
-
1.
$20666
2.
.72
3.
.74
4.
.16
.39
.65
.50
.43
.09
.04
.16
.32
.20
$64
$60
6.
$47
$12887
-35-
TABLE 2
SOCIO-ECONOMIC VARIABLES BY AREA TYPE
UPPERS
MIDDLES
number of tracts
112
68
% of total tracts
(.24)
WORKERS
LOWERS
RESIDUALS
89
54
152
(.14)
(.19)
(.11)
(.32)
1.
.35
.15
.09
.09
.16
2.
.34
.29
.18
.16
.22
3.
.26
.46
.54
6.
.o6
.08
.17
.28
5.
4.19
.09
-04
-05
.08
6.
.16
.07
.0)4
.03
.o6
7.
.13
.22
.17
.12
.10
8.
.07
.15
.22
.17
.09
9.
.02
.04
.07
.o8
.02
h5
.13
-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 occupations 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 incomeoccupation 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
variables to test their value for predicting the socio-economic groupings.
-37-
'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.
ism used to discriminate in
the ADMINS
Because of the mechan-
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
Insert D-Walthar
-38-
a
}!APl:i
Types of Arcas Outside
Boston City
Inser
B; lgnn City
Malden
Medford
Insert D-Walthan
IN
S~Go"
PPERS
MIDDLES
WORKERS
LOWERS
RESIDUALS
-39-
KAP 2
Types of Areas
Boston City
g0
Isert A
ownm
m*
Pm
PESMIDDLES
WORKERS
4
LOWERS
m
a
RESIDUALS
-0-
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 procedures 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.
reason.
Availability of data is
probably the
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,
way of characterizing the flow.
which is
another
Residential mobility is the compounded
resultant of thousands of individual residence shifts.
the point of view of the individual household,
Looked at from
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.
tinguished from each other?
How are these types dis-
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 individuals.
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?
Expect
to
move?
less than
5 years
more than
5 years
yes
RUNNERS
(110)
CHANGERS
(138)
no
STAYERS
(206)
SEWTLERS
(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 anticipate 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-classified using a third question about remote plans:
1 Actual mobility in
this study is
Do you plan to live in
in part established and in part proclosing the gap between what is
of
possibility
no
is
jected. There
does happen without a follow-up
actually
what
and
expected to happen
individuals.
same
the
study of
-42-
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.
these variables we can be explicit in
From the analysis of
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.
ences.
Across the rows we can read the between group differ-
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.
be ganed if
We will also demonstrate that helpful information can
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.
attitude and attribute variables are closely related.
Of course,
Leslie and
Richardson (20) ignored life-cycle or attribute variables in their
proposed model for predicting mobility and supplied instead, perceived 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 appear in the category of physical aspects rebting to property conditions.
House attitudes have both family-cycle and social implications.
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.
imply a status change.
Beshers (3)
also in status related moves.
Improved social conditions usually
accounts for household composition
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 relating 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.
cell entries for the attitude charts can be explained in
The
terms of the
push-pull migration theory.
Pushes are the bad things or the aggra-
vating circumstances inducing a move and pulls are the attractions of
an area or the gratifications attained by moving.
We canvssume that
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 compromise 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 associates 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.
The length of residence shows its
other side in
the responses of
.-1,
the Runners.
place.
-
Runners have a limited commitment to their residence
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, inconvenience 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 migration.
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
L
corrected in theirnove.
Also a pattern pointed out by Whitney and Grigg
(42) is exhibited here.
A majority of the Runners have come from out
of state.
Initially they moved in to areas convenient to their activi-
ties (probably near to work place) but their next move will be to
improve their physical surroundings.
In their study, Whitney and Grigg
concluded that a long distance move is followed by one or more local
moves and that the local moves are house-oriented.
In comparing the attributes of the groups, length of residence is
not a significant variable.
The stage of career or life cycle is more
indicative of moving status.
Chicago that changes in
Duncan (8) found in a study of families in
residential patterns tend to occur for groups
whose relative socio-economic status is changing.
our results.
This is confirmed by
Runners and Stayers are young professionals whose income
is relatively low now but whose high-income potential is high.
When the age of the youngest child and the size of the household
are combined for comparison we see further indication of different life
cycle stages for the Runners and Stayers, and Gangers and Settlers.
Runners are adjusting to the needs of their newly expafiding family.
They have onlycne young child.
ment.
Their move will be to a larger apart-
Stayers, though, are adjusting to their completed family.
They
have bought a single family home to accorwdate their family of two or
three children.
The Settlers have also completed their family and their
children are older.
The type of housing and tenure status of the movers support each
other in that multi-unit houses provide units for rent and those who
move often usually prefer the convenience of renting.
-47-
Rossi (32) makes the observation that tenure is a complex variable
having an attitudinal aspect expressing how a household regards its
housing in terms of rejection or acceptance of the high valuation placed
on home ownership in this country.
In part, the type of dwelling is
directly related to tenure status.
Rental units have different charac-
than owner-occupied units.
teristics
reflected in
And the commitment t6 a unit is
the tenure status of its occupant.
However,
the response
to the Why move question reveals that many renters move specifically
to change their tenure status from renter to owner.
related to life cycle stage.
Tenure may be
When moves are most frequent in early
family formation years, rental status is more convenient.
By looking at the composition of the housing available in the
tracts where different types of households live we can confirm some of
the observations made above.
Stayers show a strong preference for areas
where single family homes predominate.
The tenure status of stayers
corresponds with the percent of single family homes in the tracts where
they are located.
Runners live in areas where multi-unit structures
comprise the housing stock.
The overwhelming majority of Runners are
renters but the tract value for tenure does not reflect this.
Changers
occur in tracts showing a similar distribution of housing types as
Runners.
Studies which treat mobile vs. stable areas usually suggest that
the dichotomy is based on the type of people who live in an area.
Our
dichotomy looks at mobile vs. stable people and the results show that
the composition of housing types in an area is a strong indicator of the
types of people who will live there.
The mobility of the households is
a reflection of the transitional stages in their life/career cycle.
They will change their status to stayer after sufficient housing adjustments have been made.
The area from which they came, however,
will continue to be considered mobile because other transitional households will find the housing it offers satisfactory for their present
purposes.
Chart 3 shows the reanns why households move with respect to the
attitudes and attributes mentioned above.
The rationality of a move
for any individual can only be hinted at here because we don't have any
housing market data.
When a household gives reasons for moving which
are related to the disadvantages of his present neighborhood and actually moves to a location where he can overcome these and still maintain
or improve upon the assets of his old neighborhood it is said to act
rationally.
The reasons shown in Chart 3 are consistent with the at-
titudes and attributes of the four types of households.
behavior are stages in a connected sequence.
Motivation and
In order to understand
the action we must find out what conditions precipitated the moving
action.
Here we have two sources of information.
The attitudes and char-
acteristics of the households give a clue to possible motivations for
moving.
To the extent that they are supported by the actual reasons
given for moving we can use them as surrogte variables when reason data
is not available.
Reasons for moving are coded into broad categories
but can be compared against the categories of the other attitude data.
One shortcoming of measuring reasons for moving before a move without a
follow-up interview is
in
the assessment of the importance of the reason
given by a household head as the force actually bringing about the action.
Also reasons are directly related to the knowledge an actor has about
the choices open to him.
All types of households unanimously agree that they would move
if
. their job demanded it.
'
Runners and Changers have more reasons for moving, an indication
of support for the relation of reasons to changes in
either short-term or imminent.
behavior that are
The reasons have been classified to com-
pare with the measures of households discussed earlier.
Changers exhibit corrective reasons for moving.
Runners and
They strongly support
home-ownership and are moving specifically to change their tenure.
Stayers and Settlers already own their own homes.
On reasons for mov-
ing explained by the attitudescf households the movers 'to' respond in
terms of luxuries while the movers *from' are still correcting for
necessities.
Status moves follow after all other requirements have
been satisfied.
Because Stayers and Settlers are also less eager to
move, status may be less of an incentive than aggravation to generate
a move.
Initial forces against moving build up with long residence in
one place.
Changers are overcoming this force because of dissatisfaction.
From this brief analysis it can be concluded that valuable information can be gained by refining the stayer-mover dichotomy.
Movers dif-
ferentiate according to whether they are moving to or from an area.
Length of residence has significant effects on attitudes of households
and reasons for moving (or not moving).
Also it appears that there is
a social psychological order to the ongoing movement of urban populations.
Although the results here are merely descriptive they do provide
direction foi research in a more rigorous hypothesis-testing situation.
__
_..&WWWft_
-50--
CHART
1
NEGATIVE Attitudes Toward Neighborhood
Improverler
Physical
Social
ad thing s
property
RUNNIERS
cond-ition
from
property
C-HANIGERS
cople
composition
of nghbhd
bad for child
STAYEIRS
inconvenience
to
SET TLERS
CHART 2
Positive Attitudes Toward Neighborhood
Good Things
P
Social
convenience
children
HUYNNERS
Services
recreation
entertainment
from
convenience
CHAN~GEIRS
STAYEIS
housing
people
condition
child-rearing
to
housirg
condition
people
child-rearing
SETTLERS
Ct
I
-52-
CHART 3
Reasons for Moving
ATTITUDES
ATTRIBUTES
Job
Family
size
RUNNER
x
x
x
x
CHANGER
X
X
X
X
PAN
Status
Tenure
Diss atis
fact ion
People
X
I
STAYER
X
X
SETTLED
x
x
-~~~~~u
am
mopitF-
-
V"I
m
--
---
4
,i
m
n m
m
m.
Area-to-Household Mapping
A primary task of this study is to adapt the instrument of an
information system to two disparate files of information.
In order
to explore the available data a main emphasis of this research was
methodological and an attempt to produce an example of how new systems can be employed in the study of social data.
The design was
constructed with the information system in mind and so the results
are conditioned by the way the study was laid out.
By assuming that an area is relatively homogeneous in many
features we can state the probability of what an individual's own
characteristics may be.
We know what particular pattern of demo-
graphic features stimulates him as an
inhabitant of his social area.
He may be a deviant but he constantly confronts the modal features of
his neighborhood group.
The Settlers are the continuous residents of their census tracts.
They are expected to determine and maintain the stability of the area
in which they live.
They insure the continuity of social values.
To
the extent that the pattern of variables for the Settlers does not conform to the pattern for the census tracts where they live, we may say
that it
is
due to sample size (too small) or that homogeneity does
not hold.
The principle on which the areas were classified was socioeconomic characteristics.
Individuals were classified according to
the extent of their mobility.
This difference of approach is
based on
the assumption that those characteristics of areas are more critically
affected by the type of household within it or moving to it than its
character as a mobile or stable area.
Those census variables which corresponded to individual attribute
variables were mapped onto the record for each UCS respondent.
The
matching was done by the census tract of the present- residence of each
individual.
Three avenues of investigtion of the mapped information
were taken to (1)
show the flexibility of the system in
combining data
sources and (2) tie together and relate the separate analyses of areas
and individuals.
First, means for the UCS individual values were com-
pared against the census tract values for each type of mover (see Table
3).
The deviation of the individual from the census tract is indeed
great.
The co-occurrence of different types of individuals within
the same census tract dampens the effect of any one type and the small
sample would require much greater homogeneity of tracts for a comparison to show agreement.
However, the second investstion of the differ-
ences between census tract variables over the four types of movers was
more insightful.
Since the census tract information was now aggregated
by groups of movers (rather than by types of areas)
it
was instructive
to observe the differences between the measures over the aggregate of
tracts within which the four groups occurred.
On all counts the Stayers
have higher values on variables indicating high status and lower values
on variables indicating low status than any of the other three types of
movers.
The Changers show just the reverse pattern.
Changers are horizontal.
Moves for the
They will move to a bigger house or different
iv ghborhood but in an area with socio-economic characteristics similar
to their present location.
do Runners.
(see table
4)
Stayers exhibit upward social mobility,
as
-55-
Chart 4 shows how the types of movers co-occur within census
tracts.
For example,
those ten tracts where Runners and Stayers oc-
cur can be said to support upwardly mobile people while the thirteen
in which the Changers only occur can be expected to be of low socioeconomic status.
The co-occurrences of the mover types within the same census
tracts dampens the effect that any one type contributes but a corrected effect could be shown if we could get the number of each type
of mover in every census tract and weigh their occurrence as a measure
of effect.
This could not be done without a restructuring of the data
since the four groups of movers are indexed as mutually exclusive sets.
In order to get an intersection on census tracts a different breakdown would be necessary.
The third approach taken was a look at the distribution of the
types of movers over the types of areas.
In this step we attempted
to tie together the classification of areas and the household types.
Table 4 shows the number of each type of mover in each of the five
area types and also the percentage of each type of mover in each kind
of area.
in
The distributions support many of the explanations included
earlier parts of this chapter and also give further clues for the
residual category.
The upward mobility and higher economic standing of
is
confirmed by the representation of more than half of
the movers
'to'
the Settlers and Stayers in Upper and Middle tracts.
A large proportion of the Runners and Changers also occur within
Upper tracts.
The mobility of the population is closely associated
with high socio-economic status.
More areas are open to them.
The
-56-
Running done in the Lower tracts is the milling about that is prevalent
within low stus areas.
These people are often forced to move.
Forced
moves and relocation were not treated here because the area covered was
too large and the sample too sparse to show any results.
Most forced
moves occur within central city areas (except those associated with
highway construction) and the dispersion of the population as a result
of ielocation is so widespread that surveys restricted to the tracing
of these people exclusively are required.
From the distribution of each of the mover types within the residual
category of areas we can see that sme of our earlier descriptions are
borne out.
category.
The Changers appear in
largest proportion in
the residual
For them these tracts provide the change to better sur-
roundings without a great jump in
cost.
Rather than a place of inter-
vening opportunities they are the situation-correcting areas.
For the
Runners the idea of intervening opportunities in the Residual tracts is
more applicable.
They are upwardly mobile and stopover in
these areas
as their families expand and their career position improves.
the Stayers are moving into newly developed areas.
are included in
Some of
These areas,
too,
the residual category.
The analysis of migration streams of the households was intended
to show linkage between areas - the kind of movers on the flow and
their reasons for moving.
age.'
It
This we would have called an 'informed
link-
was expected that all respondents would have had a previous
residence and there would be a specific future residence indicated by
some.
From this double series - previous to present - present to future
patterns could be detected for the four.groups.
With the reason for
-
-57-
moves associated with the location of the move a more definitive analysis of the migration within the SMSA might emerge.
This procedure had
to be stopped short of its goal because of the coding of the data on
both previous and future places of residence.
For all three locational
questions the data were aggregated to different levels.
Vicinity
breakdowns were given for the previous residence, e.g. out of state, other
town in SMSA etc. and town names were given for expected future residence.
The system allows aggregation to any level of interest to the researcher.
However, aggregation to the gross level of the previous residence category negated the value of the quest for informed linkages.
Future
destinations different from present residence town were only given by
198 respondents.
Since this sub-sample size was so small, theaggregation
of tracts within towns was carried out as an exercise and town values
on the variables were calculated and mapped onto those 198 individuals.
The results are shown on Table III but are inconclusive.
It was men-
tioned earlier that the individual/census tract disparity was too great
to allow responsible inference.
To match individuals against town ag-
gregates would compound that disparity.
The superimposition of the census tract file on the individual
file
allowed the testing of a technique.
Substantive conclusions for
the study were indicated but further support for them would be required
if
they are to have any theoretical significance.
either or both of the data sources in more depth,
found.
By probing into
such support may be
The technique though was used successfully and from the experi-
ence gained in
be suggested.
this practice other useful substantive applictions can
-58-
Parallel analysis of different data sources would allow an
effective means for analyzing panel studies.
Different data sources
can be different in content or different in time of collection.
Sources different in content can supplement each other provided the
agents of comparison are measured on the same level of aggregation
or can be combined into comparable levels.
lect and process their own data.
Many city agencies col-
For example, departments of vital
statistics, school department and welfare department all maintain
files on individuals.
The combination of these or even access to
the sources for selection of data for mapping from one file onto
another would improve both the efficiency and effectiveness of these
agencies.
Improved processing and availability of data will make the
work of the planner and adminstrator more effective also.
Some further
considerations on the availability of data ard the use of information systems in
city planning are included in
the closing section of this paper.
-59-
TABLE 3
Census Tract Values and
Individual Values
for
'Jpes if Movers
(also Town Values)
Variable
Value
of
Home
Mover
Typ e
Monthly
Tenure
(percent
owners)
$16811
CHANCER
13588
21860
16402
STAYER
16o63
26200
16674
SETTLER
15032
21128
16692
RUNNER
$68
$100
$62
CHANGER
64
83
61
STAYER
57
95
71
71
59
SETTLER
61
RUNNER
.44
.16
CHANGER
.4h
.34
STATER
.6h
.62
.50
SET'iLER
57
.68
.59
Percent
CH'ANGER
.37
Single
STAYER
Percent
2-4
Unit
Dwellings
Town
Values
j$2h280~
.34
Homes
Values
$14084
RUNNER
Family
Individual
RUNNER
I
Rental
Census
Value
63
SETTLED
.53
RUNNER
.37
CHANGER
.hi
STAYER
*26
SETTLER
.3h
.52
4
Table 3 (cont,)
Variable
Percent
5*
Unit
Structures
Median
Family
Income
Mover
Type
Percent
Lanagers
Individual
Value
Town Value
RUNNER
.26
GHNGER
.20
STAYER
.10
SETTLER
.11
RUNNER
86968
$6000
CHANGER
:'6661
$7835
STATER
7639
7180
7219
9000
RUNNER
.12
.25
CHAi GER
.10
STAYER
.13
.29
.13
SETTLER
.12
.13
.13
RUNNER,
.08
.10
.09
CHANGER
.07
.13
.10
STAYER
.10
.16
.10
SETTLER
.09
.13
.10
.18
.13
SETTLER
Percent
Prof essionals
Census
Value
RUNNER
.13
.12
CHANGER
.16
.17
.14
STAYER
.16
.13
.12
SETTLER
.16
RUNNER
.13
.07
*10
Percent
CHANGER
.13
.153
.11
Semi-skilled
vorkers
STAYER
.12
.14
.08
SETTLER
.13
.10
.10
Percent
Skilled
Wrkers
.l4
- -- -MMMMMMNM
-61-
Table
4
DISTRIBUTIONS OF TYPES OF MOVERS
WITHIN TYTES OF AREAS
UPPERS
MIDDLES
WORKERS
LOWERS
RESIDUALS
17
14
35
Totals
RUNNERS
36
(.33)
CHANGERS
STAYERS
SETTLERS
8
(.07)
(.15)
(.13)
(.32)
33
17
33
12
43
(24)
(.12)
(.2h)
(.09)
(.31)
8)
(.1)
44
(.23)
(.10)
252
352
102
(.34)
(.20)
20
(.14)
8
(.04)
h
(.21)
38
193
(.05)
(.27)
-62-
CHART 4
Co-occurrences of Types of Movers
in Boston Area Census Tracts
-63Chapter IV
The Use of Information Systems and Their Contribution to City Plan
Between data and information lies a gap that is being partially
filled by the organizing and processing techniques available through
modern technology and the ingenuity of the researcher.
The computer
based information system allows for greater amounts of storage facility
and more efficient retrieval capabilities than older non-automated file
card type approaches.
The two major components for such a system are the data inputs and
the program which comprises the software of the system.
The program
may be general, an all purpose program designed to handle all kinds of
data,
unstructured or highly structured.
The data is
specific to the
problem to be analyzed.
For planning purposes,
an aid in decision making.
information systems are being proposed as
The integration of information systems with
data banks of generally available records and special purpose data is
expected to support both the theory and practice of city planning.
Empirical testing of theoretical models can be done drawing from these
sources.
Also descriptive reports can be generated.
That is, both
context and content can be manipulated in such a system.
The informa-
tion system is the tool for accomplishing the manipulation.
Present
shortcomings in the use of such systems arise both from the systems
themselves and the data available for use within them.
The conceptual approach to the use of data banks has been improving in response to improved file-handling capabilities of information systems and the pressures for more 'hard'
sciences..
In early practice,
data in
the social
data banks referred to a 'set
of tapes
on a shelf.'
Mere availability of data was acceptable.
was nothing more than a transformed file
cabinet.
The data bank
Its new form allowed
for faster peeks at the information but no better approach for understanding its message or relation to other forms or sources of data.
No doubt this had to be the first step.
Availability of data and
speed of processing improved the state of the art of information
gathering enough to launch the second stage of information processing.
Discovering relationships among data files improves understanding.
These relationships may be between like sources with substantive overlap or simply complementary relationships which help overcome the
problem of ceteris paribus.
has several benefits.
The multi-file approach to social research
First, the biases built into any one data set
can be detected and possibly corrected (or corrected for).
the options for alternative research designs are increased.
Second,
Third,
areas of study, whether academic or practical, which have heretofore
been isolated can be coordinated with relative ease.
Of course, as the demands for more data increase and the facilities
for handling these data improve serious obstacles to progress arise.
Two major problems discussed widely are the issue of privacy and error
handling.
These problems refer respectively to the content and to the
form of the data.
The issue of privacy received national attention in
the 1966 hearings before a Special Subcommittee on the Invasion of
Privacy in
the House Government Operations Committee in
proposed National Data Bank.
response to a
The bureau of the Census has set stringent
controls for the maintenance of privacy of its files.
However, the
fear is that with increasing availability of data and extended access
to remote time-sharing stations, such control will be lost.
If
privacy is violated individuals will be reluctant to divulge information and research efforts will be stifled.
Without getting into the technical complications involved in
error correction, an indication of the extent or seriousness of the
problem can be stated.
Because of the ways information is gathered -
surveying, observing, measuring etc. - errors of interpretation, reporting and omission are 'built in.'
Errors are compounded in the
coding procedures, that is, in preparing the raw data for automated
handling and in the key-punching operation.
When faced with incor-
rect responses in the analysis procedures the researcher must usually
compromise the validity of his procedures.
Mechanisms for detecting
and correcting data errors must then be an integral part of any processing system.
In the ADMINS system, for example, error correction
is handled in two ways.
Either the data itself can be accessed and
altered or the description of the data can be changed to accomodate
vagaries in response patterns (or both types of changes can be accomplished).
The decision about which to change is left to the researcher.
Unless errors are corrected or handled responsibly the validity of
conclusions is questionable and the applicability of the research is
doubtful.
From my experience gained in the actual use of an informa-
tion system (ADMINS) and two data sources (a mini-data-bank) a few
other obstacles were noticed.
It became obvious early in the use of
this system that the limitations for this study were imposed by the
two data sources rather than the system.
Errors within any file must
be corrected but the capacity for multi-file processing introduces
-66-
other error-type obstacles.
Incompatibility and inconsistency of data are chronic problems.
Compatibility refers to the ability to use two files in concert.
At
the simplest level, compatibility problems, to the extent of allowing
for merely matching data, can be solved by providing a cross-reference
code that is common to all files which are to be processed in one
For example,
analysis.
in this analysis the census tract code was a
common item in both files.
Closely allied to compatibility is
con-
Consistency of data is questioned within the definition of
sistency.
For data to exhibit meaningful comparisons, definitions
variables.
must be consistent across files.
For example, exact definitions for the
census categories must be provided so that surveyors can classify respondents correctly if an individual/census match is to be made.
In
planning, areas like neighborhood and community need specific definition.
The level of aggregation at which data is reported is usually
determined by the question or hypothesis which is
of data.
demanding collection
(This problem may be considered as a subset of the problems
of consistency and compatibility where many files are sampled.)
is
If data
to be generally available then the lowest level of aggregation allows
greater flexibility for its use.
With these problems identified before
collection, data can be gathered, stored, retrieved and processed more
satisfactorily.
Retrieval and processing involve combining social sci-
ence procedures with mathematical techniques.
Boolean intersections and
other set operations are necessary as a minimum inspection technique and
statistical operations are essential if hypothesis testing is to be
undertaken.
-67-
Beyond the processing of data with more sophisticated methods lies
the use of the data.
Use must be distinguished from usefulness.
The
information made available may be used for different purposes, from
different points of view, experimented with, discarded, retrieved or
abandoned.
After heuristic assessment it may be declared useful.
In-
terest is being focused on the use of information in developing social
indicators.
The approach used in this paper may be one that has some
relevance to this development.
Social indicators would attempt to
measure, in a given social situation, 'where we stand' and 'where we
are going.'
Two approaches must develop simultaneously.
A scientific
inquiry into the nature of the social system must be undertaken to improve understanding of its structure.
A pragmatic study of the state
of the system at any point in time must continue in parallel for effective controls to be introduced.
The existence of wide-ranging data
sources allows for flexibility in the. construction of these indicators.
However, dangers arise in stopping too soon or not trying 'far out'
combinations.
C.
imag-
Wright Mills advocates cultivating 'sociological
ination,' that is the capacity to shift from one perspective to another,
ranging from remote transformations to inherent characteristics.
A
deliberate self-conscious attempt to describe phenomena using different
combinations and permutations of data should result in the choice of a
best description.
The development of indicators will result from the experimentation
with types of data and the capacity of the system to respond to the information.
I describe these two notions as social relativity and
social relevance.
Social relativity takes account of all
the levels
-68-
at which measures are taken and the relation of one measure to another.
For example, it is not the same thing to measure characteristics of the
unemployed and to measure unemployment.
Social relevance depends on
the value of the measure in the context in which it is being used.
Crime rates are often used as an index of the degree of integration in
a society.
Associations between poverty and high crime rates are drawn.
However, Biderman in Social Indicators (1) points out that the crimes
which make up the crime index reflect the affluence rather than the
poverty of the society being measured.
Initially the perplexing question is what to measure.
will reflect priorities either of need or of power.
The answer
It is likely that
one road taken will be assessment of Federal programs.
Bauer, et al.
propose measures of performance of the social system which show the effects of the mace program.
In their attempts to measure or even describe
the impact of the space program they find themselves in areas far removed from the space effort in intent and interest.
intended effects are only one aspect of impact.
Anticipated and
Any agent of change
also acts as a catalyst for other aspects of a highly interdependent
system.
In the first step analytic and predictive objectives must be
measured and normative objectives will follow.
For city planning pur-
poses the development of social indicators is especially relevant.
One
contribution of the Model Cities program is likely to be self-conscious
attempts at assessing its impact on the lives of the people directly
involved, and its effectiveness as an agent of change for the larger
community.
Under this umbrella program its component parts will be
evaluated.
The wide range of elements will require different kinds of
measures.
Improvements in quantitative techniques will be forced as
well as recognition of the value of qualitative data.
As experience accumulates in the use of information systems and
data analysis the directions should become clearer.
Identification
of relevant data and accurate (or just more adequate) statistics will
be an arduous task feeding back on itself for refinement.
CHAPTER V
Summary and Conclusions
At the outset we were interested in the classification of
areas and households and observed the way census tracts are
differentiated on socio-economic variables and households on
migration status.
Further, we inquired if
by using an information'
system approach we can map tract information onto the individuals
and arrive at a richer description of movers and areas.
From an
analysis of the two data sources we found that:
1.
Classification of areas by socio-economic characteristics
yields a coherent and consistent pattern of areas, rather than a
geographic concentration.
2.
The type of housing in
an area is
a good indicator of
the type of individual (household) to be found in the area.
3.
Subdividing the stayer/mover dichotomy by length of
residence is meaningful in 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 valuable updating information and the shortcomings lie more with the data sources than with the system.
-711-
APPENDIX
Notes on the ADMINS System
ADMINS, a data information system written at MIT, was used as
the tool for analysis.
This system is run under the CTSS time shar-
ing executive system at the MIT computation center.
This system has
capabilities not available in most presently implemented programs.
The program is comprised of four sub-systems that are invoked in
iterative loops as one proceeds from simple to more complex analysis.
Although it is not appropriate to include a full description of the
system at this time, it will be illustrative to include those particular features of the system which allowed the analysis to proceed
along the lines described.
At the initial stage, the user describes the variables of interest to him and invokes the auditing procedures which check for a
match between the raw data and its normative description.
In specify-
ing a data description one is also performing a selection of only those
items relevant to the pursuant analysis and the other variables in
file
are not read in.
The data itself
is
the
sieved through the descrip-
tion for consistency and an error message is generated for each discrepancy.
This report allows the user to change either his description
or the data itself.
Error correction can be performed efficiently and
quickly proceeding in this manner and the user learns about his data
in
the process.
At this point the form of the data is
converted from
-72-
an item record file in which for each respondent (the item) there is a
record of his responses in each category, to a category record file.
Under this form each record in the file represents a response and the
entries within it are those individuals to whom it applies (or who
responded to that question).
These category records are the input to
the Analyzer where the user applies his theoretic plan to the data.
The Analyzer allows for continuing interaction between classification
and summarization procedures.
building indexes.
The classification procedures include
These classificatiorsare responsive to empirically
observed frequencies in the data.
Indexes point to sub-sets of items
in the file and are named to inform the user of the items they represent.
When the index is printed out, the system provides the number of
respondents to which the characteristic applies and that number as a
percentage of the total category from which the characteristic was extracted.
The indexes are input to Boolean intersection and union
operations which group together respondents with the same characteristics.
For each Boolean operation again the number conforming to the operation
and its percentage of the total is printed out and, in addition, a
significance level is printed out.
This significance level is computed
from a hyper geometric distribution on the basis of the largest possible
N of the intersection.
from this test.
A significance level = .9 is considered good
Wherever a value is referred to as significant in
this paper, it is above .9 (unless otherwise stated).
This statistical
information allows the user to make decisions in pursuit of high significance and also provides clues about avenues of approach which may not
give him any satisfactory information.
Complex indexes may be named
-73-
and the hierarchy of components indicated by faceting its name so that
its
construction is
reflected in
the name.
This procedure eliminates
confusion for the user as he proceeds into detailed analysis and also
aids a reviewer in understanding another researcher's documentation.
Summarization of the data in terms of these indexes is
the use of tables and displays.
performed by
The Tables instruction generates
matrices of frequencies of row and column intersections.
For each
entry a significance level is computed.
The Display Instruction displays the actual entries for items in
an index.
For specific information on individuals and/or census tracts
this instruction was used.
The displays of values of several cate-
gories for each individual within a class provided an eyeball estimate
of the variance within each measure aid was also useful for matching
individuals values with census tract values.
The Interval instruction was used to recode the census tract
numerical categories into discrete interval nominal categories.
The
output from this instruction is a new category record where the entries
are the tracts which fall within the percentiles requested.
This new
category can then be entered into use in analysis in the same manner
that any original category is used.
The Count instruction was used in an experiment to simulate a
regression on census tract variables.
A series of indexes is
built to
characteristics of interest which should discriminate between types of
areas.
list.
The instruction counts how many times an item occurs in
Discrete and cumulative counts are produced.
this
This instruction
-74-
is more pertinent for threshhold decisions where one is concerned with
a minimum count on a number of characteristics without regard to which
of the specific characteristics apply to each item.
For our own pur-
poses it was not helpful for verifying classification - perhaps it
could have been used earlier in the analysis of we had proceeded from
a more theoretical rather than empirical approach.
Another feature of the Analyzer is
one file
of information at a time.
its ability to handle more than
One way in which this multi-file
capacity was used was to create four files from the UCS data where each
of these files was in effect the indexed set of individuals (Runners,
Changers etc.).
The Subfile instruction allows one to cite an index
which will subsequently be referenced as a file
name and to create
categories of responses occurring in these indexes only.
When this was
accomplished two or more categories could be tabled against each other
for each subfile and a much more refined aspect of the data revealed.
For example, a table of responses to the questions Why move? cross
classified with responses to bad things cited about the neighborhood
could be generated for each of the four subgroups simultaneously by
working the four files on one list
and invoking them in
parallel.
The Linkage and Map Instructions allow for the inclusion in one
file, data from different sources with a common identification.
These
capacities were used in a few instances:
1.
To Map the age data onto the Census file to supplement the
original file
2.
To Map the census data onto the UCS file - The flexibility
ADMINS.provides for multi-file handling and allows one to follow many
strategies in analyzing data.
Throughout all the analysis procedure,
there was no tactic suggested that could not be accomodated by the
present system.
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-78-
List of Census Variables
Percentage
Denominator
Original
Total Population
Total Mhites
Total Non-Whites
Total Population
Number of Families
Number of Families
Income under $1000
1000-2000
2000-3000
3000-4000
000-5000
6000-6000
6000-7000
77000-8000
8000-9000
9000-10000
10000-15000
15000-25000
over $25000
Number of Housing Units
Total Ocuppied Units
Owner Occupied Units
Renter Occupied Units
Total Occupied Units
Number Living in
Unit less than 1 year
3-5 years
6-20 years
over 20 years
Number single family homes
number 2 -k family homes
Number units vith 5 oi' more units
Value of owner occupied units
median rent
Age Categories by 5 year
Intervals of Male and
Femles
Total Pobulation
-79-
census variables (cont.)
Male
Professionals
Managers
Clerical and Sales
Semi-Skilled Workers
Skilled %brkers
Household Workers
Laborers
Males over 20
-80-
List Of Original UCS Variables
Residence Place (town)
Sex of Respondent
Census Tract Code
Age of Respondent
Length Lived In Conzmunity
Relationship to Head
Part of Life Spent Here
Sex of Head
Age of Head
Previous Residence (Informant)
Improvements to Community (5)
Occupation of Head
Household Size
Income of Head
Age of Youngest Child
Total Family Income
Sex of Informant
Type of Structure
Age of Informant
Condition of Housing
Marital Status of Informant
Public Housing?
Previous Residence (Respondent)
Race of Respondent
Good Things About Neighborhood (7)
Eiployment Status of
Head
Bad Things About Neighborhood
Tenure
Value Of 1lome
Monthly Rent
Expect to Move
Plan to Stay in this House
Yehen Eight Move
Town i.here Move
Reason for Move (2)
Number of Rooms
Sex of Respondent
(3)
-81-
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New York:
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Social
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H.L.
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Unpublished Material
A.
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Boston Metropolitan Region" unpublished MCP Thesis, MIT, 1967.
B.
Beshers, James A. "The Construction of Social Area Indices: An
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.---------------------------------"The Language of ADMINS
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Rust, B.C. "Migration:
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Six Boston Municipalities"
,"
unpublished