Urban Dynamics and Ecological Studies of Delinquency

Urban Dynamics and Ecological Studies of DelinquencyAuthor(s): Robert J. Bursik, Jr.Source: Social Forces, Vol. 63, No. 2 (Dec., 1984), pp. 393-413Published by: Oxford University PressStable URL: http://www.jstor.org/stable/2579053 .

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Urban Dynamics and Ecological Studies of Delinquency*

ROBERT J. BURSIK, JR., University of Oklahoma

Abstract

A paper by Jackson and Borgatta criticizes the indiscriminate use of factor analysis in the study of ecological differentiation because the derived factors are often assumed to be real and persistent over time. This is especially true for ecological studies of delinquency, where the underlying community dimensions associated with delinquency rates are typically interpreted without regard for the historical setting and the urban dynamics giving rise to such community-level patterns.

In this research, the delinquency rates of Chicago local communities are examined for a 30-year period. Although a basic pattern emerges for 1940, 1960, and 1970, the structure of the 1950 data is very different. The implications of this divergence in light of Chicago's recent history are examined.

Jackson and Borgatta have trenchantly criticized research focused on the underlying dimensions of ecological differentiation for its predominant reliance on exploratory factor-analytic models. As they point out, one can often detect a "naive faith that common factor or component analysis will, as if by magic, produce fundamental latent variables" (56). A similar position has been taken by Berry and Kasarda, who lament that this reliance has given ecological studies an undeserved reputation as basically methodological exercises concerned with the analysis of spatial correlations and distributions. Such criticisms certainly do not dismiss the important con- tributions that factor-analytic models can make in the study of community structure. Rather, they reflect a concern that the underlying dynamics of such structures, which are at the heart of human ecology, are taken for granted. As Jackson and Borgatta argue, before one can conclude that a given analysis has discovered truly "fundamental" aspects of residential differentiation, these dimensions must be shown to exist across communities and through time (51).

This issue is especially pertinent to community-level studies of de-

*1 thank Don Merten, Gary Schwartz, Jim Webb, and an anonymous referee for helpful comments, criticisms, and insights on an earlier draft. Address correspondence to the au- thor, Department of Sociology, University of Oklahoma, Norman, OK 73069, ? 1984 The University of North Carolina Press

393



394 / Social Forces Volume 63:2, December 1984

linquency. Since the classic work of Shaw and McKay, there have been many studies presenting evidence that local delinquency rates are associated with underlying community dimensions of socioeconomic status, racial and ethnic composition, and/or anomie. Many of the most widely known of these studies' (Bordua; Chilton, b; Gordon; Lander) have, in part, relied heavily on factor models in the development of their argu- ments. However, while these studies have been conducted in a wide range of communities, there has been no attempt to study the stability of such aggregate-level associations over time within a single community.

In this paper, it is argued that the general omission of temporal considerations from this research tradition is a serious impediment to the community-level study of delinquency, for it forces the analyst to assume that the underlying dimensions associated with delinquency rates during a single time period are in fact real and persistent, regardless of historical changes in urban dynamics that may be taking place. The implications of temporal considerations are investigated here for a 30-year period in Chicago.

Community Patterns of Delinquency

Although community-level studies of delinquency appeared early in the sociological literature (e.g., Blackmar and Burgess; Breckinridge and Ab- bott; McKenzie), Clifford Shaw and Henry McKay (a, b, c) made an important advance in this field by interpreting neighborhood delinquency rates within Burgess' general framework of human ecology. This significant in- tegration of perspectives not only gave their research added criminological importance, but also made it a central component of the urban research conducted by the Chicago school.

In particular, Shaw and McKay were strongly influenced by Bur- gess' hypotheses concerning processes of invasion and succession and the ongoing relocation of social groups within a city (50, 54). As Guest and Weed have noted, Burgess' approach to human ecology assumed that the movement of population groups within a city resulted from changes in economic and social status. The primacy of such socioeconomic factors in the production of delinquency rates was also suggested by Shaw and McKay's data: the rates found in Chicago communities that had relatively stable economic levels over several decades also appeared to remain fairly stable despite changing racial and ethnic compositions. However, it was the relative stability of these areas in light of the dynamics undergone by the city as a whole that was emphasized by Shaw and McKay. As they stressed, their work was "based on the assumption that the best basis for an understanding of the development of differences among urban areas may be gained through study of the processes of city growth" (c, 17-18).



Urbanism and Delinquency / 395

By far, most of the ecological research in the tradition of Shaw and McKay has concentrated on specifying the most theoretically important associations between delinquency rates and sociodemographic indicators of community composition. The first large-scale published study of this type was Lander's ecological analysis of Baltimore, which also concluded that delinquency rates tended to be high within certain community contexts. However, Lander argued that these contexts were related "only to anomie and not specifically to the socioeconomic indications (sic) of an area" (80). This conclusion was severely criticized on both substantive and statistical grounds, leading to an important series of replications in other cities and reanalyses of Lander's data (see Bordua (Detroit); Chil- ton and Dussich (Indianapolis); Chilton, b (Detroit, Baltimore, Indianapo- lis); Gordon (Detroit, Baltimore, Indianapolis)). Gordon's reanalysis indicated that although the anomie factor did not form a genuine construct, the socioeconomic factor was highly invariant for all three cities.

It would appear that such multicity evidence strongly supports the existence of a fundamental socioeconomic status factor that may be called a general component of the community context of delinquency. In fact, Chilton comments that "in view of the limitations of the data and the differences in the cities involved . .. the congruity of the findings is re- markable" (b, 83). However, such claims should be accepted with great caution since the implications of Shaw and McKay's broader theme have virtually been ignored. Recall that they were able to reach their conclusions only after studying the local community contexts of Chicago in light of several decades of urban change. Therefore, the effects of such larger dynamics in the three cities noted above must also be carefully considered before such similarities can be accepted, in a sense, as nonspurious. Hunter, for example, has shown that the ecological structure of Chicago changed markedly between 1930 and 1960 and Bursik and Webb have shown that, while processes of racial invasion and succession were not related to changes in a community's delinquency rates between 1940 and 1950 in Chicago (which is congruent with Shaw and McKay's finding), there was a strong association between 1950 and 1960 and a moderate one between 1960 and 1970.

We propose that community processes related to delinquency can only be placed within larger urban dynamics and given a full meaning through longitudinal data. In this light, it is interesting that Rosen and Tumer have observed that the 1960 Indianapolis data presented in Chil- ton's dissertation (a) show much more congruence with Lander's 1939-42 Baltimore data than with the 1949-50 Indianapolis data analyzed in Chil- ton's 1964 publication. As Rosen and Turner quietly mention, this may indicate that "the causes of delinquency have changed" (191). More re- cently, Chilton and Dussich have also adopted this position, stating that "it is clear the situation is not immutable," although they feel that such




changes may only become apparent in data reflecting a wide range of years (81-2). Thus, only if a socioeconomic factor can be shown to exist within a variety of historical contexts may it truly be said to form an invariant component of the community context of delinquency.

Prior research certainly cannot be faulted for generalizing from cross-sectional data to fundamental processes, for the necessary longitudinal data are extremely rare. However, the fact that Gordon reached his conclusions concerning the invariance of the socioeconomic factor from 1939-42 Balitmore data, 1948-52 Detroit data, and 1948-50 Indianapolis data implies a strong assumption of urban stability. We feel that unless it can be safely assumed that the historical dynamics of urban growth in such communities are very similar, the search for invariance across cities is premature. Rather, it seems more appropriate to ensure that we can safely generalize the dynamics of a given city in terms of some invariant structure before making a comparison with others.

Factor Analysis and Ecological Approaches To Delinquency

Although the preceding section has argued that the replication of factor patterns across time is essential to the analysis of community patterns of delinquency, Hirschi and Selvin have taken a directly opposite position, stating that "in general, there is little point in seeking a precise replication of a methodologically sound factor analysis . . since these dimensions are only means to a more important end-the study of causal relation- ships" (156). Thus, going beyond the objections raised by Jackson and Borgatta, many criminologists have become impatient that factor-analytic models have had a primarily descriptive rather than predictive emphasis; Beasley and Antunes, in fact, state that due to this emphasis, such models are of very limited use (also see Wilks).

The question of causality is a critical issue, for in its usual applications, factor analysis is strictly concerned with associational patterns. However, even some factor analysts (such as Lander) have concluded that the delinquency rate is dependent on other aspects of the community, although this assumption has never been tested and it is not entirely clear why a reverse direction of causality is not possible, that is, changes in delinquency rates may directly cause subsequent changes in the sociodemographic makeup of an area.2 Even if it can be safely assumed that delinquency rates are causally posterior to other indicators of community composition, the causal order of the prior variables is unclear. Rather than testing a hypothesized order, which is the basis of true modelling, all independent variables are typically analyzed within a single equation, as in the study by Beasley and Antunes and the regression applications of Lander, Bordua, and Chilton. Not surprisingly, a great deal of multicollin-




earity is found among the predictors. As Johnston has shown, the conse- quence of this condition is a loss of precision in the parameter estimates so that "it becomes very difficult, if not impossible, to distinguish the relative influences of the various X variables" (160; also see the argument of Gor- don). Since it is precisely these influences that causal models try to untan- gle, this becomes a serious problem.

It may certainly be argued that this problem can be easily sur- mounted by the specification and testing of alternative models. However, it is at this point that problems of stationarity over time become as acute for regression models as they are for factor analysis. As Kenny as well as Heise have argued, causal analysis is appropriate only when the causal effects underlying a system of variables are not undergoing change during the period of analysis. Thus, the criticisms of Jackson and Borgatta are equally pertinent for regression-based ecological analyses-it is still necessary to document the existence of stable ecological structures before causal implications are developed.

It is at this juncture that we feel that the replication of factor models can greatly advance our knowledge of community processes and delinquency, for recent developments in confirmatory factor analysis (see Jo- reskog, b) are easily adapted to tests of temporal invariance. Although causal modelling can be incorporated into such tests, a factor model is able to detect stationarity in the entire set of intercorrelations without confounding these tests with simultaneous tests of the appropriateness of a certain model. Given the current lack of theoretical specification as to the form a community-level model should take, the problems of confounding are especially acute. For this reason, a factor-analytic approach is used in this paper to determine the degree of invariance in these ecological patterns over time.

The Data

The delinquency data analyzed in this paper were collected under the direction of Henry McKay while he was at the Institute for Juvenile Re- search (IJR) and reflect the rates of male referrals to the Cook County, Illinois Juvenile Court between 1940 and 1970 for each of the local community areas of Chicago. His discussion of these data can be found in Shaw and McKay (c) and McKay.

We have restructured these data into a format somewhat different from that found in McKay's work. His analysis was based on five distinct time periods: 1934-40, 1945-51, 1954-57, 1962-65, and 1970. However, McKay's aggregations reflect different portions of the decades. For example, given the decennial nature of U.S. census data, the extent to which the 1934-40 delinquency rates should be associated with 1930 or 1940




community characteristics is not clear. In addition, we feel that it is more appropriate that the longitudinal analysis be based on rates computed for consistent time spans rather than the 7-, 4-, and 1-year periods of McKay. Finally, census data are most reliable indicators of community composition during the year of their collection. Since the relationship of this composition to delinquency rates is at the heart of this research, the analysis is confined to delinquency occurring during the years 1940, 1950, 1960, and 1970.

It was necessary to reconstruct these rates from the original data (which, luckily, were still accessible in the IJR archives) since year-specific data were not available in any of the Shaw and McKay publications nor in McKay's internal IJR memos. However, the individual court referral records for five areas during 1960 had vanished from the files. These rates were estimated from the memos of McKay by assuming that these five rates remained constant during the 1958-61 period and using one-fourth of the total number of referrals in each area during this period as the estimator of the numerator in the 1960 rates. All rates (indicated by DEL) are computed per 1,000 males aged 10-17 living in the community.

The social compositions of the local areas are reflected in seven sociodemographic indicators that were consistently available in the U.S. census materials from 1940 to 1970: the percentage of nonwhites (NW), the percentage of foreign-born whites (FB), the percentage of the male labor force that is unemployed (UNEMP), the percentage of professional, technical and kindred workers (PROF), the percentage of owner-occupied dwellings (OWNOCC), the percentage of households with more than one person per room (DEN), and the median education level (ED).

Analysis

The investigation of temporal invariance utilizes the confirmatory maximum likelihood factor model developed by Joreskog (a) and his subsequent expansion of the model to simultaneously analyze two or more factor structures (Joreskog, b; see also Alwin and Jackson). For each year under consideration, the overall pattern of association among the eight variables is contained in the corresponding correlation matrix, presented in Table 1.

Before proceeding with the factor analysis, an important pattern in these matrices must be noted. While they are not identical, the patterns of correlations between the delinquency rate and the percentages of nonwhites and foreign born whites are fairly similar in the 1940, 1960, and 1970 matrices. The 1950 correlations, however, stand out in stark contrast: the correlation of DEL with NW is much weaker and that with FB is almost nonexistent.




Table 1. INTERCORRELATIONS AMONG THE EIGHT VARIABLES FOR THE FOUR TIME PERIODS

DEL NW FB UNEMP PROF OWNOCC DEN ED

DEL 1.000 0.787 -.402 0.676 -.168 -.465 0.633 -.064 NW 0.493 1.000 -.624 0.619 -.080 -.378 0.641 -.062 FB -.084 -.716 1.000 -.025 -.397 0.048 -.091 -.252 UNEMP 0.503 0.875 -.490 1.000 -.519 -.377 0.737 -.295 PROF -.368 -.327 0.065 -.475 1.000 -.085 -.513 0.735 OWNOCC -.323 -.515 0.116 -.662 0.158 1.000 -.332 -.079 DEN 0.483 0.892 -.582 0.897 -.458 -.569 1.000 -.275 ED -.181 -.125 -.173 -.288 0.701 0.020 -.238 1.000

1940 correlations are above the diagonal, 1950 correlations below.

DEL 1.000 0.798 -.573 0.786 -.429 -.693 0.755 -.357 NW 0.755 1.000 -.772 0.895 -.386 -.606 0.826 -.191 FB -.451 -.721 1.000 -.640 0.217 0.153 -.670 0.007 UNEMP 0.706 0.722 -.463 1.000 -.528 -.680 0.919 -.300 PROF -.230 -.256 0.199 -.397 1.000 0.282 -.583 0.553 OWNOCC -.703 -.504 0.029 -.603 0.026 1.000 -.527 0.283 DEN 0.603 0.706 -.526 0.862 -.509 -.476 1.000 -.353 ED 0.057 0.066 -.165 -.053 0.442 0.072 -.169 1.000

1960 correlations are above the diagonal, 1970 correlat'ons below.

It is certainly possible that this change can be explained by the existence of certain urban dynamics that were not operative during the other three periods. This, of course, is the basic question that is addressed in this paper. However, two other more troublesome alternatives may also account for this large shift: there may be an error in the data that is significant enough to produce such markedly different patterns or there may be one or several communities that have configurations of these variables so extreme that the entire linear association is affected.

The first problematic alternative was checked immediately, but no errors were found. Therefore, we searched for potential outliers in the data. The delinquency rate in 1950 was regressed on the other seven variables and Cook's D was computed for each community (see Cook and Weisberg). This measure represents the squared distance from the vector of beta weights for the entire sample to the vector that results when that community is removed from the analysis and is defined as:

(lp)ri(viAI(l - Vii)),

where p is the number of independent variables, ri is the standardized residual for area i and vii is the ith diagonal element of the X(XTX)Y1XT matrix.

A community is considered to have a significant effect on the equation when the value of D is large. Although there is no clearcut definition of large, Cook and Weisberg suggest a consideration of all observations




with a D greater than 1, for this represents a shift of over 50 percent in the confidence ellipsoids of the vector of beta weights when that observation is included in the analysis (339, 345).

This approach did uncover one highly influential community area during 1950: Bumside (Community Area 47) had a Cook's D of 1.50, which represents a shift of over 80 percent in the ellipsoid when it is induded in the analysis. The regression model was recomputed after eliminating Bumside from the analysis; no other area had a D greater than .5.3 Bumside was therefore eliminated from the 1950 data and the correlation matrix recomputed. As shown in Appendix 1, this new matrix is much more congruent with those of the other years. A possible explanation of Bumside's deviation will be discussed later in this section.

As the initial step in the analysis of invariance, Joreskog (b) sug- gests a test of the hypothesis that the four correlation matrices are statisti- cally equivalent using the test statistic: M = nlogISI - lngloglSgl, where n is the total sample size, ng the number of communities under consideration during year g, S the pooled correlation matrix for the four periods and Sg the year-specific correlation matrices; this statistic is approximately distributed as X2 with ?/2(m - l)(p)(p + 1) degrees of freedom, where m is the number of groups and p is the number of variables in the model.4 If the hypothesis cannot be rejected, the four correlation matrices are statisti- cally equivalent and, consequently, the factor structures underlying them are identical, that is, the underlying dimensions of the delinquency-community association are fundamental and ongoing between 1940 and 1970. On the other hand, if this hypothesis is rejected, there is evidence of a significant degree of dissimilarity among the individual factor structures for the four years.

Since this test results in a X2 value of 265.254 with 116 degrees of freedom (which is highly significant), the assumption of temporal invariance in the association of these items for all four time points is not sup- ported. However, it is possible that the underlying structures may be invariant for two or three of these periods but not for all four. Therefore, pairwise tests of this hypothesis were also made. As shown in Table 2, there is evidence that the correlation matrices for 1960 and 1970 are equivalent, indicating that the associations among delinquency rates and the community indicators did not significantly change during this ten year period. Given this equivalence, the patterns for 1960 and 1970 will be considered as a single, aggregated time period designated as 1960-70 in the remainder of the paper. The maximum likelihood estimate of this pooled correlation matrix is presented in Appendix 2.

Given the finding that the underlying structures of these variables changed between 1940 and 1960-70, we apply a series of hierarchical tests, devised by Joreskog, that examine the degrees of similarity and difference in the three factor structures. The first, most basic hypothesis is simply




Table 2. PAIRWISE TESTS FOR THE EQUALITY OF CORRELATION MATRICES*

1940 1950 1960 1970

1940 --

1950 105.033 (.0000)

1960 140.776 64.092 --

(.0000) (.0255)

1970 88.609 76.424 49.983 (.0001) (.0018) (.2478)

2

*The first entry is the x value; the number in parentheses is the associated significance level. All tests have 44 degrees of freedom.

that the same number of factors fits the three correlation matrices. For this test, an orthogonal model was fit, constraining ?12(k)(k - 1) entries to 0 in each factor structure matrix, where k is the number of hypothesized factors.5 Although Joreskog proposes that the test be conducted separately for each time period and the resulting X2 values summed to test the overall hypothesis for all groups, the aggregated X2 statistic would have masked some strong differences in the decades under consideration. For example, as shown in Table 3, the overall X2 value for the hypothesis that three factors fit all three time periods is 33.410 with 21 degrees of freedom, with an associated significance level just under .05. As a result, a decision could have been made either to obtain a better fit by modelling all of the year-specific matrices with four factors or to be satisfied with a three-factor fit that is nearly nonsignificant. However, when considered individually, a three-factor solution provides a good fit to the 1940 and 1950 matrices but a poor fit to 1960-70. An examination of a four-factor solution does indicate that the inclusion of an additional factor provides a very good fit to 1960-70. Therefore, we will assume that the 1940 and 1950 structures can be modelled by three factors and 1960-70 by four.

Even in this early stage of the analysis, two important findings concerning the stability of these patterns over time should be noted. First, the ecological structure of Chicago was significantly simpler in 1940 than during the subsequent decades; although a three-factor solution fits both 1940 and 1950, the fit is noticeable better for 1940. This finding confirms Hunt-




Table 3. X2 TESTS FOR THE NUMBER OF UNDERLYING FACTORS

Number of Factors 1940 1950 1960-70

2 (d.f.=13) 56.872 66.868 88.848 (.0000) (.0000) (.0000)

3 (d.f.=7) 4.714 11.099 17.597 (.6949) (.1344) (.0139)

4 (d.f.=2) -- 0.786 (.6750)

er's observation that Chicago was becoming more ecologically differentiated between 1930 and 1960. Relatedly, given the invariance of 1960 and 1970 matrices, these findings also suggest that community differentiation stabilized after 1960.

Given the fit of the n-factor solution, the next step in the analysis hypothesizes that the pattern of factor loadings is invariant during the three time periods. We will restrict the test of pattern similarity to the 1940 and 1950 matrices since it is apparent that the pattern for 1960-70 wi'll differ due to the additional fourth factor. It is not necessary to hypothesize the pattern for 1940 and 1950 in advance; rather, one can leave it unspeci- fled by fixing two zeroes and one nonzero loading in each column almost arbitrarily. Although the correlations between the factors and the error variances of the variables are allowed to differ for the two periods, the model assumes that the unspecified factor pattern remains constant. How- ever, this hypothesis fit the data very poorly (X2- = 74.849, d.f. = 35). Therefore, the 1940 and 1950 matrices were examined separately.

As an initial model of the 1940 ecological structure, we tested the fit of relatively pure factors corresponding to racial, economic, and living situation dimensions. Since we are no longer explicitly comparing 1940 with the other two periods, this is a case of -simple confirmatory factor analysis. For this test, DEL was allowed to load on all three factors, NW and FB on the'racial factor, UNEMP, PROF, and ED on the economic factor and OWNOCC and DEN on the living situation factor; all other loadings were constrained to equal 0 and the three factors were allowed to be- corre- lated. The fit of this model was again very poor (X2-= 128.495, d.f. = 15).

As an alternative strategy, the factor structure matrix produced by a principal three-factor solution was used to obtain a general sense of the simple structure. The initial hypothesized maximum likelihood pattern constrained all factor loadings to 0 except those whose absolute values




were at least .4 in the principal factor solution; all factors were allowed to be correlated. Although this approximation also did not fit satisfactorily, a revised model that provided a good fit was easily obtained through an examination of the standard errors of the parameters (to eliminate statisti- cally nonsignificant effects) and the first derivatives of the minimization function (to detect additional effects that should be incorporated into the model).

The factor structure derived for 1940 (Table 4) shows a very interesting pattern. The third dimension (F3) clearly represents a racial/ethnic dimension that is associated with delinquency and is very similar to one derived in Gordon's two-factor solution. The first two factors, however, depart markedly from his single economic dimension. Factor 1 represents a combination of the racial composition, unemployment rates, housing status, and delinquency rates found in Chicago communities, all of which differentiated between the living situations of whites and nonwhites during this period of Chicago's history. We propose, however, that this is primarily an economic rather than a racial dimension in a very particular sense. Gordon has argued that the ecological correlation between socioeconomic status and delinquency rates is predominantly a function of the lower end of the economic distribution of communities. Given the especially strong loadings for unemployment rates and household density, it is our position that Fl reflects the prevalence of this end of the economic continuum within a community. The failure of delinquency rates to load on the more general socioeconomic dimension (F2), the moderate negative correlation between Fl and F2, and the independence of Fl and the racial/ ethnic factor (F3) lend support to this position.

It is interesting to note that Kornhauser argues that one implication of Shaw and McKay's theoretical approach is that "with the intervening variable of social disorganization controlled, the relationship between economic level and delinquency should disappear" (85). If we can assume that social disorganization is most likely to exist in communities at the low end of the economic distribution, the 1940 findings give strong support to Shaw and McKay through the failure of delinquency rates to load- on the second factor. Unfortunately, without a precise definition of Shaw and McKay's construct, this conclusion can only be tentatively offered.

However, recall that Shaw and McKay implied that social disorganization was most prevalent in areas whose local institutions were unable to control the behavior of local residents. The strength of local organizations is to a large extent a function of local participation. Hunter has documented that participation in such organizations in Chicago is most likely for people with positive feelings about their neighborhoods; such sentiments were least likely for blacks living in neighborhoods of the lowest socioeconomic status. Earlier, Drake and Cayton also observed that the participation of the black lower class in Chicago was directly limited by




Table 4. FACTOR STRUCTURE FOR 1940*

Factor Factor Factor Unique Variable 1 2 3 Variance

DEL .788 0* -.447 .282 (.079) (.076) (.054)

NW .743 0* -.704 .075 (.061) (.066) (.039)

FB 0* 0* .168 (.076)

UNEMP .954 0* 0* .216 (.075) (.050)

PROF 0* 1* 0* -.118 (.083)

OWNOCC -.758 -.433 0? .648 (.126) (.124) (.112)

DEN 1* 0* 0* .270 (.059)

ED 0* .642 0* .504 (.100) (.085)

Factor Correlations

1. 000*

-.543 1.000* (.074)

0* -.448 1.000* (.078)

2 X =21.599 d.f.=18 p=.2503

'Standard errors are given in parentheses. All loadings and correlations marked with an asterisk have been constrained to these values by the model.




economic factors. Since we have argued that the first dimension represents the extent of this low end of the economic distribution in a community, such findings indicate that it is reasonable to conclude that a social disorganization dimension related to delinquency did exist during 1940.

The 1940 factor solution presented in Table 4 was used as a first approximation to the 1950 pattern. Although the earlier discussion indicated that these patterns were significantly different, it was again possible to obtain a structure that fit the 1950 data through the successive elimina- tion of nonsignificant effects and the incorporation of significant effects suggested by the first derivatives.

A comparison of the 1950 structure (Table 5) with that of 1940 illus- trates the danger of inferring stable ecological structures from a single period of observation. While it is true that the 1950 socioeconomic factor (F2) is almost identical to that of 1940, the other two factors have changed in important ways. First, the foreign-born white indicator is no longer only randomly associated with the social disorganization dimension (Fl); rather, during 1950, it has a strong, negative loading. Second, the racial/ ethnic factor is no longer "pure"; in 1950 it is significantly confounded with indicators of housing status. Finally, the delinquency rate does not load on the racial/ethnic dimension during 1950.

To appreciate the substantive implications of these changes, it is necessary to place them within the context of a very important shift in the settlement patterns of blacks in Chicago that occurred between 1940 and 1950 as a result of two 1948 Supreme Court decisions (Shelley v Kraemer and Hurd v Hodges) that held that racially restrictive covenants in housing could not be legally enforced. Duncan and Duncan have documented that 90 percent of Chicago's black population and less than 1 percent of the non-black population resided in census tracts traditionally referred to as the Black Belt that were more than half black in both 1930 and 1940. In addition, the population density in these almost exclusively black areas was over three times that in almost exclusively non-black areas; as Abra- hamson commented, these areas were filled to bursting in the late 1940s. However, with this legal housing barrier removed, residents of the Black Belt moved into adjoining white areas in unprecedented numbers; the number of racially mixed census tracts in Chicago (defined by Duncan and Duncan as having more than 1 and less than 97.4 percent black composition) increased from 135 in 1940 to 204 in 1950. Therefore, the issues of housing and race were strongly joined during this period in Chicago. This connection is reflected in the third factor for 1950.

As noted by Cressey, the movement of blacks into predominantly white areas always met violent opposition in Chicago; Tuttle, for example, documents a minimum of 26 bombings aimed at isolated black residences in once all-white neighborhoods between 1917 and 1919. However, as long as blacks resided primarily in the Black Belt, such movement into white



406 / Social Forces Volume 63:2, December 1984.

Table 5. FACTOR STRUCTURE FOR 1950*

Factor Factor Factor Un ique Variable 1 2 3 Variance

DEL .807 0* Q*1 .427 (.084) (.074)

NW .954 o*1 -.371 .099 (.058) (.052) (.023)

FB -*533 01*-.021 (.103) (.084)

UNEMP 1.044 Q* Q*1 9040 (.049) (.018)

PROF Q* 1* Q% .124 (.088)

OWNOCC -.981 -.507 -.496 .341 (.135) (.136) (.112) (.077)

DEN 1* 0* -.193 .119 (.048) (.024)

ED 0* .792 0* .442 (.102) (.093)

Factor Correlations

1.000*%

-.542 1.000* (.090)

of' -.4oi 1.000* (.094)

2=20.9300 d.f= 16 p= .1810

*Standard errors are given in parentheses. All loadings and correlations marked with an asterisk have been constrained to these values by the model.




areas was relatively uncommon and widely dispersed throughout the city. The open housing decisions of 1948 changed this pattern dramatically. As a result, many all-white areas of the city felt threatened by the possibility of an influx of blacks and reacted against this threat.

Hirsch, in his discussion of six serious racial disturbances that occurred in Chicago between 1947 and 1957, noted the "communal" aspects of such riots: "each community rose up in its own defense, produced its own defenders, and proceeded to fight for its self-defined goals and inter- ests" (345). In addition, he notes that ethnic whites in particular reacted strongly to their new position as "natural buffers between fleeing (more affluent) whites and inner-city blacks" (350), and documents the wide- spread participation of such ethnic groups in the six riots. Thus, it appears that, due to perceived racial threats, the "defended community" (see Sut- tles) became an especially salient feature of Chicago's structure during 1950 since two characteristics of such areas as defined by Suttles were prominent at this time: (1) attempts to keep the neighborhood identity (white) as a stable judgmental reference and (2) sentiments that the residents shared a common fate at the hands of city planners, realtors, politi- cians, and industry. Such processes account for the shift in the first factor between 1940 and 1950: the negative loading for FB implies that such ethnic neighborhoods became especially organized during this period.

In fact, it is likely that the Bumside community emerges as an out- lier in 1950 because of a similar consideration. Burnside was a small, sharply defined ethnic enclave of Hungarians and Poles in 1950. In fact, its concentration of foreign-born whites (25.6 percent) was the second highest in the city; only 0.2 percent of the population were nonwhite. It was also a predominantly blue-collar community (only 2.2 percent of the labor force were professionals) with a great deal of residential stability (60.7 percent of the dwelling unitl were owner-occupied). However, during 1950, it had the highest delinquency rate in the city of Chicago-47.2 court referrals for every 1,000 males aged 10 to 17. This was almost twice as high as the second most delinquent area (24.1) and far greater than the average of the other local communities (6.8).

Part of this large rate may be accounted for by the small population of Burnside-there were only ten petitions filed for 212 male youths. How- ever, Burnside was also in a position to exhibit some of the characteristics of the defended community. In 1949, two riots involving the movement of blacks into previously all-white areas (one of which received national ex- posure) took place in communities not far away. In addition, the area immediately to the southwest (Roseland) had changed from 4.2 percent to 18.4 percent black between 1940 and 1950. Burnside residents may also have foreseen future developments in Chatham (which surrounds Bum- side to the west and north)-it changed from 0.8 percent to 63.7 percent black between 1950 and 1960 (while Burnside maintained its nearly all-




white status). Thus, actual and potential racial changes were occurring on all sides of it.

Suttles has argued that one way in which defended neighborhoods may attempt to protect themselves is through the efforts of local delinquent gangs; this position receives support from Abrahamson's descrip- tion of delinquent activity in a Chicago neighborhood undergoing rapid change and Hirsch's observation that many of the people arrested in the 1947-57 riots were juveniles. Burnside, therefore, may have reacted to these changes in a manner far more extreme than the other ethnic areas; recall that its inclusion in the analysis caused the correlation between DEL and FB to shift from moderately negative to almost zero.

It is not possible with these data to determine the correctness of this explanation of the Burnside phenomenon. However, if it has some validity, then the high rate of delinquency in Bumside represents to some extent a reaction to dynamics taking place outside of the community, as opposed to the intracommunity processes that are typically considered in ecological analyses.

The final deviation of the 1950 structure from that of 1940 is the failure of delinquency rates to load on the third factor during 1950. We must admit that the underlying reason for this shift is not apparent to us and calls for further analysis. However, its absence, and the other changes in the structure that have been noted, strongly support the general argument of this paper, that is, the ecological structure of delinquency is sensi- tive to urban dynamics which may not be constant over time. Therefore, a conclusion of an invariant structure based on either the 1940 or 1950 data alone would have been in great error.

The final step of this analysis is to determine the extent to which the dynamics reflected in the 1950 structure persisted and appear in the 1960-70 patterns of association. Since the structure for this period has one more factor than 1940 or 1950, the fit was made using a principal four- factor solution as the initial model, and modifying it as before.

The 1960-70 factor structure (Table 6) indicates that the 1950 processes were outliers in terms of the ongoing structure of the ecological processes in Chicago. Although it is true that the ecological structure became more differentiated between 1940 and 1960-70, the two dimensions upon which delinquency loads for 1940, 1960, and 1970 are strikingly similar-a racial/ethnic factor and a social disorganization factor; in addition, for these three time periods, both of the delinquency-related dimensions are orthogonal.

Since legal restrictive covenants were not reimposed after 1950, it is interesting that none of the 1950 structure that reflects such racial move- ments persists through 1960-70. In fact, Berry and Kasarda have discussed how the defended community phenomenon was prominent in several Chicago neighborhoods between 1960 and 1970, again due to the residen-




Table 6. FACTOR STRUCTURE FOR 1960-70

Factor Factor Factor Factor Unique Variable 1 2 3 4 Variance

DEL .528 .703 0* * .255 (.075) (.087) (.050)

NW .827 .534 0* 0Q .099 (.070) (.069) (.035)

FB -1* 0* 0* .147 (.074)

UNEMP 0* .234 .820 0* .097 (.060) (.060) (.029)

PROF 0* 0* 0* 1* .075 (.150)

OWNOCC 0* -1* 0* 0* .058 (.087)

DEN Q* 0* 1* 0* .084 (.037)

ED 0* 0* 0* .539 .730 (.128) (.131)

Factor Correlations

1. 000*L

0* 1.000*

.669 .479 1.000* (.059) (.075)

0* 0* -.357 1.000 (.077)

x = 25-7301 d.f.= 18 p= .1060

*Standard errors are given in parentheses. All loadings and correlations marked with an asterisk have been constrained to these values by the model.




tial movement of blacks. However, Bursik and Webb (Table 3) have shown that the overall form of racial change in Chicago was not constant between 1940 and 1970. Seventy-five percent of all racial changes between 1940 and 1950 reflected the initial movement of blacks into the neighborhood. In later years, this was not the dominant type of racial change experienced by the local communities, although it remained an important form. There- fore, we suggest that the 1950 pattern is distinctive because the racial changes reflected radical departures from past patterns.

Conclusions

Although the preceding analysis has presented evidence of two fundamental latent constructs associated with delinquency in Chicago during 1940, 1960, and 1970, it has also documented an important shift in this structure during 1950; we have suggested that this shift is related to changes in black residential patterns that resulted from the open housing decisions of 1948. An interpretation of the 1950 pattern was possible only through a consideration of long-term dynamics of residential movement within Chicago. Thus, the findings suggest that generalizations made from cross-sectional findings may be of only limited utility in the development of community-level models of delinquency.

Such concerns go far beyond the question of inferential validity. Rather, as Bottomore has put it, they also reflect contrasting conceptions of society as a "fixed, stable structure" as opposed to a "process in which there is continual breakdown and renewal" (159). As sociologists inter- ested in delinquency, we certainly want to gain a sense of regularity in the internal dynamics of local communities. Yet, we hope that this paper has illustrated that it is often the departures from such regularity that shed a great deal of light on the underlying processes that give rise to a phenomenon.

Notes

1. Given the focus on delinquency in this paper, we will not discuss ecological work that has dealt with criminal (adult) behavior, such as Schmid. 2. Kornhauser has shown that Shaw and McKay emphasized the mutuality of these interrela- tionships and never developed a true causal ordering of their community and delinquency indicators. For an example of how the level of crime in an area can directly affect its composition, see Bursik. 3. Similar analyses of 1940, 1960, and 1970 did not produce evidence of any such influential observations. The largest Cook's D's for these years were .44, .74 and .57 respectively. These calculations were made with the BMDP9R program. 4. This formula for degrees of freedom is for the general analysis of covariance matrices. Since we are dealing with correlation matrices, we have constrained the diagonals of the estimated factor correlation matrices to 1, freeing 8 more degrees of freedom. Thus, instead




of ?/2(3)(8)(9) = 108 degrees of freedom, we have 116. Likewise, in the year-by-year compari- sons, there are 44 degrees of freedom rather than 36. All the confirmatory analyses were produced using LISREL IV. 5. In this test, the factor structure matrix is left unrestricted and all unresticted solutions give the same fit to the observed correlation matrix (Joreskog, a). Therefore, the choice of an orthogonal or oblique solution in this test is an arbitrary decision.

Appendix 1. ADJUSTED 1950 CORRELATION MATRIX (BURNSIDE COMMUNITY DELETED)


DEL 1.000

NW 0.640 1.000

FB -.349 -.726 1.000

UNEMP 0.766 0.875 -.486 1.000

PROF -.373 -.339 -.031 -.493 1.000

OWNOCC -.527 -.513 0.098 -.660 0.174 1.000

DEN 0.648 0.894 -.603 0.901 -.461 -.573 1.000

ED -.156 -.131 -.154 -.298 0.697 0.029 -.238 1.000

Appendix 2. POOLED 1960-70 CORRELATION MATRIX


DEL 1.000

NW 0.776 1.000

FB -.512 -.747 1.000

UNEMP 0.746 0.808 -.551 1.000

PROF -.330 -.321 0.208 -.463 1.000

OWNOCC -.698 -.555 0.091 -.642 0.154 1.000

DEN 0.679 0.766 -.598 0.890 -.546 -.502 1.000

ED -.150 -.063 -.079 -.177 0.498 0.178 -.261 1.000




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Urban Dynamics and Ecological Studies of Delinquency