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Community context and dropout rates
Chikira and Youth Services Review, Vol. 14, pp. 273-288.1992 Printed in the USA. All rights reserved.
019&7409/92 Copyright 0 1992 Pergmon
s5.oat.oo Press Ltd.
Community Context and Dropout Rates Josefina Figueira-McDonough Arizona State University
This paper explores the relationship between community characteristics and school dropout rates, The dropout level has reached crisis proportions in poor urban communities. This study examines the structural dimensions of communities that might induce or facilitate dropout. A large urban center with a total of 340 census tracts constitutes the sample; data are drawn from the 1980 census and from local schools.
This paper is part of a larger research effort focusing on communities and the “puerilization” of poverty. The focus is on the reproduction of poverty or, more precisely, the entrapment of the children of the poor in the underclass. Although we accept the common wisdom that behaviors such as dropping out of school, teenage pregnancy and delinquency are important contributors to such entrapment, the main focus of the research is on the structural conditions that induce or facilitate such behaviors. A crucial factor contributing to the permanency of the underclass is that contrary to the long held belief of social mobility and temporary poverty in this country, membership in the underclass has become an assigned status for the children of the very poor (Moroney, 1991, pp. 205207). With a poverty rate of about 25 percent, children are the most deprived group in the United States, and there is evidence of continuing deterioration (Bureau of the Census, 1987). The puerilization of poverty biases issues that intrinsically challenge the core of a society committed to liberal democratic ideals. Such a system does not promise equal outcomes to its citizens but is committed to equal opportunity. The conservative interpretations that poverty is self-made cannot be credibly applied to children. The fact that minority children are five times more likely to be poor than nonminority children further indicts the supposed fairness of the system in guaranteeing equal opportunity (Swinton, 1987). Requests for reprints should be sent to Josefina Figueira-McDonough, School of Social Work, Arizona State University, 244 West Hall, Tempe, Arizona, 85287-1802.
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For some years now, the conceptualization of the underclass as a description of pockets of urban poverty in the major metropolitan centers of America has taken the place of previous explanations of the culture of poverty. Although the two formulations are not totally independent, the change signifies more than a substitution of labels describing the same phenomenon, since “underclass” has become for many researchers synonymous with ghetto poverty (e.g., Danziger 8z Gottschalk, 1987; Wilson, 1987). This conveys the idea of a distinct (isolated, segregated) place that is an essential ingredient in magnifying the effects of economic deprivation. The underlying assumption is that geographic concentration of permanent poverty has consequences that go beyond the personal or familial experience of poverty. In fact, concern with the underclass, which represents only about 7 percent of all the poor in the United States (Ellwood, 1988, pe 193), reflects this belief in the multiplicative effects of bounded deprivation on social deviance, including behaviors that reinforce the future entrapment of the young in such settings. Given this conceptualization of the underclass, it is astonishing that most studies devoted to the issue have neglected the community level of analysis. A review of such studies published by the Social Science Research Council (Gephart & Pearson, 1988; Pearson, 1989) shows that they concentrate either on the macro-socioeconomic changes that produced the underclass (e.g. reduction of blue collar labor demand) or on the micro-mechanisms that accompany or transmit specific behaviors (e.g. family structure and socialization patterns). Only recently have communities been recognized as important intervening strata, mediating the impact of systemic changes and creating more or less viable contexts for diverse family structures (e.g., Jencks & Mayer, 1989). This paper will report on the part of the study that explores the effect of varying community contexts on school dropout rates. Alternate Interpretations of the Reproduction of Poverty The original purpose of culture-of-poverty constructs was to interpret the desperation of and the constraints on those living in extremely deprived conditions (Clark, 1967; Harrington, 1962). Over time, however, “culture of poverty” terminology came to signify that the poor were trapped by their own norms and values (e.g., Banfield, 1968). The poor, it was proposed, shared a deviant culture that was conducive to self-defeating behavior and prevented their integration in mainstream America. From this perspective, the high incidence of school drop-outs in underclass communities reflects an indifference to educational achievement, transmitted to children by an environment dominated by uneducated or alienated adults (Coleman, Campbell & Mood, 1966).
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Situationalists, on the other hand, view the incidence of non-normative behaviors in the underclass as adaptations to negative circumstances, namely, lack of opportunity (Liebow, 1967). Students quit school because schools in the inner city are overcrowded, teachers are overworked, learning is not positively reinforced, nor is there any evidence that a high school degree guarantees living wages (Apple, 1989; Grant Foundation, 1988; McGahey, 1986). Evidence has been collected over the past decade contradicting the inference that the poor do not share the values and norms of the larger society (e.g., Corcoran, Duncan, and Gurin, 1985). Furthermore, it has been argued that the anthropological concept of dynamic culture can bridge the two explanations (Hannerz, 1989: 183). Since the underclass poor have been exposed for long periods to negative conditions, it might be expected that some of their adaptations will become internalized as norms of behavior. From a Mertonian perspective, social strain is the source of such adaptations that can range from rebellion to withdrawal or illegal innovation (e.g., Figueira-McDonough, 1983). Were economic conditions and incentives to change and stabilize, behavior and norms would adapt to the new circumstances (e.g., Gans, 1968, p. 211). Significantly, according to this line of reasoning, norms are adaptive and the dynamic pull resides in the situation. The present research, cross-sectional and drawing on secondary data, is not designed to test this evolutionary scenario. Given the chronic nature of membership in the underclass, it is reasonable to expect a degree of coherence between behavioral norms and adaptive behavior. Data This study covers a major urban center (Detroit), with high rates of poverty and segregation. The unit of analysis is the census tract. The information used to characterize these geographic units has been obtained from the 41 original data tapes of the 1980 Census Summary tape File 3, Part A. The extraction of the relevant variables was done by the Panel Study of Income Dynamics at the Institute for Social Research, University of Michigan. The Census Extract Data set includes information on housing, ethnicity, family structure, income, education and labor force activity for the 341 tracts of the city of Detroit. From the city school systems, information on dropouts by schools have been obtained so that local rates could be checked. Dimensions Selected The dropout problem has emerged as a front-line issue in the most popular journals in education, daily newspapers, and statements by federal,
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state, and local officials. These messages tend to transmit the belief that solving the dropout problem in schools would go a long way toward alleviating the social and economic problems of local communities (Apple, 1989). Despite the popularity of this unilinear approach to the complex issue of the reproduction of the underclass, effective comprehensive programs depend on an understanding of contextual dimensions affecting the phenomenon. Apple (1989) and McGahey (1986), for example, emphasize the strong association between economic marginalization in a community and dropout rates. They argue that in areas with a high level of unemployment and/or exclusion from the labor market, young people are unlikely to perceive the completion of high school as the vehicle to a stable and decently paid job. Over time, ecological studies of social deviance have argued that poor communities are more prone to disorganization when there is high transiency among their population and evidence of physical decay in their environment (Newman, 1973; Sampson, 1988; Shaw & McKay, 1942; Stark, 1987; Yancey, 1972). Disorganized communities, in turn, are less able to preserve dominant norms and to transmit them to their young (Reissman, 1964; Simmel, 1950; Wirth, 1938). Most of the studies on dropout rates have focused on individual units and have paid special attention to parental education and supervision. The findings tend to support the expectation that parental low education and supervision are associated with high dropout risk of the children (Galloway, 1985; Sinclair & Ghory, 1987; Wells, 1990). The same argument can be extrapolated for the study of communities. An environment with few educated individuals is less likely to reinforce and uphold school goals, as well as offering rare adult models in educational achievement. Also, the more restricted aggregate availability of adults for supervision, the looser the climate of adult control in that community. In sum, economic marginalization, transiency, and decayed physical environment are seen as contexts aversive to school retention in the community. Also, the pervasiveness of low adult education and lack of availability of adult supervision are expected to contribute to neighborhood dropout rates. Operationalization of the Predictive Dropout Model Table 1 lists the measures to be used as indicators of the characteristics of the underclass. As argued previously, these dimensions are hypothetically predictive of dropout rates.
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Rates
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Table 1 Characteristics of the Underclass (e.g., Ellwood, 1988; Wilson, 1987)
Family:
High % of Female Headed Households Low Male/Female Ratio (16-34) High % Public Assistance High number of Children per Household
Education:
Low % of High School Graduates
Transiency:
High % of Unattached Individuals High Residence Mobility
Segregation:
High Concentration of Minority Residents
Phys. Deterioration:
High % Vacant Housing Units High % Rental Housing Units
Economic Marginalization:
High 8 of Nonworking Among the Adult Population
A high percentage of female-headed households is often taken as an indicator of dysfunctional families (Schuerman & Kobrin, 1986; SimchaFagan & Schwartz, 1986). More sophisticated arguments underscore the economic and nurturant difficulties of having only one adult responding to the needs of children (Hogan & Kitagawa, 1985; Matsueda & Heimer, 1987; Schorr & Moen, 1979). More traditional arguments, as the one supporting the creation of male-only schools, contend that the absence of fathers reduces appropriate gender role guidance for young males (Reiss, 1986). One feature associated with a high percentage of female-headed households is a high out-of-wedlock birth rate. According to the “marriage pool” argument, unwed motherhood is an adjustment to low sex ratios (Bane, 1986; Children’s Defense Fund, 1987; Guttentag & &cord, 1983). Wilson (1987), for example, contends that for the high procreation ages (16-34), there is a low sex ratio in Chicago ghettos, leading not only to a greater availability of females to males, but also to the unavailability of “qualified” husbands for females. Unwed mothers, especially young ones, are at a disadvantage, economically and emotionally, to control their children. Dependence on public assistance translates into absolute levels of poverty and, for the most part, also involves single mothers. Furthermore, it carries with it a stigma likely to affect the whole family and the com-
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munity (e.g., Rodgers, 1986). Finally, the ratio of children per household defines the demands of supervision. In principle, the more children per household, the greater the demand for supervision in a given community. To characterize the educational level of a community, we use the percentage of adults (25 and over) that did not finish high school. The assumption is that tracts with a high percentage of people with low education are less likely to be involved with the schools and to have available models of school achievement. Transiency has been one of the major indicators of community disorganization used by urban ecologists (e.g, Sampson, 1988; Shaw & McKay, 1942; Stark, 1987) The percentage of unattached people and the mobility of the residents in each tract are used as indicators of this dimension. The equation of the underclass with the black urban ghetto speaks of the results of extreme segregation. The percentage of blacks in a tract gives us a direct measure of this segregation. The physical setting of a neighborhood has received the attention of ecologists, criminologists, and urban planners. These settings have been analyzed as indicators of anomie and also as opportunities for illegal activities (Skogan, 1990). Given the American ideal of house ownership, rentals are seen as either more transitional and/or more conducive to lack of residential attachment. The presence of vacant housing is viewed as a statement of the undesirability of the area and not only promotes opportunities for deviant behavior, but also attracts undesirables to the area (Newman, 1975; Schuerman & Kobrin, 1986; Yancey, 1972). Finally, poverty is a given in the classification of underclass areas and, for situationalists, a necessary antecedent. The issue of reproduction of such communities is thought to derive not directly from low incomes, but from the extended marginalization caused by weak links with the labor market (Apple, 1989; McGahey, 1986). The ratio of unemployed and out of the labor force to all people 16 years or older is the most direct measure of this alienation. Bivariate Analysis
Table 2 shows the correlational analysis between the 10 indicators selected. With the exception of three correlations (public assistance and female heads of households; public assistance and unemployed and out of the labor force; and low education and unemployment and out of the labor force), all the coefficients have medium to low values. When comparing the distribution of all variables between poor and nonpoor tracts, we find that all vary significantly in the expected direction, except sex ratio.
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Context and Dropout Rates
279
Table 2 Zero Order Correlation of all Underclass Indicators
FHHHCWHHM -.03 Sex Ratio Family & SubF F.H. CH 0- 15fHH Public Asst % w/o HS Vacant Housing Rent Housing Unatt P. Ratio Stability 5Y 8 Black Pop hemp & OOLF
-.40
-.02
.20
.80 .34
Vat HQM~~w2B!&OOLF~ .29 .OO .I4 .40 .52 .I0 .69
.61 -.05 .67 .51
.62 -.25 .57 .37 .61
.21 -.67 .04 .05 .48 .65
Unemp&
Drop-
-.16
-.25
.09
.I0
-.OO .11 .04 .21 -.23 -.39 -.51
.69 .39 .54 .13 .21 .22 -.15 .26
.65 .12 .82 .83 .60 .53 -.OO .13 .32
.20 .13 .32 .53 .38 .20 .07 -.06 -.14 .39
The analysis of variance using a detailed strata of poverty gives us a finer-grained view of the distribution of each variable by poverty level (see Table 3). Percent of families with female heads of household, percent of families with public assistance income, and percent of rental and vacant housing units vary significantly across all groups and in the predicted direction. Percent of the adult population without high school degrees, percent of blacks, and dropout rates show a similar pattern, although the interstrata differences in two or three instances are not significant. Proportion of unattached persons and stability vary only in relation to the poorest tracts, while ratio of children to households differentiates only the better off tracts from all others. In one instance, the only significant difference is in relation to the poorest tracts but in the direction opposite to expectation. Sex ratio is highest in the areas with 40% or more of the population under the poverty level. In sum, with the exception of children per household ratio and sex ratio, the attributes of the underclass are verified in the poorest Detroit neighborhoods. Multivariate Analysis
The previous analysis demonstrates that there is some multicollinearity among a couple of variables and that at least one variable shows very little variation and in the direction opposite to prediction. On these criteria, we
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280
reduced the nine predictors assistance and sex ratio).
of dropout rates to seven (eliminating
public
Table 3 Five Levels of Poverty Underclass Indicators by Analysis of Variance With Interstrata Contrast Analysis Sex Ratio Mean St. D. 98.1 13.0 1 2 91.0 13.0 94.3 33.5 3 4 91.2 28.1 5 105.6 45.0 F 2.85 Sig* .023 Interstratal,2,3,4-5 Sign* (T)
Fam & Sub FH Mean St.D. 22.7 10.4 37.8 10.8 49.8 12.5 61.8 13.5 66.6 12.1 144.1 <.CQO All<.000
CH O-15/HH Mean St.D. .615 .200 .766 .265 .811 .256 .804 .279 .791 .353 6.2 .OOO l-2,3,4,5
Public Asst. Mean St.D. 7.4 3.2 15.1 5.6 24.5 5.9 32.4 5.9 40.2 9.4 286.5 <.OOO All <.OOO
%NoHS Mean St.D. 1 33.1 12.4 2 39.8 11.2 3 51.5 11.7 4 56.4 8.7 5 61.0 9.1 F 72.6 <.OOO Sig Interstrata l-2 c.000 Sign 3-4-5 c.05
Vacant Hous. Mean St.D. 2.4 1.1 5.3 4.1 8.2 2.7 12.6 5.2 15.8 6.8 98.6
Rental Hous. St.D. Mean 19.0 15.1 31.0 17.0 43.2 15.3 51.3 11.7 60.5 13.3 74.1 <.OOO All <.OOO
Unatt P. Mean St.D. .139 .08 .157 .12 .155 .08 .195 .13 ,247 .16 6.8 <.OCQ 1,2,3-4-5
Stability Mean St.D. 1 61.1 10.1 2 58.6 13.9 3 59.4 15.0 4 59.6 9.9 5 54.1 11.9 F 2.4 Sig NS Interstrata 1,2,3,4-5
Blacks Mean St.D. 30.4 31.3 60.4 33.8 63.8 37.2 79.6 24.9 77.3 22.1 26.4 <.OOO l-2,3-4,5
C.000
All c.000
Unemp & OOLF Mean St.D. 44.3 6.2 49.5 7.0 58.8 6.5 64.8 5.7 70.9 6.3 175.7 C.000 All pairs e.000
Dropouts Mean StD. 14.0 10.0 18.3 11.9 23.2 11.5 24.9 14.3 31.0 19.8 13.8 <.OOO l-2-3,4-5
*In this and subsequent tables, significance is used as a criterion of stmnth of association, not for purposes of generalization, since information on the entire census of the city of Detroit is included.
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A stepwise regression for dropout rates included the selected predictors. The total variance explained was 40 percent, with percent of adults with low education accounting for more than half. The other three variables showing significant explanatory contribution were race, number of children per household, and proportion of unrelated persons.
Table 4 Stepwise Regression Analysis Predicting Percentage of Young Adult Dropouts
Low Education among Adults (ED 25-11) Black Population Number of Children per Household (CH O-15HH) Proportion of Unrelated Individuals Multiple R = .632
-.330 .405 .299
Cumulative R2 .282 .325 .353 .400
R Square = .400
Examination of the arguments on which the selection of the predictors of dropout was made led us tentatively to group them in a causal sequence. In spite of the limitations inherent in using cross-sectional data in this way, there is some exploratory merit to this analytical strategy. It proceeds by examining the empirical relationships among variables in the order specified below. These relationships are estimated by regressing each variable on those assumed to be causally prior. Nonsignificant paths are deleted, and the model is re-estimated to produce final path coefficients (see Table 5). The rules followed to order the variable are based on a criteria of immediacy: 1) education and family; 2) environmental characteristics of transiency, segregation, and physical deterioration: and 3) economic marginalization. As expected, the results of the path analysis explained about the same percentage of the variance as the stepwise regression (R2 = .41), and the direct effects show a similar hierarchy of the relevant variables: low education, proportion of children per household, percentage of blacks, and proportion of unrelated individuals. Economic marginalization has no direct impact on dropout because of its remote position in the model and its fairly high correlation with low education and vacant housing. Inspection of the paths shows, in fact, three
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282
sequences of interest: 1) economic marginalization leads to low education leads to high drop out (indirect effect = .42); 2) economic marginalization leads to vacant housing leads to high dropout (indirect effect = .16); and 3) high economic marginalization leads to high segregation leads to low dropout rates (indirect effect = .lO).
Table 5 Path Analysis - Dependent Variable Dropout Rate
(Betas) Dropout F**E&I&on Education Number of Children Unrelated Indv Stability % Black Vacant Hous. Econ. Marg. MR R2
.35** .20** .oo -.32** .16 -.12
Number Unrel Vacant CWHHhxL St&iliQBlacksHousine
-.07* -.90** .21** -.34** -.23** .32** .17** .25** .78** -.02
.09
.07
.31**
.60**
.64 .41 .40
Adj. R2 ** Sig c.000 * Sig c.05
Environment variables also show some important paths: 1) high proportion of unrelated individuals leads to low number of children per household which leads to high dropout rate (indirect effect = .33); 2) high mobility leads to low education which leads to high dropout rate (indirect effect = . 11); and 3) high segregation leads to high education which leads to low dropout rate (indirect effect = .12); and 4) vacant housing, segregation, and mobility leads to high number of children per household which leads to high dropout (indirect effects = .09, .lO, . 11). These paths differentiate the relationship of the variables according to the model adopted. We can conclude that economic marginalization affects education negatively and dropout rates positively and, also, predicts decrepit housing with somewhat high number of children per household, which in turn affects high dropout rates.
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Two findings are unexpected: 1) the marginal impact of mobility measures; and 2) the negative effect of segregation on education and dropout rates. The marginal impact of mobility might be due to limitations of measurement, as well as conceptual inadequacy. The measure used in this study is derived from information of respondents reporting having lived in the same house during the previous five years. While this measure is adequate as a general indicator of residential stability, it cannot measure the incidence of mobility or the range of the move (within or across communities). In addition, the concept of mobility needs to be refined. Although during the time of the early ecological studies its meaning was still intrinsically tied to large demographic movements, there is evidence that in later periods communities developed mechanisms for handling ordered geographical mobility (e.g., 1981; Taub, Taylor, & Dunham; Whyte, 1956). A separation between these two concepts is necessary to clarify the expected relation between mobility and disorganization (Figueira-McDonough, 1991). Findings of the high value given to education by blacks and assessments of the failures of school integration (Corcoran, et. al, 1985; Jewell, 1988; Mahard & Crain, 1983; St. John, 1975; Sullivan, 1989) support indirectly the segregation path identified in our analysis. Furthermore, examining the association between race and dropout rates for all the SMSA tracts, we found a weak but positive association (.20), while the same correlation in the city was negative (-.15). Obviously, the racedropout association for suburban Detroit is in the expected direction but in predominantly black Detroit, race homogeneity is favorable to school retention. Discussion and Conclusion The most popular slogans regarding the economic recovery of the underclass focus on issues of rehabilitation of the family and education reform, avoiding the more direct realities of poverty and unemployment. Granted that the poorest communities are economically marginalized in terms of levels of unemployment, insecure employment, and exclusion from the labor force, the main question addressed here is how other environmental and population characteristics are affected by deprivation and, in turn, affect dropout rates. As expected, the incidence of female heads of households and percent of families receiving public assistance income increased with level of poverty, confirming the phenomenon of the feminization of poverty (e.g., Rodgers, 1986; Schorr & Moen, 1979). Percentage of black population, rate of unemployment, unstable work, and exclusion from the labor force also fitted the attributions of the underclass (e.g., Ellwood, 1988; Wilkerson & Gresham, 1989). Level of education
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and dropout rates varied, also, in the expected direction. No evidence of major differences in the greater number of children per household and transience was found by degree of poverty. Wilson’s hypothesis (1987) of the high level of single motherhood as a function of low sex ratio was not supported in the Detroit data. There was no difference in sex ratio by level of poverty, except in relation to the poorest group. This group, however, showed the highest sex ratio for the ages 16 to 34. Eggers and Massey (1991) found a similar lack of association in their study of urban communities. It is possible that the measure of sex ratio is too limited to reflect Wilson’s marriage pool hypothesis, which conceptually excludes from the pool unemployed young men and those in trouble with the law. The results of the stepwise regression analysis of dropout rates isolated four major predictors: low adult education, segregation, high number of children per household, and high proportion of unrelated individuals. The outcome of the ordered regression was quite similar but permitted the identification of distinctive paths. Tracts with high economic marginalization have a deteriorated physical environment in which the incidence of number of children per household is somewhat higher, which, in turn, predicts high school dropout rate. A still stronger path indicates that high economic marginalization predicts low education among adults that, in turn, predicts a high level of dropout. The most intriguing path, however, involves segregation. While, as expected, economic marginalization is related to segregation, segregation predicts somewhat higher education and lower dropout rates. Although poor urban communities in Detroit have, in general, the characteristics attributed to them by the students of the “underclass,” the clearest differences relate to economic marginalization, feminization of poverty, segregation, and education. Our analysis suggests that decreasing the dropout rate might not only require school reform but also a commitment to adult education with the real incentive of stable work. Also important would be programs designed to increase the supervisory capability of the community through, for example, after school programs. The findings that predominantly black communities have higher levels of education and lower levels of dropouts than other communities with greater racial mixture are especially noteworthy, since those communities tend to lack experiential economic reinforcement for educational goals. This unexpected sequence in Detroit seems to suggest that a system guaranteeing equal public expenditures for all students might be more successful for student retention than forced schemes of school integration (Eitzen & Zinh, 1989, pp. 430-434). Given the cluster of predictors of dropout rates and their concentration in the poorer neighborhoods, proposals of school reform promoting higher
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curricular and discipline demands might increase rather than decrease the dropout rates in those areas (Clayton, 1989; McDill, Matriello & Pallas, 1986). The increase of costs of attending school in a setting devoid of experiential rewards for education is likely to make the experience irrelevant for youths trapped in poor communities. Geschwendler’s (1991) findings on the relation between minority discrimination and work effort, as well as the value given to children’s education, offer some insights about the future of the association between segregation, education, and dropout rates found in our study. Geschwendler argues that groups discriminated against have historically tried to compensate for it by increasing their work effort (as evidenced by a higher involvement of wives in paid labor) and by placing greater value on children’s education. The promise of this adaptation, in the case of the black population, seems, however, to be seriously disrupted at the present time. The number of complete families has been decreasing for the general population and at an accelerating rate in the lower classes (Schorr & Moen, 1979). The urban underclass does not only have a high rate of single parenthood, which is itself related to barriers to access to work (Bane, 1986; Children’s Defense Fund, 1982), but it is also predominantly made up of minorities. The possibility of compensating for discrimination through the generation of two incomes is, therefore, severely curtailed. The belief of advancement through education received a degree of positive reinforcement through the affirmative action efforts of the sixties and most of the seventies. The eighties, however, eroded this promise. Passe1 (1991), reporting on the findings of Bond and Freeman about the diminishing returns of education for blacks, defines unambiguously this state of affairs. Between 1975 and the present time, the white-black male weekly income gap, when controlling for education and experience, increased from 11% to 18%. In the same period, the racial difference in unemployment went from 9% to 15%. The question becomes to what extent this dissociation between education and economic outcomes will have adverse consequences on school retention, especially in the Midwest where the losses have been the most extreme. Indeed, we know that the black dropout rate has increased by 20% for the whole nation and twice as much for Detroit (Detroit Public Schools, 1990). It should be evident that prevailing school reforms cannot remedy this accelerating deviance from the crucial liberal-democratic principle of equal opportunity (Bowles & Gintis, 1972) without accompanying efforts to change the poor communities’ economic and environmental constraints impacting on young people.
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Gans, H. (1968). Culture and class in the study of poverty: An approach to antipoverty research. In D.P. Moynihan (Ed.), On understanding poverty: Perspectives from the social sciences. (pp. 201-228). New York: Basic Books. Gephart, M.A. & Pearson, R. (1988). Contemporary research on the urban underclass. Items, 42, l/2, l- 10. Geschwendler, J. A. (1991). Ethgender, women’s waged labor and economic mobility. Presidential Address, Annual Meetings of the Society for the Study of Social Problems, Cincinnati, Ohio. Grant Foundation. (1988). The declining economic fortunes of young Americans, Grant Foundation Report. Guttentag, M. & Secord, P. (1983). Too many women: The sex ratio question. Beverly Hills, CA: Sage. Hannerz, U. (1989). Soulside. New York: Columbia University Press. Hatrington, M. (1962). The other America. New York: McMillan Company. Hogan, P. & Kitagawa, E. (1985). The impact of social status, family structure and neighborhood on the fertility of black adolescents. American Journal of Sociology, 90.925-955. Jencks, C. & Mayer, S. (1989). The social consequences of growing up in a poor neighborhood. Working paper. Evanston, JL: Center for Urban Affairs and Policy Research, Northwestern University. Jewell, K. S. (1988). Survival of the black family: The institutional impact of U.S. policy. New York: Praeger. Liebow, E. (1967). Tally’s comer. Boston: Little Brown. Mahard, R. E. & Cram, R. L. (1983). Research on minority achievement in desegregated schools. In C. H. Russell & W. D. Hawley (Eds.), The consequences of school desegregation. (pp. 35-52). Philadelphia: Temple University Press. McDill, E., Matriello, G. & Pallas, A. (1986). A population at risk: Potential consequences of tougher school standards for student dropouts. In Gary Matriello (Ed.), School dropouts: Patterns and policies. (pp. 106-147). New York: Teachers College Press. Matsueda, D. & Heimer, K. (1987). Race, family structure and delinquency. American Sociological Review, 52,824-40. McGahey, R. M. (1986). Economic conditions, neighborhood organization and urban crime. In A. J. Reiss, Jr. & M. Toney (Eds.), Communities and crime. (pp. 231-270). Chicago: The University of Chicago Press. Moroney, R. (199 1). Social policy and social work: Critical issues on the werfare state. New York: Aldine De Gruyter. Newman, 0. (1973). Defensible: Crime prevention through urban design. New York: Collier. Passell, P. (1991, August 28). Economic scene: Blacks’ setbacks by association. New York Times, C2. Pearson, R. (1989). Economy, culture, public policy and the urban underclass. Items, 43, 2, 23-26. Reiss, A. (1986). Why are communities important in understanding crime. In A. Reiss & M. Tonry (Eds.), Communities and crime. (pp. l-33). Chicago: The University of Chicago Press.
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Reissman, L. (1964). The urban process. New York: The Free Press. Rodgers, H. R. (1986). Poor women, poorfamilies. Armonk, NY: M.E. Sharpe, II-K.
Sampson, R. (1988). Local friendship ties and community attachment in mass society. American Sociological Review, 53, 766-779. Schorr, A. L. & Moen, P. (1979). The single parent and social policy. Social Policy, 9, 15-21.
Schuerman, L. & Kobrin, S. (1986). Community careers in crime. In A. Reiss & M. Tom-y (Eds.), Communities and Crime. (pp. 67-100). Chicago: The University of Chicago Press. Shaw, C. R. & McKay, C. (1942). Juvenile delinquency and urban areas. Chicago: The University of Chicago Press. Simmel, G. (1950). The stranger, the metropolis and mental health. In Kurt Wolff (Ed.), The sociology of Georg Simmel. (pp. 402-426). New York: The Free Press. Simcha-Fagan, 0. & Schwartz, J. (1986). Neighborhood and delinquency: An assessment of contextual effects. Criminology, 24,667-704. Sinclair, R. L. & Ghory, W. J. (1987). Reaching marginal srudenfs. McCutchan Publishing Corporation. Skogan, W.G. (1990). Disorder and decline: Crime and the spiral of decay in American neighborhoods. New York: The Free Press. St. John, N. H. (1975). School desegregation: Outcomes for children. New York: John Wiley and Sons. Stark, R. (1987). Deviant places: A theory of the ecology of crime. Criminology, 25,893-910.
Sullivan, M. L. (1989). Getting paid: Youth crime and work in the inner city. Ithaca: Cornell University Press. Swinton, D. (1987). The status of black America 1987. New York: National Urban League, Inc. Taub, R.P., Taylor, D.G. & Dunham, J.D. (1984). Paths of neighborhood change. Chicago: The University of Chicago Press. Thurow, L. (1975). Generating inequality. New York: Basic Books. U. S. Bureau of the Census (1985). Poverry areas in large ciries. 1980 Census of Washington, DC: u. s. the Population, Subject Reports, Volume 2. Government Printing Office. Wells, S. E. (1990). At-risk youth. Englewood, CO: Teacher Ideas Press. Whyte, W. (1956). The organization man. Garden City, NY: Doubleday Anchor Books. Wilkerson, M.B. & Gresham, J.H. (1989). The racialization of poverty. The Nation, July 24131, 126-132. Wilson, W.J. (1987). The truly disadvantaged. Chicago: University of Chicago Press. Wirth, L. (1938). Urbanism as a way of life. American Journal of Sociology, 44, l-24. Yancey, W. (1972). Architecture, interaction and social control. In L. Wholwhil (pp. 126-136). & D. H. Carson (Eds.), Environment and Social Sciences. Washington, DC: American Psychological Association.
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Community Context and Dropout Rates Josefina Figueira-McDonough Arizona State University
This paper explores the relationship between community characteristics and school dropout rates, The dropout level has reached crisis proportions in poor urban communities. This study examines the structural dimensions of communities that might induce or facilitate dropout. A large urban center with a total of 340 census tracts constitutes the sample; data are drawn from the 1980 census and from local schools.
This paper is part of a larger research effort focusing on communities and the “puerilization” of poverty. The focus is on the reproduction of poverty or, more precisely, the entrapment of the children of the poor in the underclass. Although we accept the common wisdom that behaviors such as dropping out of school, teenage pregnancy and delinquency are important contributors to such entrapment, the main focus of the research is on the structural conditions that induce or facilitate such behaviors. A crucial factor contributing to the permanency of the underclass is that contrary to the long held belief of social mobility and temporary poverty in this country, membership in the underclass has become an assigned status for the children of the very poor (Moroney, 1991, pp. 205207). With a poverty rate of about 25 percent, children are the most deprived group in the United States, and there is evidence of continuing deterioration (Bureau of the Census, 1987). The puerilization of poverty biases issues that intrinsically challenge the core of a society committed to liberal democratic ideals. Such a system does not promise equal outcomes to its citizens but is committed to equal opportunity. The conservative interpretations that poverty is self-made cannot be credibly applied to children. The fact that minority children are five times more likely to be poor than nonminority children further indicts the supposed fairness of the system in guaranteeing equal opportunity (Swinton, 1987). Requests for reprints should be sent to Josefina Figueira-McDonough, School of Social Work, Arizona State University, 244 West Hall, Tempe, Arizona, 85287-1802.
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For some years now, the conceptualization of the underclass as a description of pockets of urban poverty in the major metropolitan centers of America has taken the place of previous explanations of the culture of poverty. Although the two formulations are not totally independent, the change signifies more than a substitution of labels describing the same phenomenon, since “underclass” has become for many researchers synonymous with ghetto poverty (e.g., Danziger 8z Gottschalk, 1987; Wilson, 1987). This conveys the idea of a distinct (isolated, segregated) place that is an essential ingredient in magnifying the effects of economic deprivation. The underlying assumption is that geographic concentration of permanent poverty has consequences that go beyond the personal or familial experience of poverty. In fact, concern with the underclass, which represents only about 7 percent of all the poor in the United States (Ellwood, 1988, pe 193), reflects this belief in the multiplicative effects of bounded deprivation on social deviance, including behaviors that reinforce the future entrapment of the young in such settings. Given this conceptualization of the underclass, it is astonishing that most studies devoted to the issue have neglected the community level of analysis. A review of such studies published by the Social Science Research Council (Gephart & Pearson, 1988; Pearson, 1989) shows that they concentrate either on the macro-socioeconomic changes that produced the underclass (e.g. reduction of blue collar labor demand) or on the micro-mechanisms that accompany or transmit specific behaviors (e.g. family structure and socialization patterns). Only recently have communities been recognized as important intervening strata, mediating the impact of systemic changes and creating more or less viable contexts for diverse family structures (e.g., Jencks & Mayer, 1989). This paper will report on the part of the study that explores the effect of varying community contexts on school dropout rates. Alternate Interpretations of the Reproduction of Poverty The original purpose of culture-of-poverty constructs was to interpret the desperation of and the constraints on those living in extremely deprived conditions (Clark, 1967; Harrington, 1962). Over time, however, “culture of poverty” terminology came to signify that the poor were trapped by their own norms and values (e.g., Banfield, 1968). The poor, it was proposed, shared a deviant culture that was conducive to self-defeating behavior and prevented their integration in mainstream America. From this perspective, the high incidence of school drop-outs in underclass communities reflects an indifference to educational achievement, transmitted to children by an environment dominated by uneducated or alienated adults (Coleman, Campbell & Mood, 1966).
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Situationalists, on the other hand, view the incidence of non-normative behaviors in the underclass as adaptations to negative circumstances, namely, lack of opportunity (Liebow, 1967). Students quit school because schools in the inner city are overcrowded, teachers are overworked, learning is not positively reinforced, nor is there any evidence that a high school degree guarantees living wages (Apple, 1989; Grant Foundation, 1988; McGahey, 1986). Evidence has been collected over the past decade contradicting the inference that the poor do not share the values and norms of the larger society (e.g., Corcoran, Duncan, and Gurin, 1985). Furthermore, it has been argued that the anthropological concept of dynamic culture can bridge the two explanations (Hannerz, 1989: 183). Since the underclass poor have been exposed for long periods to negative conditions, it might be expected that some of their adaptations will become internalized as norms of behavior. From a Mertonian perspective, social strain is the source of such adaptations that can range from rebellion to withdrawal or illegal innovation (e.g., Figueira-McDonough, 1983). Were economic conditions and incentives to change and stabilize, behavior and norms would adapt to the new circumstances (e.g., Gans, 1968, p. 211). Significantly, according to this line of reasoning, norms are adaptive and the dynamic pull resides in the situation. The present research, cross-sectional and drawing on secondary data, is not designed to test this evolutionary scenario. Given the chronic nature of membership in the underclass, it is reasonable to expect a degree of coherence between behavioral norms and adaptive behavior. Data This study covers a major urban center (Detroit), with high rates of poverty and segregation. The unit of analysis is the census tract. The information used to characterize these geographic units has been obtained from the 41 original data tapes of the 1980 Census Summary tape File 3, Part A. The extraction of the relevant variables was done by the Panel Study of Income Dynamics at the Institute for Social Research, University of Michigan. The Census Extract Data set includes information on housing, ethnicity, family structure, income, education and labor force activity for the 341 tracts of the city of Detroit. From the city school systems, information on dropouts by schools have been obtained so that local rates could be checked. Dimensions Selected The dropout problem has emerged as a front-line issue in the most popular journals in education, daily newspapers, and statements by federal,
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state, and local officials. These messages tend to transmit the belief that solving the dropout problem in schools would go a long way toward alleviating the social and economic problems of local communities (Apple, 1989). Despite the popularity of this unilinear approach to the complex issue of the reproduction of the underclass, effective comprehensive programs depend on an understanding of contextual dimensions affecting the phenomenon. Apple (1989) and McGahey (1986), for example, emphasize the strong association between economic marginalization in a community and dropout rates. They argue that in areas with a high level of unemployment and/or exclusion from the labor market, young people are unlikely to perceive the completion of high school as the vehicle to a stable and decently paid job. Over time, ecological studies of social deviance have argued that poor communities are more prone to disorganization when there is high transiency among their population and evidence of physical decay in their environment (Newman, 1973; Sampson, 1988; Shaw & McKay, 1942; Stark, 1987; Yancey, 1972). Disorganized communities, in turn, are less able to preserve dominant norms and to transmit them to their young (Reissman, 1964; Simmel, 1950; Wirth, 1938). Most of the studies on dropout rates have focused on individual units and have paid special attention to parental education and supervision. The findings tend to support the expectation that parental low education and supervision are associated with high dropout risk of the children (Galloway, 1985; Sinclair & Ghory, 1987; Wells, 1990). The same argument can be extrapolated for the study of communities. An environment with few educated individuals is less likely to reinforce and uphold school goals, as well as offering rare adult models in educational achievement. Also, the more restricted aggregate availability of adults for supervision, the looser the climate of adult control in that community. In sum, economic marginalization, transiency, and decayed physical environment are seen as contexts aversive to school retention in the community. Also, the pervasiveness of low adult education and lack of availability of adult supervision are expected to contribute to neighborhood dropout rates. Operationalization of the Predictive Dropout Model Table 1 lists the measures to be used as indicators of the characteristics of the underclass. As argued previously, these dimensions are hypothetically predictive of dropout rates.
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Rates
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Table 1 Characteristics of the Underclass (e.g., Ellwood, 1988; Wilson, 1987)
Family:
High % of Female Headed Households Low Male/Female Ratio (16-34) High % Public Assistance High number of Children per Household
Education:
Low % of High School Graduates
Transiency:
High % of Unattached Individuals High Residence Mobility
Segregation:
High Concentration of Minority Residents
Phys. Deterioration:
High % Vacant Housing Units High % Rental Housing Units
Economic Marginalization:
High 8 of Nonworking Among the Adult Population
A high percentage of female-headed households is often taken as an indicator of dysfunctional families (Schuerman & Kobrin, 1986; SimchaFagan & Schwartz, 1986). More sophisticated arguments underscore the economic and nurturant difficulties of having only one adult responding to the needs of children (Hogan & Kitagawa, 1985; Matsueda & Heimer, 1987; Schorr & Moen, 1979). More traditional arguments, as the one supporting the creation of male-only schools, contend that the absence of fathers reduces appropriate gender role guidance for young males (Reiss, 1986). One feature associated with a high percentage of female-headed households is a high out-of-wedlock birth rate. According to the “marriage pool” argument, unwed motherhood is an adjustment to low sex ratios (Bane, 1986; Children’s Defense Fund, 1987; Guttentag & &cord, 1983). Wilson (1987), for example, contends that for the high procreation ages (16-34), there is a low sex ratio in Chicago ghettos, leading not only to a greater availability of females to males, but also to the unavailability of “qualified” husbands for females. Unwed mothers, especially young ones, are at a disadvantage, economically and emotionally, to control their children. Dependence on public assistance translates into absolute levels of poverty and, for the most part, also involves single mothers. Furthermore, it carries with it a stigma likely to affect the whole family and the com-
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munity (e.g., Rodgers, 1986). Finally, the ratio of children per household defines the demands of supervision. In principle, the more children per household, the greater the demand for supervision in a given community. To characterize the educational level of a community, we use the percentage of adults (25 and over) that did not finish high school. The assumption is that tracts with a high percentage of people with low education are less likely to be involved with the schools and to have available models of school achievement. Transiency has been one of the major indicators of community disorganization used by urban ecologists (e.g, Sampson, 1988; Shaw & McKay, 1942; Stark, 1987) The percentage of unattached people and the mobility of the residents in each tract are used as indicators of this dimension. The equation of the underclass with the black urban ghetto speaks of the results of extreme segregation. The percentage of blacks in a tract gives us a direct measure of this segregation. The physical setting of a neighborhood has received the attention of ecologists, criminologists, and urban planners. These settings have been analyzed as indicators of anomie and also as opportunities for illegal activities (Skogan, 1990). Given the American ideal of house ownership, rentals are seen as either more transitional and/or more conducive to lack of residential attachment. The presence of vacant housing is viewed as a statement of the undesirability of the area and not only promotes opportunities for deviant behavior, but also attracts undesirables to the area (Newman, 1975; Schuerman & Kobrin, 1986; Yancey, 1972). Finally, poverty is a given in the classification of underclass areas and, for situationalists, a necessary antecedent. The issue of reproduction of such communities is thought to derive not directly from low incomes, but from the extended marginalization caused by weak links with the labor market (Apple, 1989; McGahey, 1986). The ratio of unemployed and out of the labor force to all people 16 years or older is the most direct measure of this alienation. Bivariate Analysis
Table 2 shows the correlational analysis between the 10 indicators selected. With the exception of three correlations (public assistance and female heads of households; public assistance and unemployed and out of the labor force; and low education and unemployment and out of the labor force), all the coefficients have medium to low values. When comparing the distribution of all variables between poor and nonpoor tracts, we find that all vary significantly in the expected direction, except sex ratio.
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Context and Dropout Rates
279
Table 2 Zero Order Correlation of all Underclass Indicators
FHHHCWHHM -.03 Sex Ratio Family & SubF F.H. CH 0- 15fHH Public Asst % w/o HS Vacant Housing Rent Housing Unatt P. Ratio Stability 5Y 8 Black Pop hemp & OOLF
-.40
-.02
.20
.80 .34
Vat HQM~~w2B!&OOLF~ .29 .OO .I4 .40 .52 .I0 .69
.61 -.05 .67 .51
.62 -.25 .57 .37 .61
.21 -.67 .04 .05 .48 .65
Unemp&
Drop-
-.16
-.25
.09
.I0
-.OO .11 .04 .21 -.23 -.39 -.51
.69 .39 .54 .13 .21 .22 -.15 .26
.65 .12 .82 .83 .60 .53 -.OO .13 .32
.20 .13 .32 .53 .38 .20 .07 -.06 -.14 .39
The analysis of variance using a detailed strata of poverty gives us a finer-grained view of the distribution of each variable by poverty level (see Table 3). Percent of families with female heads of household, percent of families with public assistance income, and percent of rental and vacant housing units vary significantly across all groups and in the predicted direction. Percent of the adult population without high school degrees, percent of blacks, and dropout rates show a similar pattern, although the interstrata differences in two or three instances are not significant. Proportion of unattached persons and stability vary only in relation to the poorest tracts, while ratio of children to households differentiates only the better off tracts from all others. In one instance, the only significant difference is in relation to the poorest tracts but in the direction opposite to expectation. Sex ratio is highest in the areas with 40% or more of the population under the poverty level. In sum, with the exception of children per household ratio and sex ratio, the attributes of the underclass are verified in the poorest Detroit neighborhoods. Multivariate Analysis
The previous analysis demonstrates that there is some multicollinearity among a couple of variables and that at least one variable shows very little variation and in the direction opposite to prediction. On these criteria, we
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280
reduced the nine predictors assistance and sex ratio).
of dropout rates to seven (eliminating
public
Table 3 Five Levels of Poverty Underclass Indicators by Analysis of Variance With Interstrata Contrast Analysis Sex Ratio Mean St. D. 98.1 13.0 1 2 91.0 13.0 94.3 33.5 3 4 91.2 28.1 5 105.6 45.0 F 2.85 Sig* .023 Interstratal,2,3,4-5 Sign* (T)
Fam & Sub FH Mean St.D. 22.7 10.4 37.8 10.8 49.8 12.5 61.8 13.5 66.6 12.1 144.1 <.CQO All<.000
CH O-15/HH Mean St.D. .615 .200 .766 .265 .811 .256 .804 .279 .791 .353 6.2 .OOO l-2,3,4,5
Public Asst. Mean St.D. 7.4 3.2 15.1 5.6 24.5 5.9 32.4 5.9 40.2 9.4 286.5 <.OOO All <.OOO
%NoHS Mean St.D. 1 33.1 12.4 2 39.8 11.2 3 51.5 11.7 4 56.4 8.7 5 61.0 9.1 F 72.6 <.OOO Sig Interstrata l-2 c.000 Sign 3-4-5 c.05
Vacant Hous. Mean St.D. 2.4 1.1 5.3 4.1 8.2 2.7 12.6 5.2 15.8 6.8 98.6
Rental Hous. St.D. Mean 19.0 15.1 31.0 17.0 43.2 15.3 51.3 11.7 60.5 13.3 74.1 <.OOO All <.OOO
Unatt P. Mean St.D. .139 .08 .157 .12 .155 .08 .195 .13 ,247 .16 6.8 <.OCQ 1,2,3-4-5
Stability Mean St.D. 1 61.1 10.1 2 58.6 13.9 3 59.4 15.0 4 59.6 9.9 5 54.1 11.9 F 2.4 Sig NS Interstrata 1,2,3,4-5
Blacks Mean St.D. 30.4 31.3 60.4 33.8 63.8 37.2 79.6 24.9 77.3 22.1 26.4 <.OOO l-2,3-4,5
C.000
All c.000
Unemp & OOLF Mean St.D. 44.3 6.2 49.5 7.0 58.8 6.5 64.8 5.7 70.9 6.3 175.7 C.000 All pairs e.000
Dropouts Mean StD. 14.0 10.0 18.3 11.9 23.2 11.5 24.9 14.3 31.0 19.8 13.8 <.OOO l-2-3,4-5
*In this and subsequent tables, significance is used as a criterion of stmnth of association, not for purposes of generalization, since information on the entire census of the city of Detroit is included.
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A stepwise regression for dropout rates included the selected predictors. The total variance explained was 40 percent, with percent of adults with low education accounting for more than half. The other three variables showing significant explanatory contribution were race, number of children per household, and proportion of unrelated persons.
Table 4 Stepwise Regression Analysis Predicting Percentage of Young Adult Dropouts
Low Education among Adults (ED 25-11) Black Population Number of Children per Household (CH O-15HH) Proportion of Unrelated Individuals Multiple R = .632
-.330 .405 .299
Cumulative R2 .282 .325 .353 .400
R Square = .400
Examination of the arguments on which the selection of the predictors of dropout was made led us tentatively to group them in a causal sequence. In spite of the limitations inherent in using cross-sectional data in this way, there is some exploratory merit to this analytical strategy. It proceeds by examining the empirical relationships among variables in the order specified below. These relationships are estimated by regressing each variable on those assumed to be causally prior. Nonsignificant paths are deleted, and the model is re-estimated to produce final path coefficients (see Table 5). The rules followed to order the variable are based on a criteria of immediacy: 1) education and family; 2) environmental characteristics of transiency, segregation, and physical deterioration: and 3) economic marginalization. As expected, the results of the path analysis explained about the same percentage of the variance as the stepwise regression (R2 = .41), and the direct effects show a similar hierarchy of the relevant variables: low education, proportion of children per household, percentage of blacks, and proportion of unrelated individuals. Economic marginalization has no direct impact on dropout because of its remote position in the model and its fairly high correlation with low education and vacant housing. Inspection of the paths shows, in fact, three
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282
sequences of interest: 1) economic marginalization leads to low education leads to high drop out (indirect effect = .42); 2) economic marginalization leads to vacant housing leads to high dropout (indirect effect = .16); and 3) high economic marginalization leads to high segregation leads to low dropout rates (indirect effect = .lO).
Table 5 Path Analysis - Dependent Variable Dropout Rate
(Betas) Dropout F**E&I&on Education Number of Children Unrelated Indv Stability % Black Vacant Hous. Econ. Marg. MR R2
.35** .20** .oo -.32** .16 -.12
Number Unrel Vacant CWHHhxL St&iliQBlacksHousine
-.07* -.90** .21** -.34** -.23** .32** .17** .25** .78** -.02
.09
.07
.31**
.60**
.64 .41 .40
Adj. R2 ** Sig c.000 * Sig c.05
Environment variables also show some important paths: 1) high proportion of unrelated individuals leads to low number of children per household which leads to high dropout rate (indirect effect = .33); 2) high mobility leads to low education which leads to high dropout rate (indirect effect = . 11); and 3) high segregation leads to high education which leads to low dropout rate (indirect effect = .12); and 4) vacant housing, segregation, and mobility leads to high number of children per household which leads to high dropout (indirect effects = .09, .lO, . 11). These paths differentiate the relationship of the variables according to the model adopted. We can conclude that economic marginalization affects education negatively and dropout rates positively and, also, predicts decrepit housing with somewhat high number of children per household, which in turn affects high dropout rates.
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Two findings are unexpected: 1) the marginal impact of mobility measures; and 2) the negative effect of segregation on education and dropout rates. The marginal impact of mobility might be due to limitations of measurement, as well as conceptual inadequacy. The measure used in this study is derived from information of respondents reporting having lived in the same house during the previous five years. While this measure is adequate as a general indicator of residential stability, it cannot measure the incidence of mobility or the range of the move (within or across communities). In addition, the concept of mobility needs to be refined. Although during the time of the early ecological studies its meaning was still intrinsically tied to large demographic movements, there is evidence that in later periods communities developed mechanisms for handling ordered geographical mobility (e.g., 1981; Taub, Taylor, & Dunham; Whyte, 1956). A separation between these two concepts is necessary to clarify the expected relation between mobility and disorganization (Figueira-McDonough, 1991). Findings of the high value given to education by blacks and assessments of the failures of school integration (Corcoran, et. al, 1985; Jewell, 1988; Mahard & Crain, 1983; St. John, 1975; Sullivan, 1989) support indirectly the segregation path identified in our analysis. Furthermore, examining the association between race and dropout rates for all the SMSA tracts, we found a weak but positive association (.20), while the same correlation in the city was negative (-.15). Obviously, the racedropout association for suburban Detroit is in the expected direction but in predominantly black Detroit, race homogeneity is favorable to school retention. Discussion and Conclusion The most popular slogans regarding the economic recovery of the underclass focus on issues of rehabilitation of the family and education reform, avoiding the more direct realities of poverty and unemployment. Granted that the poorest communities are economically marginalized in terms of levels of unemployment, insecure employment, and exclusion from the labor force, the main question addressed here is how other environmental and population characteristics are affected by deprivation and, in turn, affect dropout rates. As expected, the incidence of female heads of households and percent of families receiving public assistance income increased with level of poverty, confirming the phenomenon of the feminization of poverty (e.g., Rodgers, 1986; Schorr & Moen, 1979). Percentage of black population, rate of unemployment, unstable work, and exclusion from the labor force also fitted the attributions of the underclass (e.g., Ellwood, 1988; Wilkerson & Gresham, 1989). Level of education
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and dropout rates varied, also, in the expected direction. No evidence of major differences in the greater number of children per household and transience was found by degree of poverty. Wilson’s hypothesis (1987) of the high level of single motherhood as a function of low sex ratio was not supported in the Detroit data. There was no difference in sex ratio by level of poverty, except in relation to the poorest group. This group, however, showed the highest sex ratio for the ages 16 to 34. Eggers and Massey (1991) found a similar lack of association in their study of urban communities. It is possible that the measure of sex ratio is too limited to reflect Wilson’s marriage pool hypothesis, which conceptually excludes from the pool unemployed young men and those in trouble with the law. The results of the stepwise regression analysis of dropout rates isolated four major predictors: low adult education, segregation, high number of children per household, and high proportion of unrelated individuals. The outcome of the ordered regression was quite similar but permitted the identification of distinctive paths. Tracts with high economic marginalization have a deteriorated physical environment in which the incidence of number of children per household is somewhat higher, which, in turn, predicts high school dropout rate. A still stronger path indicates that high economic marginalization predicts low education among adults that, in turn, predicts a high level of dropout. The most intriguing path, however, involves segregation. While, as expected, economic marginalization is related to segregation, segregation predicts somewhat higher education and lower dropout rates. Although poor urban communities in Detroit have, in general, the characteristics attributed to them by the students of the “underclass,” the clearest differences relate to economic marginalization, feminization of poverty, segregation, and education. Our analysis suggests that decreasing the dropout rate might not only require school reform but also a commitment to adult education with the real incentive of stable work. Also important would be programs designed to increase the supervisory capability of the community through, for example, after school programs. The findings that predominantly black communities have higher levels of education and lower levels of dropouts than other communities with greater racial mixture are especially noteworthy, since those communities tend to lack experiential economic reinforcement for educational goals. This unexpected sequence in Detroit seems to suggest that a system guaranteeing equal public expenditures for all students might be more successful for student retention than forced schemes of school integration (Eitzen & Zinh, 1989, pp. 430-434). Given the cluster of predictors of dropout rates and their concentration in the poorer neighborhoods, proposals of school reform promoting higher
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curricular and discipline demands might increase rather than decrease the dropout rates in those areas (Clayton, 1989; McDill, Matriello & Pallas, 1986). The increase of costs of attending school in a setting devoid of experiential rewards for education is likely to make the experience irrelevant for youths trapped in poor communities. Geschwendler’s (1991) findings on the relation between minority discrimination and work effort, as well as the value given to children’s education, offer some insights about the future of the association between segregation, education, and dropout rates found in our study. Geschwendler argues that groups discriminated against have historically tried to compensate for it by increasing their work effort (as evidenced by a higher involvement of wives in paid labor) and by placing greater value on children’s education. The promise of this adaptation, in the case of the black population, seems, however, to be seriously disrupted at the present time. The number of complete families has been decreasing for the general population and at an accelerating rate in the lower classes (Schorr & Moen, 1979). The urban underclass does not only have a high rate of single parenthood, which is itself related to barriers to access to work (Bane, 1986; Children’s Defense Fund, 1982), but it is also predominantly made up of minorities. The possibility of compensating for discrimination through the generation of two incomes is, therefore, severely curtailed. The belief of advancement through education received a degree of positive reinforcement through the affirmative action efforts of the sixties and most of the seventies. The eighties, however, eroded this promise. Passe1 (1991), reporting on the findings of Bond and Freeman about the diminishing returns of education for blacks, defines unambiguously this state of affairs. Between 1975 and the present time, the white-black male weekly income gap, when controlling for education and experience, increased from 11% to 18%. In the same period, the racial difference in unemployment went from 9% to 15%. The question becomes to what extent this dissociation between education and economic outcomes will have adverse consequences on school retention, especially in the Midwest where the losses have been the most extreme. Indeed, we know that the black dropout rate has increased by 20% for the whole nation and twice as much for Detroit (Detroit Public Schools, 1990). It should be evident that prevailing school reforms cannot remedy this accelerating deviance from the crucial liberal-democratic principle of equal opportunity (Bowles & Gintis, 1972) without accompanying efforts to change the poor communities’ economic and environmental constraints impacting on young people.
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