Control for Concentrated Disadvantage

In Chapter 9, we explained that contemporary authors have studied “concentrated disadvantage” rather than gross measures of poverty. The “concentrated disadvantage” construct was included in the poverty chapter as a natural progression of that literature, but it might easily have been included in this chapter on communities. An important empirical question is whether indicators of social disorganization or neighborhood ties are useful for predicting violent crime, when it is clear that disorganized communities are frequently the most disdvantaged.

Almost all of the studies that controlled for poverty, concentrated disadvantage, or some indicator of resource deprivation, reported robust, statistically significant associations between violent crime and other community-level measures. These included measures of social disorganization (owner-owned property, occupied units, percent divorced, average length of residence) (Hipp, 2007); residential instability (vacancies, population change etc.) (Cancino et al., 2007); and disorder (residential mobility, divorce rate, and urbanism) (Hannon & DeFronzo, 1998). This suggests that instability has a robust effect on violent crime, but these papers also report that the association between community factors were also robustly associated with levels of nonviolent crime (two other studies do not lend further support; Sampson & Raudenbush, 1999; Steffensmeier & Haynie, 2000).

Standardized coefficients are reported in one study. A side-by-side comparison of the findings for robbery and burglary rates (both logged), suggests that the effect of disorder is larger for robbery than for burglary (B = .31 compared to .07, and the effect for burglary is not statistically significant), and the effect of collective efficacy also appears to be stronger for robbery than burglary (B = -.35 vs. -.27, both are statistically significant). However, the pattern of effect sizes for other community factors (residential stability, immigrant concentration, population density) is not consistent with the differential etiology hypothesis. Because disorder had earlier emerged as a differential predictor, this finding helps build on evidence that disorder may be a differential predictor of violence. The limited effects of disorder and collective efficacy on violent versus nonviolent offending is not enough to draw any conclusion from this study.

Thus, the quantitative evidence so far suggests that measures of community disorder may be differentially associated with violence, and that, among other community-level indicators, indicators of social networks, such as collective efficacy, have not been eliminated as a good prospect.

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