Ecological approaches to explaining juvenile delinquency emphasize the importance
of spatial influences on patterns of delinquency. Studies of recidivism among juvenile
offenders, on the other hand, have rarely taken neighborhood influences into account.
Moreover, conventional statistical approaches adapted for investigating spatial neighborhood effects, such as hierarchical linear modeling (HLM), are typically subject to assumptions regarding the nature of the spatial relationships under investigation that may, in fact, mask relevant neighborhood influences on individual outcomes. The study discussed in this article applied geographic analysis to the analysis of adjudicated juvenile delinquents assigned to court-ordered programs by the Family Court of Philadelphia, Pennsylvania. We examined the simultaneous effects of neighborhood and individual (including family)
characteristics on juvenile recidivism using local spatial clustering of probabilities of reoffending.
Geographic Information Systems provided the technology to integrate diverse
spatial data sets, quantify spatial relationships, and visualize the results of spatial analysis.
In the context of juvenile recidivism, this approach provided new insights on how and
why recidivism rates vary from place to place. We found not only that recidivism was
concentrated in specific areas of the city, but also that types of recidivism offenses were
spatially concentrated. Importantly, the findings also show that predictors of reoffense
vary from place to place.