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The goal of Cityscape is to bring high-quality original research on housing and community development issues to scholars, government officials, and practitioners. Cityscape is open to all relevant disciplines, including architecture, consumer research, demography, economics, engineering, ethnography, finance, geography, law, planning, political science, public policy, regional science, sociology, statistics, and urban studies.

Cityscape is published three times a year by the Office of Policy Development and Research (PD&R) of the U.S. Department of Housing and Urban Development.

  • Crime and Urban Form
  • Volume 13 Number 3
  • Managing Editor: Mark D. Shroder
  • Associate Editor: Michelle P. Matuga

The Coaction of Neighborhood and Individual Effects on Juvenile Recidivism

Philip W. Harris , Jeremy Mennis , Zoran Obradovic , Alan J. Izenman , Heidi E. Grunwald, Temple University

As with the articles in this issue, this introduction reflects the views of the authors and does not necessarily reflect the views of the U.S. Department of Housing and Urban Development.


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.

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