Predicting Arrest Trajectories in Micro-Places: A Test of Social Disorganization Theory



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Although much has been learned about crime in micro-places, their development and continuity over time remains largely misunderstood. In 2006, Weisburd, Bushway, Lum and Yang were the first to develop trajectories of crime at micro-places, but their study was largely atheoretical. In 2012, Weisburd, Groff, and Yang explored theoretical predictors of crime in micro-places, but they did not formally test any one theory. This study builds on both prior efforts by testing whether social disorganization theory predicts Census block-level arrest trajectories in Dallas, Texas, between 2010 and 2014. Results suggest that social disorganization can help explain arrest trajectory group membership, but not completely. While socioeconomic factors, residential stability, and family disruption were significantly associated with trajectory group membership, racial heterogeneity was only significant when it was interacted with other variables. Also, urbanization exerted no discernible effect on arrest trajectory group membership. Finally, social disorganization variables helped predict certain arrest trajectories, but not all of them. Policy implications and research limitations are also discussed.



Crime at place, Trajectory analysis, Multinomial logistic regression, Geospatial analysis, Social disorganization, Logistic regression analysis, Crime forecasting, Geospatial data, Social ecology


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