The spatial elements of crime occurrence and the identification of crime generators/attractors have remained a prominent area of research. We focus on the utility of the 80-20 rule and the labeling of risky facilities in crime forecasting models with risk terrain modeling (RTM). We first examine whether the rule holds across types of crime generating places including liquor stores, department stores, hotels/motels, restaurants/bars, and apartment complexes. Next, we use our findings to test whether conducting preliminary analyses to identify risky facilities increases the predictive power of RTM versus using all possible facilities. When restricting the RTM approach to only risky facilities, results were more accurate than a traditional RTM approach. Findings and implications are nested in the utilization of the wider body of environmental criminology research to increase our understanding of where crime is likely to occur.
Amidst the proliferation of community-and place-based, several innovative measurement tools have become more readily available for criminological and criminal justice researchers. The current study illustrates the utility of two novel data sources -Google transportation data and municipal infrastructure files -as a means of extending studies focused on racial and ethnic segregation's effect on crime to include critical insights from environmental criminology regarding neighborhood boundary permeability. In doing so, we utilize data from over 120 block groups in Little Rock, Arkansas that include measures of Black isolation and boundary permeability: walk times to adjacent neighborhoods and thru streets captured in city infrastructure files.Our findings reveal that both segregation and neighborhood boundary permeability affect crime independently and net of key structural and spatial covariates, but that boundary permeability conditions the effect of segregation on crime. We conclude by discussing how the integration of newer and under-utilized measurement tools advances long-standing research on segregation and crime by operationalizing key theoretical concepts that have remained difficult to include using more standard secondary databases
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