Innovative data in communities and crime research: an example at the intersection of racial segregation, neighborhood permeability, and crime

Abstract

ABSTRACT 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