Interpersonal conflict is the strongest predictor of community crime and misconduct

Special Issue: Reimagining Broken Windows: From Theory to Policy

Guest editors: Brandon C. Welsh, Anthony A. Braga and Gerben J. N. Bruinsma

From Journal of Research in Crime and Delinquency

Neighborhoods with more interpersonal conflict, such as domestic violence and landlord/tenet disputes, see more serious crime according to this study. Private conflict was a better predictor of neighborhood deterioration than public disorder, such as vandalism, suggesting the important role that individuals play in community safety.

“Private conflicts, for example, domestic violence or friendship disputes over money or girlfriends, can and do spill over into public spaces, be it on stoops or street corners, in bars or local parks.” reported study authors Daniel O’Brien and Robert J. Sampson of Northeastern University and Harvard University.


Objectives: “Broken windows” theory is an influential model of neighborhood change, but there is disagreement over whether public disorder leads to more serious crime. This article distinguishes between public and private disorder, arguing that large-scale administrative data provide new opportunities to examine broken windows theory and alternative models of neighborhood change.

Method: We apply an ecometric methodology to two databases from Boston: 1,000,000+ 911 dispatches and indicators of physical disorder from 200,000+ requests for nonemergency services. Both distinguish between disorder in public and private spaces. A cross-lag longitudinal analysis was conducted using two full years of data (2011–2012).

Results: The two databases provided six dimensions of physical and social disorder and crime. The cross-lag model revealed eight pathways by which one form of disorder or crime in 2011 predicted a significant increase in another in 2012. Although traditional interpretations of broken windows emphasize the role of publicdisorder, private conflict most strongly predicted future crime.

Conclusions: Our results describe a social escalation model where future disorder and crime emerge not from public cues but from private disorder within the community, demonstrating how “big data” from administrative records, when properly measured and interpreted, represent a growing resource for studying neighborhood change.


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Article details
Daniel Tumminelli O’Brien and Robert J. Sampson
Public and Private Spheres of Neighborhood Disorder: Assessing Pathways to Violence Using Large-scale Digital Records Journal of Research in Crime and Delinquency July 2015 52: 486-510, first published on June 2, 2015 doi:10.1177/0022427815577835







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