In their seminal "Broken Windows" article in Atlantic Monthly, J. Q. Wilson and G. L. Kelling (1982) suggested that police could more effectively fight crime by targeting minor offenses. They hypothesized that untended disorder increases fear of crime in a community, starting a chain of events that eventually leads to heightened levels of crime. By targeting disorder, police can thus circumvent this cycle of neighborhood decline (Skogan, 1990). This study aimed to improve knowledge of the relationship between disorder and fear of crime in the context of the broken windows hypothesis by using a micro-place level research design involving a police crackdown on disorder and minor crime at hot spots. The results of the current study suggest that perceived social disorder and observed levels of physical disorder have a strong impact on fear of crime. This confirms the relationship between disorder and fear hypothesized by the broken windows literature, and implies that police may be able to reduce fear of crime by reducing disorder. It was also found, however, that the police intervention itself significantly increased the probability of feeling unsafe. Accordingly, any fear reduction benefits gained by reducing disorder may be offset by the fact that the policing strategies employed simultaneously increase fear of crime. These findings suggest the importance of a careful focus on "how" broken windows policing programs are implemented. Such programs must be geared not only to reduce disorder, but also to prevent increases in citizen fear that accompany crackdowns and other intensive enforcement efforts associated with broken windows policing.
Bibliographical noteFunding Information:
This research was supported in part by a grant from the National Institute of Justice (NIJ Grant #: 98-IJ-CX-0070). The authors would like to thank the anonymous reviewers and Laura Dugan, Gary LaFree, Stephen Mastrofski, Jean McGloin, and Lorraine Mazerolle for their helpful comments on early versions of this manuscript. The authors would also like to thank Laura Wyckoff and Sue-Ming Yang for their help with data preparation and analysis, as well as providing many thoughtful comments on study design and early drafts of this article.