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Routine activity theory suggests that neighborhood-level activity patterns influence crime rates, and that the convergence of three elements in space and time a motivated offender, a suitable target, and the absence of a capable guardian result in increased likelihood of criminal events. As such, particular land-use patterns may explain why disadvantaged neighborhoods have higher crime rates than more advantaged areas. This monograph examines whether the effect of neighborhood disadvantage on crime may be a function of its association with land-use patterns. This research also examines whether…mehr

Produktbeschreibung
Routine activity theory suggests that
neighborhood-level activity patterns influence crime
rates, and that the convergence of three elements in
space and time a motivated offender, a suitable
target, and the absence of a capable guardian result
in increased likelihood of criminal events. As such,
particular land-use patterns may explain why
disadvantaged neighborhoods have higher crime rates
than more advantaged areas. This monograph examines
whether the effect of neighborhood disadvantage on
crime may be a function of its association with
land-use patterns. This research also examines
whether land-uses have greater effects in
disadvantaged neighborhoods. By understanding the
effects of land-use, planners and managers could make
changes in land-use patterns that decrease crime
rates. Findings reveal that both social
characteristics and several land-use patterns
exhibited different degrees of influence within three
research sites. Generally, the percent of land-use
dedicated to commerce as well as some commercial
institutions were significant predictors of robbery
rates. However, types of commercial land and
establishments varied by the study site.
Autorenporträt
Karen Hayslett-McCall is an Assistant Professor of Criminology
and Geography/GIS at the University of Texas at Dallas. Her
interests include neighborhood effects on a variety of
social issues, the refinement of contextual definitions, and the
integration of statistics with GIS. She earned her Ph.D. from The
Pennsylvania State University.