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Research on crime "hot spots" tends to use official data to identify hot spots, such as 911 calls or calls for service. While the use of call data is less biased than many official measures of crime (e.g. arrest data), call data still miss some portion of actual crimes committed. To an extent, "the dark figure of crime" is an unavoidable limitation of any criminological inquiry. However, in this study we put forth an alternative method of identifying crime hot spots that we argue is a useful tool for understanding the spatial distribution of crimes. In addition, we show how this method can be useful for understanding the dynamics of crime at places. Specifically, we examine discrepancies between perceptual (self-reported) hot spots and official hot spots gleaned from calls for service. Our methodological approach – spatial video and geonarratives – enables us to map hot spots identified by police officers, ex-offenders, and local residents during “ride-alongs” through a high crime neighborhood. Our results suggest that using call data risks missing key hot spots. We focus on one hot spot in particular, the “corner store." The corner store elicited a high number of crime mentions across participants, but does not emerge as a hot spot when using call data. We then drill down into this location to understand this discrepancy. Specifically, we draw on visual and narrative data from participants to better understand the social and physical context of this locale.
Lauren Porter, University of Maryland
Eric Jefferis, Kent State University
Andrew Curtis, Kent State University
Susanne Mitchell, Kent State University