Risky Business: Examining the 80-20 Rule in Relation to a RTM Framework

Abstract

The spatial elements of crime occurrence and the identification of crime generators/attractors have remained a prominent area of research. We focus on the utility of the 80-20 rule and the labeling of risky facilities in crime forecasting models with risk terrain modeling (RTM). We first examine whether the rule holds across types of crime generating places including liquor stores, department stores, hotels/motels, restaurants/bars, and apartment complexes. Next, we use our findings to test whether conducting preliminary analyses to identify risky facilities increases the predictive power of RTM versus using all possible facilities. When restricting the RTM approach to only risky facilities, results were more accurate than a traditional RTM approach. Findings and implications are nested in the utilization of the wider body of environmental criminology research to increase our understanding of where crime is likely to occur.

When Crime Moves Where Does It Go? Analyzing the Spatial Correlates of Robbery Incidents Displaced by a Place-based Policing Intervention

“…However, the lack of nuance among categories of crime generators and attractors is a regular limitation of many studies that employ crime pattern theory constructs, making this area potentially fruitful for further research into the concentration of crime at places. While the “Iron Law of Troublesome Places” as proposed by Wilcox and Eck (2011) suggests that only a few risky facilities with chronic crime problems are driving the relationships observed, it was infeasible to discern differences within facility types as in Steinman et al (2020). Specifically, due to the small study area and the correspondingly low numbers of facilities, we did not have sufficient variance across features to identify those 20 percent of facilities that are “risky.”…”

Disorder or Disadvantage: Investigating the Tension Between Neighborhood Social Structure and the Physical Environment on Local Violence

“…Specifically, RTM systematically identifies environmental risk factors associated with a type of crime in a particular area and assesses how the spatial influences of these risk factors collocate to increase an area’s vulnerability of experiencing future incidents of crime. RTM has been used to examine variation in aggravated assaults (Kennedy et al, 2016; Steinman et al, 2020; Thomas & Drawve, 2018), carjackings (Lersch, 2017), robberies (Caplan et al, 2017; Garnier et al, 2018; Kocher & Leitner, 2015), felonious battery to police officers (Caplan et al, 2014), gun-related crimes (Caplan et al, 2011; Drawve et al, 2014), and overall violent crime (Caplan et al, 2013; Drawve, 2016; Gerell, 2018). Most relevant to the current study was prior applications of RTM that examined the relationship of environmental risk factors with lethal violence (Connealy, 2019; Drawve, 2016; Gerell, 2018; Giménez-Santana et al, 2018; Kennedy et al, 2016; Thomas & Drawve, 2018; Valasik et al, 2019).…”