First a place focus must be introduced to JTC research Over 30 years of place

First a place focus must be introduced to jtc

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First, a place focus must be introduced to JTC research. Over 30 years of place-based research provides irrefutable evidence that to understand crime patterns we must take into consideration situational factors endemic to the site. Continuing to ignore the nature of the crime site (the type of place) when exploring the JTC stifles our ability to understand offender travel behavior. Examining the distance that offenders travel to commit crimes at specific types of locations (i.e., regional shopping malls, schools, parks) would support efforts to develop hotspot theory and may even lead to the theoretical integration of the concepts of crime attractors and generators 490 Journal of Research in Crime and Delinquency 48(3) at Northcentral University on September 18, 2016 Downloaded from
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(Brantingham and Brantingham 1995), with the spatio-temporal classifica- tion system for high crime areas developed by Ratcliffe (2004), and the risky facilities arguments of Clarke and Eck (2007; Eck et al. 2007). Second, the convergence settings explored here (schools, movie theaters, and shopping centers) are frequently noted as being places where youth get into trouble (Gottfredson 2001; Weisburd et al., 2009) and may provide an assembly point for potential co-offenders (Felson 2003). Thus, integrating these sites into JTC research may improve efforts to model criminal activity that involves more than one offender. Support for this notion might be drawn from social network research. For instance, recently Malm, Kinney, and Pollard (2008) found that the distribution of distances between co-offender residences peaked at 2.5 miles, suggesting that while co- offenders share the same habitat, they are unlikely to be neighbors. While this research involved an adult criminal network, it would be interesting to compare whether the travel distances of co-offending youth resemble those of adult co-offending groups. This raises the issue of dependent data. If the distance traveled to a crime site is related to general activity patterns linked to social networks, then these data may require alternative analytic techniques (i.e., Brantingham and Brantingham 2008; Groff et al. 2008; Townsley and Sidebottom 2010). Social network statistics are designed to explore dependent data and thus, these tools may be better able to identify the potential that certain Table 4. Individual Variation in Median Distance Traveled by Subgroups Characteristic Median N Mean Rank Kruskal-Wallis w 2 df Sig. Travel method (2,248) 108.7 2 .000 Sweat 2.02 630 895.77 Vehicle 3.20 1,443 1,214.67 Combination 3.25 175 1,204.38 City Class (2,562) 128.4 2 .000 Core 2.80 531 1,215.33 Periphery 2.65 1,678 1,215.33 Isolate 5.00 353 1,685.73 Age (2,198) 17.6 2 .000 10 to 12 2.38 143 1,016.67 13 to 15 2.70 1,263 1,062.35 16 and over 3.08 792 1,173.70 Note: No substantive differences were found among four subgroups: gender, ethnicity, gang affiliation, and offense type. Bichler et al. 491 at Northcentral University on September 18, 2016 Downloaded from
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Table 5.
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