The Impact of Neighborhoods, Schools, and Malls on the Spatial Distribution of Property Damage

Abstract

Using data obtained from three different sources, principles derived from routine activities theory are used to predict the distribution of minor property crimes in a medium-sized Canadian city during a 1-year period. Mischief and vandalism incidents recorded by the local police, transit department, and department of parks and recreation are aggregated by census enumeration area using mapping software, and analyzed in relation to three sets of predictors: (1) neighborhood demographic characteristics; (2) the proximity of shopping malls; and (3) the proximity of public and Catholic senior and junior high schools. Similar patterns observed for the three types of damage are examined in relation to the convergence of potential offenders, reduced guardianship, and increased opportunity as derived from routine activities theory.

Land Use Influencing the Spatial Distribution of Urban Crime: A Case Study of Szczecin, Poland

“…In numerous studies in the US, it has been confirmed that public housing and its immediate neighborhoods are characterized by an increased crime [4,8,11,18,21]. However, Greenberg et al [20] emphasize, based on the analysis of eight types of serious crimes committed in housing estates, that different forms of management influence the level of local crime stronger than social variables, such as the sense of bond with the territory of an estate or the level of social control.…”

“…In the US and Canada, an influence of schools and other places of gathering of the youth on the concentration of crime has been examined [12,17,21]. The influence of the land use type dormitories and school buildings on the distribution of crimes in Szczecin shows an attracting nature.…”

“…They used simple statistical analysis and observed that differences in physical characteristics distinguished between low and high crime neighborhoods to a far greater extent than did differences in informal territorial control. LaGrange [21] in his analysis in Edmonton, Canada in 1992 examined demographic characteristics of neighborhoods, shopping malls, and public and Catholic high schools and their influence on three crime types (mischief, transit vandalism, and park vandalism). In his study, he used multiple regression analysis and determined that areas containing high schools or malls and those with higher unemployment concentrate property crime.…”

The dynamics of robbery and violence hot spots

“…Environmental criminologists using Pareto's 80/20 rule have pointed out that not all parks are full of drug users/dealers (Wilcox et al 2004;Eck et al 2007;Groff and McCord 2012), not all high schools have high rates of delinquency (Wikstrom et al 2012;Glover 2002;LaGrange 1999), not all bars contain high rates of assault (Ratcliffe 2012;Newton and Hirschfield 2009;Eck et al 2007;Gorman et al 2001), and not all parking lots have high rates of auto theft (Rengert 1997;Clarke and Goldstein 2003). In fact, even 'high crime' neighborhoods contain hot spots (high density crime areas) and cold spots (zero/low crime areas), high crime streets and zero/low crime streets, and both 'good' (i.e.…”

Land Use and Violent Crime*

“…Thus, land use is completely absent from anomie/strain research and most tests of social disorganization/collective efficacy theories (but see Sampson and Groves 1989). 2 Research also frequently focuses on a few specific land uses such as taverns (Roncek and Maier, 1991;Roncek and Pravatanier, 1989) or schools (LaGrange, 1999;Roncek and Faggiani, 1985;Roncek and LoBosco, 1983), or combines land use information into indices (McCord, Ratcliffe, Garcia, and Taylor 2007;Wilcox et al, 2004), or single measures of "mixed" or nonresidential land use. For example, Sampson and Raudenbush (1999) include a measure of "mixed land use" but find no effects of the measure on crime, whereas Cahill (2005) finds significant effects of mixed land uses on crime.…”