The Geography of Crime: Examining the Distribution of Break and Enters Across Regina Neighbourhoods Using Geographic Information Systems (GIS)
type: CreativeWork
description: Crime is not a random event that occurs evenly across time and space; instead, it is clustered in certain areas known as hot spots (Sherman, Gartin, & Buerger, 1989). Understanding patterns of crime and the reasons why hot spots exist provides a foundation for crime control and prevention strategies. This study provides an analysis of the distribution of break and enters in Regina, Saskatchewan using calls for service, both emergency and non-emergency, made to the Regina Police Service (RPS) in 2006. The researcher coded and analyzed the data using ArcMap, a Geographic Information System (GIS). Pairing calls for service data with census data from 2006 enabled the examination of break and enter occurrences using the variables outlined by Shaw and McKay’s (1942) social disorganization theory. This study found that break and enters clustered both spatially and temporally. Furthermore, the strongest predictors of break and enter distribution were found to be ethnic heterogeneity, unemployment, and residential mobility. This study has the potential to shape future social disorganization research as it validates some variables of the theory and identifies which variables are not as useful in explaining where break and enters are likely to occur. Keywords: social disorganization theory, break and enter, crime mapping, hot spots, GIS, location quotients.
abstract: Crime is not a random event that occurs evenly across time and space; instead, it is clustered in certain areas known as hot spots (Sherman, Gartin, & Buerger, 1989). Understanding patterns of crime and the reasons why hot spots exist provides a foundation for crime control and prevention strategies. This study provides an analysis of the distribution of break and enters in Regina, Saskatchewan using calls for service, both emergency and non-emergency, made to the Regina Police Service (RPS) in 2006. The researcher coded and analyzed the data using ArcMap, a Geographic Information System (GIS). Pairing calls for service data with census data from 2006 enabled the examination of break and enter occurrences using the variables outlined by Shaw and McKay’s (1942) social disorganization theory. This study found that break and enters clustered both spatially and temporally. Furthermore, the strongest predictors of break and enter distribution were found to be ethnic heterogeneity, unemployment, and residential mobility. This study has the potential to shape future social disorganization research as it validates some variables of the theory and identifies which variables are not as useful in explaining where break and enters are likely to occur. Keywords: social disorganization theory, break and enter, crime mapping, hot spots, GIS, location quotients.
author: Pieracci, Danielle Maria
language: en
date published: 2015-12
date modified: 2026-07-24T04:03:43Z
provider: University of Regina
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Faculty of Graduate Studies and Research, University of Regina

PropertyValue
property ID: Handle
value: https://hdl.handle.net/10294/6846

PropertyValue
property ID: DOI
value: 10.82465/4667