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Analyzing the Influence of Ethnic Composition and Immigrant Residents on the Spatial Distribution of Violent Crime

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Advances in Spatial Data Handling and Analysis

Part of the book series: Advances in Geographic Information Science ((AGIS))

Abstract

The spatial distribution of violent crime is influenced by small-area characteristics. The social disorganization theory proposes that neighbourhood-scale characteristics, including ethnic composition and immigrant residents, indirectly influence crime through social control. Recent spatial demographic changes in urban areas, including increased immigration and ethnic heterogeneity in city peripheries, have motivated reconsiderations of social disorganization. Using exploratory spatial data analysis and spatial regression methods, this research identifies violent crime hotspots and analyzes the influence of ethnic composition and immigrant resident concentration on violent crime in Toronto, Ontario, at the census tract scale. Results suggest that violent crime hotspots are located in downtown and north Toronto and that ethnic heterogeneity is positively associated with violent crime rate while immigrant resident concentration is negatively associated. This research provides novel insight into the spatial dimensions of crime and the effects of spatial demographic changes on violent crime and social disorganization in contemporary cities.

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Authors and Affiliations

  1. University of Waterloo, Waterloo, Ontario, Canada

    Matthew Quick & Jane Law

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  1. Matthew Quick
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  2. Jane Law
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Correspondence to Matthew Quick .

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Editors and Affiliations

  1. Department of Geography, Environment and Society, University of Minnesota, Minneapolis, Minnesota, USA

    Francis Harvey

  2. Dept. of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong SAR, China

    Yee Leung

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Quick, M., Law, J. (2015). Analyzing the Influence of Ethnic Composition and Immigrant Residents on the Spatial Distribution of Violent Crime. In: Harvey, F., Leung, Y. (eds) Advances in Spatial Data Handling and Analysis. Advances in Geographic Information Science. Springer, Cham. https://doi.org/10.1007/978-3-319-19950-4_14

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