Bars on blocks: A cellular automata model of crime and liquor licensed establishment density

被引:13
|
作者
Spicer, Valerie [1 ]
Reid, Andrew A. [1 ]
Ginther, Jordan [1 ]
Seifi, Hasti [2 ]
Dabbaghian, Vahid [2 ]
机构
[1] Simon Fraser Univ, ICURS, Sch Criminol, Burnaby, BC V5A 1S6, Canada
[2] Simon Fraser Univ, MoCSSy Program, IRMACS Ctr, Burnaby, BC V5A 1S6, Canada
关键词
Cellular automata von Neumann (Rook) and Moore (Queen); neighborhood; Liquor establishments; Entertainment districts; Distribution of crime; Urban planning; ALCOHOL-RELATED CRIME;
D O I
10.1016/j.compenvurbsys.2012.02.004
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Criminologists have extensively researched the problems generated by licensed establishments. Violent offending and disorderly behavior resulting from pubs, taverns, dance clubs and bars are of particular interest to this field of study. The relative density of these liquor establishments has been found to be associated with the level of violence and disorder in surrounding areas. A complex systems approach can be used to further understand the dynamic interplay between licensed establishments, violent offending and disorder, and urban planning decisions. The model presented here utilizes cellular automata as the mathematical framework to view the varying impact of liquor licensing density on crime. This study uses a sample of liquor establishments and crime data from the City of Vancouver in British Columbia. The cellular automata model incorporates transition rules which govern the change of city blocks from low-risk blocks to high-risk blocks. The results represented by a 50 x 50 cellular grid show that high-risk blocks multiply when liquor licenses are grouped. Two scenarios are presented to contrast the impact of grouping high-risk blocks which contain more liquor establishments and dispersing such blocks. A third scenario demonstrates how increasing the positive influence in a grouped scenario stops high-risk blocks from taking over the entire grid. Future iterations of this model will incorporate census data, public transportation data, land use data and entertainment districts from other cities to further analyze the effect of licensed establishments on the distribution of crime. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:412 / 422
页数:11
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