The ‘Exposed’ Population, Violent Crime in Public Space and the Night-time Economy in Manchester, UK

被引:0
作者
Muhammad Salman Haleem
Won Do Lee
Mark Ellison
Jon Bannister
机构
[1] Manchester Metropolitan University,Crime and Well
[2] University of Oxford,being Big Data Centre
来源
European Journal on Criminal Policy and Research | 2021年 / 27卷
关键词
Exposed population-at-risk; Mobile phone data; Violent crime; Public space; Night-time economy; Routine activity theory;
D O I
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中图分类号
学科分类号
摘要
The daily rhythms of the city, the ebb and flow of people undertaking routines activities, inform the spatial and temporal patterning of crime. Being able to capture citizen mobility and delineate a crime-specific population denominator is a vital prerequisite of the endeavour to both explain and address crime. This paper introduces the concept of an exposed population-at-risk, defined as the mix of residents and non-residents who may play an active role as an offender, victim or guardian in a specific crime type, present in a spatial unit at a given time. This definition is deployed to determine the exposed population-at-risk for violent crime, associated with the night-time economy, in public spaces. Through integrating census data with mobile phone data and utilising fine-grained temporal and spatial violent crime data, the paper demonstrates the value of deploying an exposed (over an ambient) population-at-risk denominator to determine violent crime in public space hotspots on Saturday nights in Greater Manchester (UK). In doing so, the paper illuminates that as violent crime in public space rises, over the course of a Saturday evening, the exposed population-at-risk falls, implying a shifting propensity of the exposed population-at-risk to perform active roles as offenders, victims and/or guardians. The paper concludes with a discussion of the theoretical and policy relevance of these findings.
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页码:335 / 352
页数:17
相关论文
共 104 条
[1]  
Andresen M a(2011)The ambient population and crime analysis The Professional Geographer 63 193-212
[2]  
Bellis MA(2010)Cross-sectional measures and modelled estimates of blood alcohol levels in UK nightlife and their relationships with drinking behaviours and observed signs of inebriation Substance Abuse Treatment, Prevention, and Policy 5 5-87
[3]  
Hughes K(1965)Urban Crime Patterns American Sociological Review 30 899-480
[4]  
Quigg Z(2018)Routine activity, population(s) and crime: spatial heterogeneity and conflicting propositions about the neighborhood crime-population link Applied Geography 95 79-414
[5]  
Morleo M(2018)Crimes by visitors versus crimes by residents: the influence of visitor inflows Journal of Quantitative Criminology 34 465-75
[6]  
Jarman I(2014)Risky facilities: crime radiators or crime absorbers? A comparison of internal and external levels of theft Journal of Quantitative Criminology 30 389-173
[7]  
Lisboa P(2007)Visualising space and time in crime patterns: a comparison of methods Computers, Environment and Urban Systems 31 52-205
[8]  
Boggs SL(2010)Contemporary public space, part two: classification Journal of Urban Design 15 157-220
[9]  
Boivin R(1979)Social change and crime rate trends: a routine activity approach American Sociological Review 44 588-601
[10]  
Boivin R(2015)A spatio-temporal analysis of on-premises alcohol outlets and violent crime events in Buffalo, NY Applied Geography 58 198-206