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入室盗窃临近重复案件与孤立案件分布的影响因素对比研究
引用本文:柳林,陈德宝,徐冲,龙冬平,肖露子,陈悉.入室盗窃临近重复案件与孤立案件分布的影响因素对比研究[J].地理科学,2021,41(9):1625-1633.
作者姓名:柳林  陈德宝  徐冲  龙冬平  肖露子  陈悉
作者单位:1.广州大学地理科学与遥感学院/广州大学公共安全地理信息分析中心,广东 广州 510006
2.辛辛那提大学地理系,美国俄亥俄州 辛辛那提市 45221-0131
基金项目:广东省自然科学基金研究团队项目(2014A030312010);国家自然科学基金项目(41601138);国家自然科学基金项目(41901172);国家自然科学基金项目(41531178);广州大学研究生“基础创新”项目(2019GDJC-M03)
摘    要:以中国南方某特大城市YP区为例,结合犯罪地理学主要理论选取相关变量构建二元逻辑回归模型,探讨区域环境对入室盗窃临近重复案件和孤立案件分布的影响差异。研究发现:居民数量、银行&ATM机和公园集聚的区域发生临近重复案件的概率比孤立案件更高,而道路密度高的社区难以发生临近重复案件;青少年人口比重高和低租金住户多的社区会加剧弱势群体、问题人群的集中趋势,临近重复犯罪发生的可能性也会随之上升,其中青少年人口的影响程度高于低租金住户。研究结果可对微观社区层面入室盗窃临近重复犯罪的治安防控与警务政策制定提供一定的参考。

关 键 词:入室盗窃  临近重复  孤立案件  社会解组理论  日常活动理论  
收稿时间:2020-07-22
修稿时间:2020-09-14

Comparative Study on the Influencing Factors of the Distribution of Near Repeat Cases and Isolate Cases of Burglary
Liu Lin,Chen Debao,Xu Chong,Long Dongping,Xiao Luzi,Chen Xi.Comparative Study on the Influencing Factors of the Distribution of Near Repeat Cases and Isolate Cases of Burglary[J].Scientia Geographica Sinica,2021,41(9):1625-1633.
Authors:Liu Lin  Chen Debao  Xu Chong  Long Dongping  Xiao Luzi  Chen Xi
Institution:1. Center of GeoInformatics for Public Security, School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, Guangdong, China
2. Department of Geography, University of Cincinnati, Cincinnati OH45221-0131, USA
Abstract:Previous studies have shown a significant association between burglary and micro-environment, and burglary usually has a spatiotemporal phenomenon of near repeat occurrence. However, there is no literature on the comparative analysis of spatial influencing factors of the distribution of near repeat cases and non-near repeat cases in China. Combing with social disorganization theory, routine activities theory and crime patterns theory, this study taking YP District of a large city in the southern China as an example, and divides the burglary cases into two types by importing into near repeat caculator, namely, near repeat cases and non-near repeat cases (isolate cases). Using the data of burglary alarm, the sixth census data, and point of interest (POI), a binary logistic regression model was constructed to explore the influence of the micro characteristics of regional environment on the distribution of near repeat and non near repeat cases of burglary. The results show that the higher the spatial-temporal interaction strength between the criminal target and potential criminals, the more significant the pattern of near repeat. More specifically, the probability of near repeat cases in areas with more residents, banks & ATMs and parks is higher than that of isolate cases, while the communities with higher road density are difficult to have near repeat cases. We also find that the communities with higher proportion of youth population and more low-rent households will aggravate the concentration trend of vulnerable people and problem people, and the possibility of near repeat crimes will increase. The impact of the proportion of youth population is higher than that of low rent households. These findings can provide certain reference for the public security prevention & control and police policy making of burglary near repeat crime at the micro community level.
Keywords:burglary  near repeat  isolate cases  social disorganization theory  routine activities theory  
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