社会空间视角下广州居住地犯罪风险的格局与模式

doi:10.11821/dlyj201712016

摘要/Abstract

摘要：

基于社会解组理论,以广州118个街道为基本评价单元,在外来人口、性别与年龄、收入、失业、教育、婚姻、职业、住房等8类社会因子中选取相应指标,构建侵财犯罪风险和暴力犯罪风险的综合评价体系;利用信息熵方法评价各街道的犯罪风险得分;通过GDI指数测度各圈层地域内部犯罪风险的异质性;以此为基础,基于空间自相关方法探索其犯罪风险热点区,总结其空间模式。结果表明：① 广州居住地犯罪风险的空间分异显著,旧城犯罪风险最高,核心区犯罪风险最低。两种类型的犯罪风险格局各异,且圈层内部的异质性各有不同。② 广州居住地犯罪风险具有显著的空间相关性和集聚特征,犯罪风险热点区位于旧城区。③ 广州居住地侵财犯罪风险由中心到外围呈“U”型分布规律,暴力犯罪风险由中心到外围呈现高低交错的“波浪式”分布规律,两种类型的犯罪风险都具有“圈层+扇形”的空间分异模式。

关键词: 犯罪风险, 居住地犯罪, 社会空间, 社会因子, 广州

Abstract:

The spatial distribution of inner-city crime rates and crime risks is a topic of great concern in the fields of criminal geography and urban geography. Many empirical studies have shown that inner city criminal behaviors exhibit distinct spatial differentiation characteristics. This is of great importance to pattern analysis of real crime, especially has greater practical significance for its role in predicting patterns of urban crime risk. Because of restrictions related to the difficulty of acquiring real crime data and issues of confidentiality, there are currently few academic summaries of crime risk patterns and model results for Chinese inner-city residents.

Using social disorganization theory, the criminal risks of 118 neighborhoods were evaluated by the characteristics of social space in Guangzhou. The comprehensive evaluation system of property criminal risks and violent criminal risks are composed of social factors, including a floating population, sex and age, income, unemployment, education, matrimony, occupation, and housing. The scores of criminal risks in terms of neighborhoods were then examined based on information entropy. The heterogeneities of criminal risks in four layers of a circle were subsequently captured by GDI. On this basis, hot spots of criminal risks were explored by methods of spatial autocorrelation (GMI, LMI). Finally, the model and dynamics of spatial patterns were summarized according to the results obtained.

The results show that: (1) there exists obvious spatial differentiation for criminal risks in Guangzhou. The criminal risk in the old city is the highest, and that in the core area is the lowest. The differentiation of property risks and violent criminal risks in the inner circles are different, and (2) the spatial correlation and agglomeration of criminal risks are obvious in this city. Hot spots of criminal risks are located in the old city and the western fan-shaped area. (3) The curve corresponding to property criminal risk shows a "U" shape from the city center to the periphery. Moreover, the curve of violent criminal risk is a "wave" shape. Their spacial models show the "circle layer + fan shape".

Key words: crime risk, residential crime, social space, social factor, Guangzhou

王洋, 金利霞, 张虹鸥, 吴康敏, 王长建, 黄耿志. 社会空间视角下广州居住地犯罪风险的格局与模式[J]. 地理研究, 2017, 36(12): 2465-2478.

Yang WANG, Lixia JIN, Hong'ou ZHANG, Kangmin WU, Changjian WANG, Gengzhi HUANG. Pattern and model of residential criminal risk based on social space in Guangzhou, China[J]. GEOGRAPHICAL RESEARCH, 2017, 36(12): 2465-2478.

图/表 9

图1

图2

表1

表2

图3

表3

图4

图5

图6

参考文献 53

[1]	Lockwood D.Mapping crime in Savannah social disadvantage, land use, and violent crimes reported to the police. Social Science Computer Review, 2007, 25(2): 194-209. doi: 10.1177/0894439307298935
[2]	Jiang S, Land K C, Wang J.Social ties, collective efficacy and perceived neighborhood property crime in Guangzhou, China. Asian Journal of Criminology, 2013, 8(3): 207-223. doi: 10.1007/s11417-013-9167-1
[3]	赵婷婷, 陈鹏, 马伟. 基于GIS的北京市治安案件空间特征分析. 测绘与空间地理信息, 2014, 37(8): 19-22. doi: 10.3969/j.issn.1672-5867.2014.08.006
	[Zhao Tingting, Chen Peng, Ma Wei.Spatial analysis to the crimes in Beijing based on GIS techniques. Geomatics & Spatial Information Technology, 2014, 37(8): 19-22.] doi: 10.3969/j.issn.1672-5867.2014.08.006
[4]	毛媛媛, 丁家骏. 抢劫与抢夺犯罪行为时空分布特征研究: 以上海市浦东新区为例. 人文地理, 2014, 29(1): 49-54.
	[Mao Yuanyuan, Ding Jiajun.Study on spatial-temporal patterns of robbery and snatch: A case study of Pudong New Area, Shanghai. Human Geography, 2014, 29(1): 49-54.]
[5]	徐冲, 柳林, 周素红, 等. DP半岛街头抢劫犯罪案件热点时空模式. 地理学报, 2013, 68(12): 1714-1723. doi: 10.11821/dlxb201312011
	[Xu Chong, Liu Lin, Zhou Suhong, et al.The spatio-temporal patterns of street robbery in DP peninsula. Acta Geographica Sinica, 2013, 68(12): 1714-1723.] doi: 10.11821/dlxb201312011
[6]	李业锦, 朱红. 北京社会治安公共安全空间结构及其影响机制: 以城市110警情为例. 地理研究, 2013, 32(5): 870-880. doi: 10.11821/yj2013050010
	[Li Yejin, Zhu Hong.Spatial distribution and influencing mechanism of social and public security: An urban security spatial analysis based on from city crime alarm data. Geographical Research, 2013, 32(5): 870-880.] doi: 10.11821/yj2013050010
[7]	冯健, 黄琳珊, 董颖, 等. 城市犯罪时空特征与机制: 以北京城八区财产类犯罪为例. 地理学报, 2012, 67(12): 1645-1656. doi: 10.11821/xb201212006
	[Feng Jian, Huang Linshan, Dong Ying, et al.Research on the spatial-temporal characteristics and mechanism of urban crime: A case study of property crime in Beijing. Acta Geographica Sinica, 2012, 67(12): 1645-1656.] doi: 10.11821/xb201212006
[8]	刘大千, 修春亮, 宋伟. 基于因子分析的长春市犯罪分区研究. 人文地理, 2015, 30(5): 38-42, 64.
	[Liu Daqian, Xiu Chunliang, Song Wei.Research on classification of crimes in Changchun using factor analysis. Human Geography, 2015, 30(5): 38-42, 64.]
[9]	单勇, 阮重骏. 犯罪制图:城市犯罪风险分析的新技术与新挑战. 山东警察学院学报, 2014, 138(6): 100-107.
	[Shan Yong, Ruan Chongjun.Crime mapping: New technology and challenge in risk analysis of urban crime. Journal of Shangdong Police College, 2014, 138(6): 100-107.]
[10]	耿莎莎, 张旺锋, 刘勇, 等. 基于GIS的城市犯罪行为空间分布特征及预警分析. 地理科学进展, 2011, 30(10): 1240-1246. doi: 10.11820/dlkxjz.2011.10.006
	[Geng Shasha, Zhang Wangfeng, Liu Yong, et al.GIS- based spatial pattern of the crimes in cities and the early warning mechanism. Progress in Geography, 2011, 30(10): 1240-1246.] doi: 10.11820/dlkxjz.2011.10.006
[11]	王发曾. 城市犯罪空间盲区的综合治理研究. 地理研究, 2010, 29(1): 57-67.
	[Wang Fazeng, Study on the comprehensive treatment of spatial blind areas in urban crime. Geographical Research, 2010, 29(1): 57-67.]
[12]	Cahill M, Mulligan G.Using geographically weighted regression to explore local crime patterns. Social Science Computer Review. 2007, 25(2): 174-193. doi: 10.1177/0894439307298925
[13]	严小兵. 上海市就业市场状况与城市犯罪的空间计量分析. 人文地理, 2013, 28(3): 85-90.
	[Yan Xiaobin.A spatial econometric analysis on local labor market and crime in Shanghai. Human Geography, 2013, 28(3): 85-90.]
[14]	王发曾. 我国城市犯罪空间防控研究二十年. 人文地理, 2010, 25(4): 25-30.
	[Wang Fazeng.A review of urban spatial anti-crime study in China from 1980 to 2000. Human Geography, 2010, 25(4): 25-30.]
[15]	杜德斌. 加拿大爱得蒙顿市犯罪问题的地理研究. 地理研究, 1998, 17(4): 415-422. doi: 10.3321/j.issn:1000-0585.1998.04.012
	[Du Debin.A geographical study on the spatial patterns of crimes in Edmonton, Canada. Geographical Research, 1998, 17(4): 415-422.] doi: 10.3321/j.issn:1000-0585.1998.04.012
[16]	余建辉, 张文忠, 王岱, 等. 基于居民视角的居住环境安全性研究进展. 地理科学进展, 2011, 30(6): 699-705. doi: 10.11820/dlkxjz.2011.06.007
	[Yu Jianhui, Zhang Wenzhong, Wang Dai, et al.Living environment safety based on the residents' perception: A review. Progress in Geography, 2011, 30(6): 699-705.] doi: 10.11820/dlkxjz.2011.06.007
[17]	王发曾. 城市空间环境对城市犯罪的影响. 人文地理, 2001, 16(2): 1-7.
	[Wang Fazeng.The urban spatial environment's influences on urban crime. Human Geography, 2001, 16(2): 1-7.]
[18]	Wing M G, Tynon J F.Crime mapping and spatial analysis in national forests. Journal of Forestry, 2006, 104(6): 293-296. doi: 10.1007/978-3-319-27793-6_8
[19]	王益澄, 林玲. 东部沿海城市犯罪问题的城市地理学研究: 以浙江省宁波市为例. 宁波大学学报: 人文科学版, 2009, 22(1): 109-113.
	[Wang Yicheng, Lin Ling.An urban geography-based study of civil crimes in eastern coastal cities: A case study of Ningbo, Zhejiang. Journal of Ningbo University: Liberal Arts Edition, 2009, 22(1): 109-113.]
[20]	周向红. 城市空间环境与犯罪防控的关系: 基于上海部分社区的实证研究. 上海城市规划, 2009, 86(3): 20-23. doi: 10.3969/j.issn.1673-8985.2009.03.006
	[Zhou Xianghong.The relation between the urban space environment and the crime control and prevention: Based on theoretical and empirical study. Shanghai Urban Planning Review, 2009, 86(3): 20-23.] doi: 10.3969/j.issn.1673-8985.2009.03.006
[21]	Oscar N. Defensible Space. New York: Macmillan, 1972.
[22]	Clarke R V. Situational Crime Prevention. Albany: Harrow and Heston, 1992.
[23]	Crowe T D.Crime Prevention Through Environ-Mental Design: Applications of Architectural Design and Space Management Concepts. London: Butterworth-Heinemann, 1991.
[24]	Xiong H.Urban spatial disorganization and crime: punctate distribution pattern. In: Xiong H. Urban Crime and Social Disorganization in China. Singapore: Springer, 2016: 71-93.
[25]	Cornwell C, Trumbull W N.Estimating the economic model of crime with panel data. Review of Economics and Statistics, 1994, 76(2): 360-366. doi: 10.2307/2109893
[26]	卢建平. 中国犯罪治理研究报告. 北京: 清华大学出版社, 2015.
	[Lu Jianping.Report on Chinese Crime Governance. Beijing: Tsinghua University Press, 2015.]
[27]	Richard B, Wim B.Finding a serial burglar's home using distance decay and conditional origin-destination patterns: A test of empirical Bayes journey-to-crime estimation in the Hague. Journal of Investigative Psychology and Offender Profiling, 2009, 6(3): 187-211. doi: 10.1002/jip.108
[28]	Situ Y, Liu W.Restoring the neighborhood, fighting against crime: A case study in Guangzhou city, People's Republic of China. International Criminal Justice Review, 1996, 6(1): 89-102. doi: 10.1177/105756779600600106
[29]	Xu J.Drive-away policing and situational crime prevention in China: An analysis of motorcycle ban (jinmo) policy in Guangzhou. International Journal of Offender Therapy and Comparative Criminology, 2012, 56(2): 239-264. doi: 10.1177/0306624X10395715
[30]	黄慧霞. 广州市抢劫、抢夺犯罪空间特征研究: 一种环境犯罪学视角下的探索. 见: 王牧. 犯罪学论丛: 第4卷. 北京: 中国检查出版社, 2006: 346-382.
	[Huang Huixia.The spatial feature of robbery and loot crimes in Guangzhou: Analysis based on environmental criminology. In: Wang Mu. Criminology Symposium: Volume 4. Beijing: China Procuratorate Press, 2006: 346-382.]
[31]	张强, 陈怡霓, 杨秦. 2015年中国广州社会形势分析与预测. 社会科学文献出版社, 2015.
	[Zhang Qiang, Chen Yini, Yang Qin.Annual and Forecast on Social Situation of Guangzhou in China (2015). Social Sciences Academic Press, 2015.]
[32]	Roberts J P.Bare Branches: The security implications of Asia's surplus male population. Political Psychology, 2006, 27(2): 319-321. doi: 10.1111/pops.2006.27.issue-2
[33]	Steffensmeier D, Allan E.Gender and crime: Toward a gendered theory of female offending. Annual Review of Sociology, 2003, 22(1): 459-487. doi: 10.1146/annurev.soc.22.1.459
[34]	Messner S F, Sampson R J.The sex ratio, family disruption, and rates of violent crime: The paradox of demographic structure. Social Forces, 1991, 69(3): 693-713. doi: 10.1093/sf/69.3.693
[35]	Quetelet A.A Treatise on Man and the Development of His Faculties: A Facsimile Reproduction of the English Translation of 1842. Delmar: Scholars' Facsimiles and Reprints, 1969.
[36]	Deane G D.Cross-national comparison of homicide: Age/sex-adjusted rates using the 1980 U. S. homicide experience as a standard. Journal of Quantitative Criminology, 1987, 3(3): 215-227. doi: 10.1007/BF01063829
[37]	Triplett R, Myers L B.Evaluating contextual patterns of delinquency: Gender-based differences. Justice Quarterly, 1995, 12(1): 59-84. doi: 10.1080/07418829500092571
[38]	Ehrlich I.Participation in illegitimate activities: A theoretical and empirical investigation. The Journal of Political Economy, 1973, 81(3): 521-65. doi: 10.1086/260058
[39]	Kelly M.Inequality and crime. Review of Economics and Statistics, 2000, 82(4): 530-539. doi: 10.1162/003465300559028
[40]	康树华, 张小虎. 犯罪学. 北京: 北京大学出版社, 2004.
	[Kang Shuhua, Zhang Xiaohu.Criminology. Beijing: Peking University Press, 2004.]
[41]	Raphael S, Winter-Ebmer R.Identifying the effect of unemployment on crime. Journal of Law and Economics, 2001, 44(1): 259-284. doi: 10.1086/320275
[42]	章元, 刘时菁, 刘亮. 城乡收入差距、民工失业与中国犯罪率的上升. 经济研究, 2011, (2): 59-72.
	[Zhang Yuan, Liu Shijing, Liu Liang.Can we attribute increasing criminal rate to enlarging urban-rural inequality in China?. Economic Research Journal, 2011, (2): 59-72.]
[43]	Leonida L, Buonanno P.Education and crime: Evidence from Italian regions. Applied Economics Letters, 2006, 13(11): 709-713. doi: 10.1080/13504850500407376
[44]	毛颖. 民生支出有助于减低刑事犯罪率吗: 来自中国(1995-2008)省级面板数据的证据. 南开经济研究, 2011, (4): 32-49. doi: 10.3969/j.issn.1001-4691.2011.04.003
	[Mao Ying.Will the expenditure on people's livelihood reduce crime rate: Evidence from Chinese provincial panel data (1995-2008). Nankai Economic Studies, 2011, (4): 32-49.] doi: 10.3969/j.issn.1001-4691.2011.04.003
[45]	刘瑞明, 毛颖. 中国转型时期的离婚与犯罪: 法律经济学的解释和验证. 世界经济文汇, 2014, (5): 84-104.
	[The divorce and crime during the period of transition in China: The interpretation and verification of the law economics. World Economic Papers, 2014, (5): 84-104.]
[46]	Maume M O, Ousey G C, Beaver K.Cutting the grass: A reexamination of the link between marital attachment, delinquent peers and desistance from marijuana use. Journal of Quantitative Criminology, 2005, 21(1): 27-53. doi: 10.1007/s10940-004-1786-3
[47]	Courtwright D T. Violent Land, Single Men and Social Disorder from the Frontier to the Inner City. Cambridge, Massachusetts: Harvard University Press, 2001.
[48]	Weiss H E, Reid LW.Low-quality employment concentration and crime: An examination of metropolitan labor markets. Sociological Perspectives, 2005, 48(2): 213-232. doi: 10.1525/sop.2005.48.2.213
[49]	王洋, 方创琳, 盛长元. 扬州市住宅价格的空间差异与模式演变. 地理学报, 2013, 68(8): 1082-1096.
	[Wang Yang, Fang Chuanglin, Sheng Changyuan.Spatial differentiation and model evolution of housing prices in Yangzhou. Acta Geographica Sinica, 2013, 68(8): 1082-1096.]
[50]	Morenoff J D, Sampson R J, Raudenbush S W.Neighborhood inequality, collective efficacy, and the spatial dynamics of urban violence. Criminology, 2001, 39(3): 517-559. doi: 10.1111/crim.2001.39.issue-3
[51]	陈斐, 杜道生. 空间统计分析与GIS在区域经济分析中的应用. 武汉大学学报: 信息科学版, 2002, 27(4):391-396. doi: 10.3321/j.issn:1671-8860.2002.04.013
	[Chen Fei, Du Daosheng.Application of the integration of spatial statistical analysis with GIS to the analysis of regional economy. Journal of Wuhan University: Information Science, 2002, 27(4): 391-396.] doi: 10.3321/j.issn:1671-8860.2002.04.013
[52]	王洋, 金利霞, 张虹鸥, 等. 广州市居民住房条件的空间分异格局与形成机制. 地理科学, 2017, 37(6): 868-875.
	[Wang Yang, Jin Lixia, Zhang Hong'ou, et al. The spatial differentiation pattern and formation mechanism of housing conditions in Guangzhou city, China. Scientia Geographica Sinica, 2017, 37(6): 868-875.]
[53]	王洋, 张虹鸥, 叶玉瑶, 等. 广州市社会空间质量的综合评价与分布格局. 热带地理, 2017, 37(1): 25-32. doi: 10.13284/j.cnki.rddl.002910
	[Wang Yang, Zhang Hong'ou, Ye Yuyao, et al. Comprehensive evaluation and distribution pattern of social space quality in Guangzhou, China. Tropical Geography, 2017, 37(1): 25-32.] doi: 10.13284/j.cnki.rddl.002910

犯罪类型	评价因子	代表性指标（单位）	指标的计算过程	对犯罪风险作用方向
侵财犯罪	FP1外来人口	外来人口比重（%）	流动人口/常住人口	正向
	FP2收入	低收入群体比重（%）	月租金低于200元住户数/租房户总户数	正向
	FP3失业	失业率（%）	失业人口/经济活动人口	正向
	FP4职业	低端服务业从业人员比重（%）	（批发和零售业人口+租赁和商务服务业人口 +居民服务和其他服务业人口）/就业总人口	正向
暴力犯罪	FV1性别与年龄	青少年男性人口比重（%）	15~29岁男性人口/常住人口	正向
	FV2教育	低学历人口比重（%）	小学及以下学历人口/6岁及以上常住人口	正向
	FV3婚姻	离婚率（%）	15岁以上离婚人口/15岁以上总人口	正向
	FV4职业	低端服务业从业人员比重（%）	（批发和零售业人口+租赁和商业服务业人口 +居民服务和其他服务业人口）/就业总人口	正向
	FV5住房	租房户比重（%）	租房户数/住房总户数	正向

犯罪类型	指标分类（单位）	信息熵	冗余度	权重
侵财犯罪	外来人口比例（%）	0.9620	0.0380	0.2353
	低收入群体比例（%）	0.9397	0.0603	0.3731
	失业率（%）	0.9612	0.0388	0.2405
	低端服务业从业人员比例（%）	0.9756	0.0244	0.1512
暴力犯罪	青少年男性人口比例（%）	0.9400	0.0600	0.3563
	低学历人口比例（%）	0.9857	0.0143	0.0846
	离婚率（%）	0.9638	0.0362	0.2152
	低端服务业从业人员比例（%）	0.9756	0.0244	0.1450
	租房户比例（%）	0.9665	0.0335	0.1988

	旧城	核心区	中心城区	近郊区
侵财犯罪风险平均值	0.485359	0.332138	0.373958	0.414465
暴力犯罪风险平均值	0.411957	0.318869	0.377209	0.334737
侵财犯罪风险的GDI指数	0.155288	0.321721	0.275701	0.257127
暴力犯罪风险的GDI指数	0.176015	0.227638	0.124541	0.265237