The impact of civil registration-based demographic heterogeneity on community thefts
The impact of civil registration-based demographic heterogeneity on community thefts
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基于民事登记的人口异质性对社区盗窃的影响
DOI：
10.1016/j.habitatint.2022.102673
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发表时间：
2022-09-28
影响因子：
6.8
通讯作者：
Chen，Xi
中科院分区：
文献类型：
--
作者：
Xu，Chong;Yang，Yinxia;Chen，Xi
由于中国独特的民事登记制度（户口），使用流动人口或国内流动人口的比例作为种族/民族异质性的指标是应用社会无序理论解释中国城市犯罪的常见做法。然而，这种方法并没有完全反映出中国城市种族/民族异质性的实质内涵。在本研究中，我们在研究中国大城市的犯罪时，除了考虑流动人口的比例外，还考虑了户籍的异质性。基于社会失组织理论，本文采用负二项回归模型，结合2017年的盗窃数据、第六次全国人口普查数据和利益点（POI）来描述民事登记异质性和流动人口比例对盗窃的影响。研究发现：1)基于户口的民族异质性指数能更好地反映中国背景下的民族异质性，对盗窃行为有显著影响；2)拥有更多租赁住房单元的社区更容易发生盗窃；(3)居委会管辖的小区盗窃较多；网吧、银行、超市和餐馆的集聚往往加剧了社区盗窃行为。本研究通过细分社区居民民事登记类别来划分种族/民族异质性，探讨其对社区盗窃的影响，构建更适合中国社区的优化指标。这是对非西方社会犯罪理论和现有方法的有益补充。
Because of China's unique civil registration system (Hukou), using the proportion of floating population or domestic migrants as an index of racial/ethnic heterogeneity is a common practice to apply social disorganization theory to explain crime in Chinese cities. However, this method does not fully reflect the substantive connotation of racial/ethnic heterogeneity in Chinese cities. In this study, we add the heterogeneity of civil registration, i.e. Hukou, in addition to the proportion of floating population when studying crime in a big Chinese city. Following social disorganization theory, we use negative binomial regression models with theft data in 2017, the Sixth National Population Census data, and Point of interests (POI) to delineate effects of the heterogeneity of civil registration and proportion of floating population on thefts. We have four major findings: 1) the Hukou-based ethnic heterogeneity index can better illustrate the ethnic heterogeneity in the Chinese context and have a significant impact on thefts; 2) communities with more rental housing units tend to experience more thefts; 3) there are more thefts in communities that are under the jurisdiction of neighborhood committee; and 4) the agglomeration of Internet cafes, banks, supermarkets, and restaurants tend to exacerbate the thefts in communities. This study subdivides the community residents' civil registration categories to delineate racial/ethnic heterogeneity, explores its impact on community thefts, and constructs a more optimized indicator that better suits communities in China. This is a meaningful supplement to crime theory and existing methods in non-western societies.