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城市犯罪集中程度的衡量

The scaling of crime concentration in cities.

作者信息

Oliveira Marcos, Bastos-Filho Carmelo, Menezes Ronaldo

机构信息

BioComplex Laboratory, Florida Institute of Technology, Melbourne, Florida, United States of America.

Escola Politécnica de Pernambuco, Universidade de Pernambuco, Recife, Pernambuco, Brazil.

出版信息

PLoS One. 2017 Aug 11;12(8):e0183110. doi: 10.1371/journal.pone.0183110. eCollection 2017.

DOI:10.1371/journal.pone.0183110
PMID:28800604
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5553724/
Abstract

Crime is a major threat to society's well-being but lacks a statistical characterization that could lead to uncovering some of its underlying mechanisms. Evidence of nonlinear scaling of urban indicators in cities, such as wages and serious crime, has motivated the understanding of cities as complex systems-a perspective that offers insights into resources limits and sustainability, but that usually neglects details of the indicators themselves. Notably, since the nineteenth century, criminal activities have been known to occur unevenly within a city; crime concentrates in such way that most of the offenses take place in few regions of the city. Though confirmed by different studies, this concentration lacks broad analyses on its characteristics, which hinders not only the comprehension of crime dynamics but also the proposal of sounding counter-measures. Here, we developed a framework to characterize crime concentration which divides cities into regions with the same population size. We used disaggregated criminal data from 25 locations in the U.S. and the U.K., spanning from 2 to 15 years of longitudinal data. Our results confirmed that crime concentrates regardless of city and revealed that the level of concentration does not scale with city size. We found that the distribution of crime in a city can be approximated by a power-law distribution with exponent α that depends on the type of crime. In particular, our results showed that thefts tend to concentrate more than robberies, and robberies more than burglaries. Though criminal activities present regularities of concentration, we found that criminal ranks have the tendency to change continuously over time-features that support the perspective of crime as a complex system and demand analyses and evolving urban policies covering the city as a whole.

摘要

犯罪是对社会福祉的重大威胁,但缺乏一种统计特征描述,而这种描述可能有助于揭示其一些潜在机制。城市指标(如工资和严重犯罪)的非线性缩放证据促使人们将城市理解为复杂系统——这一观点为资源限制和可持续性提供了见解,但通常忽略了指标本身的细节。值得注意的是,自19世纪以来,人们就知道犯罪活动在城市内部分布不均;犯罪集中的方式是,大多数犯罪发生在城市的少数区域。尽管不同研究都证实了这种集中现象,但对其特征缺乏广泛分析,这不仅阻碍了对犯罪动态的理解,也妨碍了提出合理的对策。在此,我们开发了一个框架来描述犯罪集中情况,该框架将城市划分为人口规模相同的区域。我们使用了来自美国和英国25个地点的分类犯罪数据,这些数据涵盖了2至15年的纵向数据。我们的结果证实,无论城市如何,犯罪都会集中,并且揭示了集中程度与城市规模无关。我们发现,城市中犯罪的分布可以用幂律分布来近似,其指数α取决于犯罪类型。特别是,我们的结果表明,盗窃比抢劫更倾向于集中,抢劫比入室盗窃更倾向于集中。尽管犯罪活动呈现出集中规律,但我们发现犯罪排名有随时间不断变化的趋势——这些特征支持了将犯罪视为复杂系统的观点,并要求对整个城市进行分析并制定不断演变的城市政策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a23a/5553724/b75e720e44df/pone.0183110.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a23a/5553724/511fc0c905e8/pone.0183110.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a23a/5553724/03352621ae3a/pone.0183110.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a23a/5553724/1f526b38f125/pone.0183110.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a23a/5553724/b75e720e44df/pone.0183110.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a23a/5553724/511fc0c905e8/pone.0183110.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a23a/5553724/03352621ae3a/pone.0183110.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a23a/5553724/1f526b38f125/pone.0183110.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a23a/5553724/b75e720e44df/pone.0183110.g004.jpg

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