CRIME DIVERSITY
CRIME DIVERSITY
复制标题
DOI：
10.1111/1745-9125.12116
复制
发表时间：
2016-11-01
期刊：
影响因子：
5.8
通讯作者：
Brantingham, P. Jeffrey
中科院分区：
文献类型：
--
作者：
Brantingham, P. Jeffrey
与小的地理区域相比，大的地理区域应该拥有更多的犯罪多样性。这一主张是合理的，因为更大的地理区域不仅应该支持更多的犯罪，而且还应该包含更多产生犯罪的环境的多样性。本文使用一个中性模型来刻画犯罪丰富度作为面积的函数。该模型从两个中立的假设开始：1)所有环境在统计上是相等的，不会对那里发生的犯罪类型产生影响；2)不同的犯罪类型相互独立地发生。该模型对犯罪丰富度的均值和方差随着面积的增加进行了严格的预测。对2013年洛杉矶发生的172,055起犯罪事件样本进行的模型测试，在质量上符合中性的预期。通过恒定标度使模型在数量上保持一致。重采样实验表明，最多20%的平均犯罪丰富度归因于犯罪类型的非随机聚类和分类。考虑到犯罪集中度变化的修正中性模型与观察到的犯罪丰富度变化是一致的。结果表明，非常普遍和基本中立的法律可能正在推动空间犯罪的多样性。
Large geographic areas should host a greater diversity of crime compared with small geographic areas. This proposition is reasonable given that larger geographic areas should not only support more crime but also contain a greater diversity of criminogenic settings. This article uses a neutral model to characterize crime richness as a function of area. The model starts with two neutral assumptions: 1) that all environments are statistically equivalent and exert no influence on what types of crimes occur there; and 2) that different crime types occur independently of one another. The model produces rigorous predictions for the mean and variance in crime richness with increasing area. Tests of the model against a sample of 172,055 crimes occurring in Los Angeles during the year 2013 are qualitatively consistent with neutral expectations. The model is made quantitatively consistent by constant scaling. Resampling experiments show that at most 20 percent of the mean crime richness is attributable to nonrandom clustering and assortment of crime types. A modified neutral model allowing for variation crime concentration is consistent with observed variance in crime richness. The results suggest that very general and largely neutral laws may be driving crime diversity in space.