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Spatial and temporal analysis of sex crimes in Charlottesville, Virginia

机译:弗吉尼亚州夏洛茨维尔的性犯罪时空分析

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Sexual assault and interpersonal violence affects university communities in disproportionate numbers to those of the general population. It is estimated that one in five women will be the victims of a sexual assault during their college years. In this study, we use kernel density estimation, logistic regression and random forest modeling to conduct spatial and temporal analysis of sexual assault at the University of Virginia and wider Charlottesville community between 1990 and 2015. This paper takes into account the cultural characteristics of the community to explore the underlying reasons for concentrations of criminal sexual assault behavior. Our results show that proximity to registered sex offenders and Greek life residences are the two most important predictors of sexual assault crime among all the variables studied. These spatial and temporal models provide insights to better understand crime patterns and improve policing and response.
机译:性侵犯和人际暴力对大学社区的影响与普通人群的比例不成比例。据估计,在大学期间,五分之一的妇女将成为性侵犯的受害者。在这项研究中,我们使用内核密度估计,逻辑回归和随机森林模型对弗吉尼亚大学和更广泛的夏洛茨维尔社区在1990年至2015年之间的性侵犯进行了时空分析。本文考虑了该社区的文化特征探索犯罪性侵犯行为集中的根本原因。我们的结果表明,在所有研究的变量中,接近注册的性犯罪者和希腊人的住所是性侵犯犯罪的两个最重要的预测因子。这些时空模型为深入了解犯罪模式和改善警务和应对提供了见识。

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