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Spatial dark figures of rapes: (In)Consistencies across police and hospital data

机译:强奸的空间黑暗数据:(in)警察和医院数据的一致

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摘要

The dark figures of crime are occurrences that, by some criteria, are called crime yet that are not registered in the official statistics. According to several studies, only a few rapes are reported to the authorities. The current study, using crime data from Campinas, Brazil, sought to examine the spatial dark figures of rapes through the comparison between the spatial patterns of incidents from an official source (police) and the spatial patterns of incidents from an unofficial source (hospital). We used Kernel density estimation maps, generalized Gini coefficient, and a spatial point patterns test to measure the spatial dissimilarities between both sources. Also, we estimated the likelihood of spatial dark figures of rapes using logistic regression models. The results indicate patterns of spatial dark figures of rapes and its association with the street segment and the neighborhood factors. The findings suggest the potential for partnerships between police and medical services in targeting locations with high levels of rape underreport. In addition, it supports place-based prevention measures.
机译:犯罪的黑暗形象是出现的,通过一些标准,被称为犯罪,但尚未在官方统计中登记。根据几项研究,仅向当局报告了几个强奸。目前的研究,利用巴西坎皮纳斯的犯罪数据,试图通过比较来自官方来源(警察)的事件的空间模式与非官方来源的事件的空间模式(医院)的空间模式的比较来检查强奸的空间黑暗数据。我们使用内核密度估计图,广义基尼系数和空间点模式测试来测量两个来源之间的空间异化。此外,我们估计使用Logistic回归模型的Rapes的空间黑暗数据的可能性。结果表明,与街道段和街道区间的空间黑暗数据的样式及其与邻域因素。调查结果表明,警察和医疗服务之间的伙伴关系潜在,在具有高水平的强奸额外的地点。此外,它还支持基于地点的预防措施。

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