Georgia Southern University, Statesboro, USA.
Iowa State University, Ames, USA.
J Interpers Violence. 2022 Apr;37(7-8):NP3905-NP3929. doi: 10.1177/0886260520951317. Epub 2020 Sep 1.
A large number of studies have examined predictors of female crime quantities yet considerably less attention has been directed toward exploring patterns in the nature or of female violence within and across communities. Although research consistently demonstrates that females engage in less criminal behavior than males, research on the variability across contexts is somewhat sparse. The authors conduct analyses to determine if Anderson's initial observations of female violence in neighborhoods inundated with the code of the streets persist a decade after his initial ethnographic account. Specifically, we examine incident-level data from the National Incident Based Reporting System with contextual-level data on the cities in which the incidents occurred. We use hierarchical linear and nonlinear modeling techniques to explore variations in predictors of offender gun use and extent of victim injury in violent female encounters. Supporting Anderson's initial accounts for street females and prior research we find the probability of gun usage and level of victim injury is not significantly influenced by differences in community context, and specifically not exacerbated by the types of conditions that make the code of the street locally salient.
大量研究探讨了女性犯罪数量的预测因素，但对于探索社区内和社区之间女性暴力的性质或模式的关注要少得多。尽管研究一致表明女性的犯罪行为比男性少，但对跨环境变异性的研究却有些匮乏。作者进行分析以确定在他最初的民族志描述十年后，安德森对充斥着街头规则的社区中的女性暴力的最初观察是否仍然存在。具体来说，我们检查了来自国家事件基础报告系统的事件级数据，以及事件发生城市的上下文级数据。我们使用分层线性和非线性建模技术来探索在暴力女性遭遇中，罪犯使用枪支和受害者受伤程度的预测因素的变化。支持安德森对街头女性的最初描述和之前的研究，我们发现枪支使用的概率和受害者受伤的程度并没有受到社区环境差异的显著影响，特别是没有被使街头规则在当地变得突出的条件类型所加剧。
