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Statistical Biases, Measurement Challenges, and Recommendations for Studying Patterns of Femicide in Conflict
Peace Review ( IF 0.4 ) Pub Date : 2022-03-26 , DOI: 10.1080/10402659.2022.2049002
Maria Gargiulo

Collecting data on conflict mortality—including data on femicide—is difficult and can be dangerous. The resulting data is often incomplete and not statistically representative of the victim population as a whole. Data on femicide in conflict suffers from additional complications due to measurement challenges stemming from definitional and operational ambiguities. Despite these difficulties, as more and higher quality data on femicide becomes available, there are new opportunities to use statistical methods to study patterns of violence, which can help inform policy and accountability efforts. However, this data needs to be used carefully: drawing population level inferences from incomplete datasets risks misunderstanding the true underlying dynamics of the violence. This article explores the challenges and opportunities of collecting and analyzing data on femicide and offers four recommendations for data collectors and data analysts.



中文翻译:

统计偏差、测量挑战和研究冲突中杀害女性模式的建议

收集冲突死亡率数据(包括杀害女性的数据)很困难,而且可能很危险。由此产生的数据通常不完整,并且在统计上不能代表整个受害者群体。由于定义和操作上的模糊性带来的测量挑战,冲突中杀害女性的数据受到额外的复杂性影响。尽管存在这些困难,但随着越来越多、更高质量的杀害女性数据的出现,使用统计方法研究暴力模式的新机会出现了,这有助于为政策和问责工作提供信息。但是,需要谨慎使用这些数据:从不完整的数据集中得出人口水平的推论可能会误解暴力的真正潜在动态。

更新日期:2022-03-26
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