Identifying femicide locally and globally: Understanding the utility and accessibility of sex/gender-related motives and indicators
Identifying femicide locally and globally: Understanding the utility and accessibility of sex/gender-related motives and indicators
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DOI：
10.1177/0011392120946359
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发表时间：
2020-08-28
影响因子：
2
通讯作者：
Carrigan, Michelle
中科院分区：
文献类型：
--
作者：
Dawson, Myrna;Carrigan, Michelle
杀戮女性，即与性别相关的杀害妇女和女孩的行为，在过去十年中受到了国际社会前所未有的关注，引发了关于如何定义和衡量杀戮女性的更多讨论。在回顾了定义和指标之后，本文探讨了众多与性/性别相关的动机和指标 (SGRMI) 在区分杀戮女性与其他凶杀案方面的效用，以及这些指标在社会科学研究人员通常访问的数据源中的可访问性。具体来说，使用一个主要关注女性杀戮的综合数据库，将男性-犯罪者/女性-受害者凶杀案（与杀戮女性概念最接近的杀戮）中 SGRMI 的存在与其他犯罪者-受害者性别组合进行比较。结果表明，与其他凶杀案相比，多重 SGRMI 在男性犯罪者/女性受害人杀戮中更为常见，这意味着它们有助于将杀戮女性区分为一种独特的暴力类型。然而，信息的可及性很弱，缺失数据的比例很高。讨论了这些发现对预防的影响，包括数据偏差如何可能使妇女和女孩的生命面临风险，以及需要强调预防作为数据收集的优先事项，而不是政府的行政需求。
Femicide, the gender-related killing of women and girls, has received an unprecedented rise in international attention in the past decade, prompting increased discussions about how to define and measure femicide. Following a review of definitions and indicators, this article examines the utility of numerous sex/gender-related motives and indicators (SGRMIs) for distinguishing femicide from other homicides as well as the accessibility of these indicators in data sources typically accessed by social science researchers. Specifically, using a comprehensive database whose primary focus is femicide, the presence of SGRMIs in male-perpetrator/female-victim homicide - those killings most closely aligned with the concept of femicide - is compared to other perpetrator-victim gender combinations. Results show that multiple SGRMIs are more common in male-perpetrator/female-victim killings than other homicides, meaning they are useful for distinguishing femicide as a distinct type of violence. However, accessibility to information is weak with high proportions of missing data. Implications of these findings for prevention are discussed, including how data biases may be putting the lives of women and girls at risk and the need to emphasize prevention as the priority for data collection rather than administrative needs of governments.