Linking physical violence to women’s mobility in Chile

IF 3 2区 计算机科学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Hugo Contreras, Cristian Candia, Rodrigo Troncoso, Leo Ferres, Loreto Bravo, Bruno Lepri, Carlos Rodriguez-Sickert
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Abstract

Despite increased global attention on violence against women, understanding the factors that lead to women becoming victims remains a critical challenge. Notably, the impact of domestic violence on women’s mobility—a critical determinant of their social and economic independence—has remained largely unexplored. This study bridges this gap, employing police records to quantify physical and psychological domestic violence, while leveraging mobile phone data to proxy women’s mobility. Our analyses reveal a negative correlation between physical violence and female mobility, an association that withstands robustness checks, including controls for economic independence variables like education, employment, and occupational segregation, bootstrapping of the data set, and applying a generalized propensity score matching identification strategy. The study emphasizes the potential causal role of physical violence on decreased female mobility, asserting the value of interdisciplinary research in exploring such multifaceted social phenomena to open avenues for preventive measures. The implications of this research extend into the realm of public policy and intervention development, offering new strategies to combat and ultimately eradicate domestic violence against women, thereby contributing to wider efforts toward gender equity.

Abstract Image

将身体暴力与智利妇女的流动性联系起来
尽管全球越来越关注对妇女的暴力行为,但了解导致妇女成为受害者的因素仍然是一项重大挑战。值得注意的是,家庭暴力对妇女流动性的影响——这是决定她们社会和经济独立的关键因素——在很大程度上仍未得到研究。这项研究弥补了这一差距,利用警方记录来量化身体和心理上的家庭暴力,同时利用手机数据来代理妇女的流动性。我们的分析揭示了身体暴力与女性流动性之间的负相关关系,这种关系经受住了稳健性检查,包括对教育、就业和职业隔离等经济独立变量的控制,数据集的自举,以及应用广义倾向得分匹配识别策略。该研究强调了身体暴力对减少女性流动性的潜在因果作用,强调了跨学科研究在探索这种多方面的社会现象以开辟预防措施途径方面的价值。这项研究的影响延伸到公共政策和干预发展领域,为打击并最终消除针对妇女的家庭暴力提供了新的战略,从而为实现性别平等做出了更广泛的努力。
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来源期刊
EPJ Data Science
EPJ Data Science MATHEMATICS, INTERDISCIPLINARY APPLICATIONS -
CiteScore
6.10
自引率
5.60%
发文量
53
审稿时长
13 weeks
期刊介绍: EPJ Data Science covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital “tracks” of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.
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