EAGER: ISN: Modeling Operations of Human Trafficking Networks for Effective Interdiction

这项探索性研究的早期概念拨款将有助于我们了解并有能力破坏非法性贩运网络的运作，从而加强国家的健康、繁荣和福利。在美国，性交易是一个复杂的社会和犯罪企业，与非法的性劳动市场交织在一起，需要高度剥削，往往是暴力，以获取利润。由于贩运是隐蔽的、非法的和危险的，因此很难收集必要的数据，以制定贩运网络的有效定量业务模型及其对干预措施的反应。为了应对这一挑战，该项目将建立一个由社会科学家、业务研究人员、执法人员和性交易幸存者组成的协作团队，分析执法数据，建立网络模型。该奖项将支持识别性交易网络的独特方面，这些方面将为数学模型提供信息，从而支持有效决策以破坏这些网络。该项目将产生性贩运网络数据，可用作测试这些模型的基础。性交易的受害者不成比例地来自我们最脆弱的社区，包括那些生活贫困、之前有过性侵犯、家庭暴力、离家安置、无家可归和其他创伤经历的人。预计该项目将对这些人口的健康、繁荣和福利产生特别的影响。本研究将对执法案件档案和利益相关者访谈进行定性分析，以确定性交易网络的最重要特征，包括其构成、其如何适应拦截，以及其实体网络和网络网络之间的依赖关系。研究小组将确定这些案例中性交易网络的底层结构和关键特征，构建数据的节点弧网络表示，并确定当前网络拦截模型的关键变化，以确保在破坏性交易操作中的适用性。该项目将开始填补限制其适用于破坏人口贩运网络的拦截文献中最重要的空白。由此产生的网络数据将公开提供，研究小组将详细说明复制网络生成过程的方法，以开发其他贩运网络数据集，包括劳工贩运网络。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This EArly-concept Grant for Exploratory Research (EAGER) will enhance the national health, prosperity, and welfare by contributing to our understanding of and ability to disrupt the operations of illicit sex trafficking networks. Sex trafficking within the United States is a complex social and criminal enterprise interwoven within the illegal labor market for sex, and entails highly exploitative, often violent, means to extract profit. Because trafficking is hidden, illegal and dangerous it is difficult to gather the data needed to develop effective quantitative operational models of trafficking networks and their response to interventions. To tackle this challenge, the project will build a collaborative team of social scientists, operations researchers, law enforcement personnel, and sex trafficking survivors to analyze law enforcement data for network modeling. This award will support identification of unique aspects of sex trafficking networks that will inform mathematical models that can support effective decisions to disrupt these networks. The project will produce sex trafficking network data that can be used as a basis for testing such models. Sex trafficking victims disproportionally come from our most vulnerable communities, including those who live in poverty and have had prior experiences of sexual assault, family violence, out of home placement, homelessness, and other traumatic experiences. This project is expected to have a particular impact on the health, prosperity, and welfare of these populations.This research will apply qualitative analysis of law enforcement case files and stakeholder interviews to identify the most important features of sex trafficking networks, including their composition, how they adapt to interdictions, and the dependencies between their physical and cyber networks. The research team will identify the underlying structure and key features of sex trafficking networks in these cases, construct node-arc network representations of the data, and identify key changes to current network interdiction models to ensure applicability in disrupting sex trafficking operations. The project will begin to fill the most significant gaps in the interdiction literature that limits its applicability to disrupting human trafficking networks. The resulting network data will be made publicly available and the study team will detail methods for replicating the network generation process to develop additional trafficking network datasets, including labor trafficking networks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.