RAPID: Data Collection for Designing Refugee Matching Systems

该快速反应研究赠款（RAPID）奖支持为最近流离失所的阿富汗和乌克兰难民重新安置到美国的收容社区收集定性和定量数据。通过一种很少使用的途径，即人道主义假释，美国正在通过非政府组织（NGO）和社区合作伙伴提供安全、法律的移民的快速手段，对流离失所的阿富汗和乌克兰难民的紧急需求做出回应。因此，这一途径为获得难民和社区偏好和结果数据提供了一个短暂的机会之窗，而这些数据以前是不存在的，或者是以非系统、临时的方式收集的。这些新数据将有助于为今后的研究提供信息，例如调查匹配系统，该系统利用难民的偏好和收容社区的优先事项，有效地指导决策，并以有限的资源取得更好的结果。这一项目有利于繁荣和健康的国家利益，使未来的匹配系统能够纳入难民和社区的偏好和结果数据，以支持所服务的难民的社会联系和最终融入社区。通报对难民偏好和结果的重要理解，以改进涉及三个利益和能力互补的关键行为者的匹配决策：难民、收容社区和非营利利益相关者。将通过一系列焦点小组、半结构化访谈和现有工件的内容分析来收集强大的定性和定量数据。这项研究为未来的系统提供了基础，例如重新安置工作人员和社区利益相关者（如邻里支持团队）之间共享的数据收集动态界面，以及匹配推荐系统，以改善目前支离破碎和脱节的流程。这项研究的结果承诺更明智和数据驱动的决策，更合适的匹配建议，并增加难民和社区的归属感和繁荣。今后的研究将力求设计匹配系统，以符合社区资源的方式，预期难民的需求和偏好，以减轻这些移民由于缺乏对需求和资源的认识而面临的创伤和不确定性。该奖项反映了NSF的法定使命，并通过利用基金会的知识价值和更广泛的影响进行评估，被认为值得支持审查标准。

This Grant for Rapid Response Research (RAPID) award supports collection of qualitative and quantitative data for recently displaced Afghan and Ukrainian refugees relocated to host communities in the United States. Through a rarely used pathway known as humanitarian parole, the US is responding to urgent needs of displaced Afghan and Ukrainian refugees by providing an expedited means for secure, legal migration through non-governmental organizations (NGOs) and community partners. As such, this pathway provides an ephemeral window of opportunity for obtaining refugee and community preference and outcomes data, which previously was nonexistent or was collected in a nonsystematic, ad hoc manner. These new data will serve to inform future research such as the investigation of matching systems that use refugee preferences and host community priorities to effectively guide decision making and derive better outcomes with limited resources. This project benefits the national interests of prosperity and health by empowering future matching systems to incorporate refugee and community preferences and outcome data to support the social connections and eventual community integration of refugees served.This project advances the state of knowledge of both pre- and post-arrival refugee data, informing critical understanding of refugee preferences and outcomes to improve matching decision-making involving three key actors with complementary interests and capacities: refugees, host communities, and nonprofit stakeholders. Robust qualitative and quantitative data will be collected through a series of focus groups, semi-structured interviews, and content analysis of existing artifacts. This research provides a foundation for future systems, such as dynamic interfaces for data collection shared between resettlement staff and community stakeholders (like neighborhood support teams), as well as matching recommendation systems to improve what are presently fragmented and disconnected processes. The results of this study promise more informed and data-driven decision making, more fitting matching recommendations, and increased belonging and thriving for refugees and communities. Future research will seek to design matching systems that are anticipative of refugee needs and preferences in a manner that aligns with the resources of communities, so as to alleviate the trauma and uncertainty that such immigrants face due to a lack of awareness of needs and resources.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.