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RAPID: Data Collection for Designing Refugee Matching Systems

RAPID: Data Collection for Designing Refugee Matching Systems
RAPID:用于设计难民匹配系统的数据收集
批准号:
2233377
负责人:
Andrew Trapp
金额:
$6.49万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-08-01 至 2024-07-31

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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.
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Collaborative Research: FW-HTF-R: Mobilizing Nonprofit Resources and Talents with a Community Tool for Purpose-Driven Work
  • 批准号:
    2222713
  • 项目类别:
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  • 资助金额:
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  • 财政年份:
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  • 负责人:
    Andrew Trapp
  • 依托单位:
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  • 负责人:
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