AI 中文总结
本研究利用纵向街头外展数据，采用关系事件模型分析营地清理后无家可归者的流动与住房结果，发现其迁移距离近、难获住房，且精神疾病患者对原住地依恋更强，为相关研究提供了实证支持。
AI 中文摘要
2024年格兰茨帕斯（Grants Pass）的裁决进一步鼓励美国各城市通过被迫流离失所来管理无遮蔽的无家可归问题。尽管已有文献表明该策略会造成有害的健康和物质影响，但其对住房结果和流动模式的长期影响仍不太明确。为此，本研究利用纵向街头外展数据，调查人们在营地清理后迁移到何处。我们特别采用关系事件模型（relational event models）来预测清理后各种结果的可能性，例如迁移到其他普查区、进入收容所或获得住房。结果显示，流离失所的居民迁移距离不远，但清理仍可能通过减少营地社区规模来降低可见的无家可归现象。此外，人们似乎不太可能迁移到室内，反而面临与服务提供者失去联系的高风险。无论个体人口统计特征如何，这些趋势均成立，尽管有精神健康状况的人对其原住地表现出更强的依恋。证据还表明，社区条件可能影响这些迁移行为。这些发现证实了关于场所依恋、居住流动性和贫困隐形化的更广泛文献。本文最终回应了迫切需求，即更深入理解被迫流离失所如何影响无家可归问题及住房获取途径。
英文摘要
The 2024 Grants Pass decision newly emboldens US cities to manage unsheltered homelessness through forced displacement. Although literature demonstrates the harmful health and material impacts of this tactic, the longer-term results for housing outcomes and migration patterns remain less clear. In response, this study leverages longitudinal street outreach data to investigate where people move following encampment clearances. We specifically employ relational event models to predict the likelihood of various outcomes post-removal, such as relocating tracts, entering shelter, or obtaining housing. Results suggest that displaced residents do not travel far, yet clearances may still reduce visible homelessness by decreasing the size of camp communities. Furthermore, people appear unlikely to move indoors and instead face high risks of losing contact with service providers. These trends hold regardless of individual demographics, although people with mental health conditions demonstrate stronger attachments to their original sites. Evidence additionally indicates that neighborhood conditions could influence these migration behaviors. Such findings corroborate broader literature on place attachments, residential mobility, and invisibilization of poverty. This paper ultimately addresses the urgent need for a deeper understanding of how forced displacement impacts homelessness and pathways to housing.
