Doctoral Dissertation Research: Investigating differential data collection among migrants, aid workers, and officials

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公法117-2)。政治和环境动荡导致个人流离失所。记录流动人口有助于努力改善流离失所的影响。流动人口的记录也具有挑战性，因为个人在途中通过各种临时设施和住房安排。此外，个人的特征--无论是移民还是与移民互动的人--都会影响记录移民特征和流动的方式，从而在记录过程中造成鲜为人知的差异。这项博士论文研究运用治理和文化人类学的理论来理解个体属性的交集如何影响移民与援助人员和政府官员的互动。除了支持对人类学研究生进行实证、科学数据收集和分析方法的培训外，该项目还通过向相关利益攸关方和政策制定者广泛传播其研究结果来增进对科学的理解。具体地说，这项研究项目调查了援助人员和政府官员在与不同种族的移民互动时如何使用不同的数据收集技术。这名博士生使用人种学和档案学方法回答研究问题，重点是援助人员和政府官员如何理解和使用数据收集技术，以及工作人员、官员和移民的个人特征如何影响不同技术的使用。这些发现为人道主义行为者、机构和政策制定者提供了指导，这些人有兴趣更好地了解哪些数据收集战略和相关做法在为受移民影响的个人和社区取得积极成果方面最有效。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Political and environmental turmoil have led to the displacement of individuals from their homes. Documenting mobile populations facilitates efforts to ameliorate the effects of displacement. Documentation of mobile populations is also challenging as individuals move through various temporary facilities and housing arrangements while en route. Moreover, the traits of individuals – both migrants and those with whom migrants interact – affect how migrant characteristics and movements are documented, creating poorly understood variation in the process of documentation. This doctoral dissertation research uses theory from governance and cultural anthropology to understand how the intersections of individual attributes affect migrant interactions with aid workers and government officials. In addition to supporting the training of a graduate student in anthropology in methods of empirical, scientific data collection and analysis, the project enhances scientific understandings by broadly disseminating its findings to relevant stakeholders and policy makers. Specifically, this research project investigates how different data collection technologies are employed by aid workers and government officials as they interact with heterogeneous migrants. The doctoral student uses ethnographic and archival methods to answer research questions focusing on how aid workers and government officials understand and use data collection technologies, and how individual characteristics of the workers, officials, and migrants affect the use of different technologies. These findings offer guidance to humanitarian actors, agencies, and policy makers interested in better understanding which data collection strategies and associated practices are most effective in achieving positive outcomes for individuals and communities affected by migration.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.