Using Science to Build Tribal Capacity for Data-Intensive Research

联邦政府对部落国家负有信托责任，这一责任通过旨在促进经济自给自足和部落国家及其人民独特的主权地位的联邦法规和方案来实施。高质量的部落级数据对于确保联邦信任和为部落首领加强政府的工作提供信息至关重要。在这一更广泛的背景下，该项目将通过建立部落、社会科学家和联邦政策制定者的数据网络，协助正在进行的部落数据收集，以提高部落数据的可靠性、有效性和长期可持续性，并通过使用人口普查局S研究数据中心，为部落提供更符合部落边界和部落需求的数据，从而提高部落数据的质量和数据密集型研究的能力。这项工作的广泛影响是深远的，包括：1)改进数据收集和分析，以帮助部落更好地满足他们所服务的土著人口的需求；2)加强部落数据基础设施，以便能够制定比较分析和政策，而不是基于单个部落案例；3)通过部落的真实数据经验，为社会科学研究美洲印第安人和阿拉斯加土著(AI/AN)的人口特征提供新的见解；4)解决部落政府面临的数据安全和保密问题；以及5)关于大数据集中数据联系和土著身份识别等新兴国际对话的见解。美国拥有无与伦比的科学能力，但它长期以来甚至未能提供最基本的人工智能/人工智能人的统计。尽管有详尽的文件表明，这些人口面临着巨大的贫困风险，以及贫困带来的问题，但有关劳动力参与、社会服务需求、教育程度和相关信息的详细信息很少，也不可靠。统计问题涉及与适合部落人口的指标有关的问题，与为部落数据生成适当地理边界有关的问题，以及与为计量目的实际收集部落数据有关的问题。该项目旨在采用参与式研究方法解决列举问题。它探讨了如何提高部落一级数据收集、报告和管理的质量，以帮助部落首领、联邦政策制定者和社会科学家。该项目将利用多种方法，包括通过访谈和焦点小组进行定性数据收集和分析，对从人口普查局、S研究数据中心和合作伙伴部落收集的二次数据进行量化分析，以及由伙伴部落收集调查数据。其目标是开发一系列工具和资源，以改善部落层面的数据收集和使用，包括一个调查模板，部落国家以及人口普查局和内政部等联邦机构可以使用该模板来补充现有的从美国印第安人和阿拉斯加原住民那里收集的个人层面的数据。

The federal government has a trust responsibility to tribal nations that is implemented through federal statutes and programs intended to promote economic self-sufficiency and the distinct sovereign status of tribal nations and their people. Quality, tribal-level data is essential for ensuring the federal trust and for informing the work of tribal leaders to strengthen their governments. Within this broader context, this project will improve tribal data quality and capacity for data-intensive research by building a data network of tribes, social scientists and federal policymakers; assisting with ongoing tribal data collection designed to improve the reliability, validity, and long-term sustainability of tribal data; and by using the Census Bureau?s Research Data Centers to provide tribes with data better aligned to tribal boundaries and tribal needs. The broader impacts of this work are far reaching and include: 1) Improved data collection and analyses to assist tribes to better meet the needs of the Native populations they serve; 2) Strengthened tribal data infrastructure so that comparative analyses can be developed and policy based on more than individual tribal cases; 3) New insights for social science research about American Indian and Alaska Native (AI/AN) demographic characteristics through real-world data experiences of tribes; 4) Solutions to data security and confidentiality issues facing tribal governments; and 5) Insights for emerging international conversations about data linkage and Indigenous identification in large data sets, amongst others.The United States boasts unmatched scientific capacity, but it has long failed to provide even the most basic enumeration of AI/AN people. Despite thorough documentation that this population is at great risk of poverty and the problems that flow from poverty, detailed information about labor force participation, social service needs, educational attainment, and related information is sparse and unreliable. Enumeration issues involve those related to indicator fit for tribal populations, those related to generating appropriate geographic boundaries for tribal data, and those related to the actual collection of tribal data for measurement purposes. This project is designed to address enumeration issues using a participatory approach to research. It explores the question of how to improve the quality of tribal-level data collection, reporting, and management to assist tribal leaders, federal policymakers, and social scientists. The project will utilize multiple methods, including qualitative data collection and analysis through interviews and focus groups, quantitative analysis of secondary data collected from the Census Bureau?s Research Data Centers and from, and survey data collection by partner tribes. The goal is to produce a range of tools and resources to improve tribal-level data collection and use, including a survey template that could be used by tribal nations and federal agencies like the Census Bureau and the Department of the Interior to supplement existing person-level data collection from American Indian and Alaska Native people.