Article by Dylan Baysa, Melodie A. Lopez & Lana Fred: “For years, nearly every piece of data the Tucson Indian Center (TIC) collected was designed to answer someone else’s questions. Since 1963, TIC has served the urban Native community in Tucson, Arizona, offering primary care and behavioral health services, diabetes prevention and wellness programs, employment and job training, and emergency housing assistance. Intake forms for those programs, satisfaction surveys, and reporting metrics were all developed to collect data that met federal grant requirements but told us almost nothing about what our community wanted to know about itself.
Eventually, those of us leading and working at TIC said, “Enough.” We began building a different kind of data system—one organized around our community’s priorities. But to understand why this work is both difficult and transformative requires understanding the origins of contemporary data systems that are used to quantify Native people in the United States.
For much of the 19th and 20th centuries, information about Native peoples was collected and controlled primarily by federal agencies, academic institutions, and other outside entities. Rooted in settler colonialism and white supremacy, that control was part of broader efforts to dominate Native land, identity, and governance, and it has left many Native nations dependent on data rarely collected by or for them. Data, including census records and blood-quantum classifications, were used to define Native identity, determine eligibility for land and government benefits, and advance assimilation policies, often with limited Tribal authority over how information was collected, interpreted, shared, or used. In this way, quantification became a tool of administration and control. Research also frequently took a deficit-based approach, emphasizing poverty, health disparities, unemployment, and other challenges while overlooking community strengths, cultural knowledge, Tribal priorities, and the social and historical conditions shaping those outcomes. In doing so, it reinforced stereotypes and informed policy without adequately reflecting Indigenous perspectives. Many of today’s data failures, such as the chronic failure to collect mortality data for Indigenous populations, continue that history through seemingly mundane administrative policy and practice…(More)”.
