Framework for Centering Racial Equity Throughout the Administrative Data Life Cycle

Abstract

IntroductionData integration by local and state governments is undertaken for the public good to support theinterconnected needs of families and communities. Though data infrastructure is a powerful toolto support equity-oriented reforms, racial equity is rarely centered or prioritized as a core goalfor data integration. This raises fundamental concerns, as integrated data increasingly provide theraw materials for evaluation, research, and risk modeling. Generally, institutions have not adequatelyexamined and acknowledged structural bias in their history, or the ways in which data reflect systemicracial inequities in the development and administration of policies and programs. Meanwhile, civicdata users and the public are rarely consulted in the development and use of data systems ObjectivesThis paper presents a framework and site-based examples of “Work in Action” that werecollaboratively generated by a civic data stakeholder workgroup from across the U.S. in 2019–2020. MethodsPurposive sampling was used to curate a diverse 15-person workgroup that used participatory actionresearch and public deliberation to co-create a framework of best practices. ResultsThis framework aims to support agencies seeking to acknowledge and compensate for the harmsand bias baked into data and practice. It is organized across six stages of the administrativedata life cycle—planning, data collection, data access, use of algorithms/statistical tools, analysis,and reporting and dissemination. For each stage, the framework includes positive and problematicpractices for centering racial equity, with site-based examples of “Work in Action” from across theU.S. Using this framework, the workgroup then developed a Toolkit for Centering Racial EquityThroughout Data Integration, a resource that has been broadly disseminated across the U.S. ConclusionsFindings indicate that centering racial equity within data integration efforts is not a binary outcome,but rather a series of small steps towards more equitable practice. There are countless ways tocenter racial equity across the data life cycle, and this framework provides concrete strategies fororganizations to begin to grow that work in practice.