Transportation Policy and Indigenous Ways of Knowing: What Counts as Evidence in Tribal Policy Contexts? - Cole Grisham (Hatfield Graduate Journal of Public Affairs)
Evidence-based policy making is the notion that policy decisions should be based on (1) rigorous data collection and research and (2) focus on ‘what works.’ This approach aligns with the broader theory of New Public Management (NPM), which contends that the public sector should adopt the practices of and operate more like the private sector, including a reliance on measuring performance. That said, the application of evidence-based policy approaches to Tribal contexts is often difficult, if not impossible, due to the reliance on oral traditions rather than data collection. The result is that Tribal contexts are often underrepresented in contemporary policy analyses or overlooked for services that analyses should have otherwise directed policymakers towards. The questions then are (1) whether evidence-based policy making and Tribal policy contexts are compatible or not and (2) how would either need to adapt accommodate the other? Some social science researchers in Tribal contexts employ Indigenous Research Methods (IRM) in contrast to contemporary positivist approaches, emphasizing storytelling, relationship, and positionality. Unlike evidence-based policy making, which is rooted in positivist views that knowledge is objective and verifiable, IRM suggests a more interpretive worldview and that reality is subjective, socially constructed, and a composite of multiple perspectives. I argue that the two approaches are not incompatible but instead that evidence-based policy making and IRM can inform one another. The underlying issue separating the two is what constitutes ‘knowledge’ for the purposes of policy decision making. In this paper, I outline the foundations of evidence-based policy making in comparison with Indigenous Research methods, including the assumptions, applications, and gaps implied by both. My intent is to show how the two approaches align and diverge as well as what this means for researchers operating in both context.