Statistical Approaches to the Inclusion of Indigenous Knowledge in Modelling (Cancelled) (22w5093)

The Banff International Research Station will host the "Statistical Approaches to the Inclusion of Indigenous Knowledge in Modelling " workshop at the UBC Okanagan campus in Kelowna, B.C., from May 29 to June 3, 2022.

The inclusion of Indigenous knowledge (IK) in environmental research, monitoring, and management can promote shared learning between scientists and IK holders, empower local communities, and increase the breadth and depth of information available compared to conventional scientific studies. Despite these benefits, it remains a challenge to ethically and effectively bridge science and IK in ways that recognize the parallel yet unique aspects of each. This workshop will address one particular facet of this topic: statistical and mathematical approaches to bridging different knowledge types in modelling studies. It will bring together statisticians and mathematicians working in ecology and environmental sciences, IK researchers, and Indigenous Peoples to explore the ethical and practical considerations of including IK in modelling. Our objectives are threefold: (1) to promote awareness among scientists of the nuances and ethical considerations of engaging with IK in their research, (2) to share and develop new statistical methods for the respectful inclusion of IK in modelling studies, and (3) to introduce modelling concepts to IK holders so they can make more informed decisions about whether and how to collaborate with researchers implementing modelling approaches.

The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. BIRS is supported by Canada's Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional de Ciencia y Tecnología (CONACYT).