Heather Krause
This is a walkthrough of one way to center Indigenous Peoples’ rights and wellbeing at every single step of the statistical process and to document those choices so they’re auditable, accountable, and owned by the right people. We’ll use the Data Equity Framework as scaffolding and make the CARE Principles operational, not ornamental. We’ll introduce a set of tools that enable data practitioners to move stage by stage through the data life cycle with concrete artifacts that highlight choies, priorities, and power dynamics. including: Purpose & power mapping (CARE: Collective Benefit): Define the community purpose first; map who benefits, who decides, and how benefits are returned. Sampling & inclusion audits (Responsibility): Build community-defined universes, oversample where the risk of erasure is highest, and publish the trade-offs. Measurement & instruments (Ethics grounded in Indigenous law/protocols): Co-create indicators, translations, and context notes; retire colonial proxies. Collection & care: Hire and train local enumerators; set data residency and safety protocols. Analysis & modeling choices: Choose methods that match community purpose; state priors; document imputation, weighting, suppression, and uncertainty in plain language. Sense-making & reporting: Do joint interpretation; publish layered products (community briefs first), and credit community intellectual property. No compliance theater here. We’ll show decision logs, data biographies, and template packs you can lift for your next project. This session treats ethics as relationships and statistics as a series of public, community-led choices you can trace, test, and stand behind.