Advancing trust and accountability through community governance of immigration data: embedding community perspectives.

Abstract

Objective: Outside recognized Indigenous Data Governance Principles, there is a growing movement towards community governance of other demographic data. Community governance seeks to recenter decision-making about how data are used and reported with those who are the subject of the data, but broad understanding on how to operationalize this principle is lacking. We sought to develop a community-guided governance approach for the use of immigration data at ICES, a health data institute which holds administrative health and demographic data for the province of Ontario, Canada.

Approach: Community perspectives to guide our approach were gathered using semi-structured focus groups. 36 individuals were recruited using purposive and snowball sampling based on their lived or professional expertise in immigration.

Results: Key recommendations emerged from the discussions, including 1) clearly delineating which research projects would require community engagement; 2) emphasizing the need for reciprocity in community relationships; 3) building researchers' capacity in critical reflexivity and data contextualization; 4) developing an organizational change management strategy to socialize expectations; and 5) establishing an intersectionally diverse Community Governance Advisory Table to guide and oversee the approach.

Conclusion: These discussions highlighted tangible operational considerations, including the importance of engagement with immigrant communities and of change management when implementing structural-level change to organizational processes. We will employ a participatory approach to further develop and operationalize community members' recommendations.