IASSIST 2023: C2 Finding tools for data documenting racism

In the wake of the murders of George Floyd, Breonna Taylor and Ahmaud Arbery in 2020, among other (on-going) acts of violence against African Americans, a group of IASSIST members felt compelled to gather materials that can help all of us better recognize, acknowledge and combat inherent racial bias. Their work led to the formation of the current IASSIST Anti-Racism Resources Action Group. This Group has three subgroups that have been working to compile a variety of resources that might otherwise be difficult to find, such as: (1) sources of data and datasets on a variety of topics that document racism and the Black experience internationally; (2) tools, articles and rubrics for building anti-racism into the process of working with data across the research lifecycle.

This panel consists of members of the subgroup that is working to developing a guide for finding these race and race-related data and resources. We will discuss the challenges and considerations in finding data documenting racism and the Black experience internationally, as well discrimination based on indigenous, national, and cultural/ethnic origins. We will share strategies and examples of how to apply the strategies. We will answer questions about the finding tool and the related list of data sources and guides for working with an anti-racism lens. We may begin to explore how these tools might be adapted and expanded over time to address other types of discrimination, such as by migrant/refugee status, religion, gender identity, or sexuality." The panel welcome participants feedback on strategies and their knowledge and experience that can contribute to making these tools applicable internationally and inclusive.

Van Bich Tran
Temple University
United States

Jennifer Boettcher
Georgetown University
United States

Kevin Manuel
Toronto Metropolitan University
Canada

Jenny McBurney
University of Minnesota - Twin Cities
United States

Ryan Womack
Rutgers University
United States

Anja Perry
GESIS - Leibniz Institute for the Social Sciences
Germany