Session: Disaggregating Racial-Ethnic Classification Systems to Improve Data Equity (Sponsored by The University of Utah) (Society for Social Work and Research 27th Annual Conference - Social Work Science and Complex Problems: Battling Inequities + Building Solutions)

All in-person and virtual presentations are in Mountain Standard Time Zone (MST).

SSWR 2023 Poster Gallery: as a registered in-person and virtual attendee, you have access to the virtual Poster Gallery which includes only the posters that elected to present virtually. The rest of the posters are presented in-person in the Poster/Exhibit Hall located in Phoenix A/B, 3rd floor. The access to the Poster Gallery will be available via the virtual conference platform the week of January 9. You will receive an email with instructions how to access the virtual conference platform.

SSRPCB-6 Disaggregating Racial-Ethnic Classification Systems to Improve Data Equity (Sponsored by The University of Utah)

Thursday, January 12, 2023: 10:15 AM-12:15 PM
Camelback B, 2nd Level (Sheraton Phoenix Downtown)
Tara Becker, PhD, University of California, Los Angeles
The most commonly used classification systems to code race-ethnicity obscure the wide variation in racial-ethnic experiences within these broad categories. This workshop will provide attendees with a more detailed understanding of the impact of data collection, coding, and tabulation on efforts to disaggregate racial-ethnic data into more granular categories in order to provide greater insight into the diversity within these groups. Specifically, it will provide an overview of the ways in which federal data collection guidelines influence the collection and weighting of racial-ethnic data in the United States, methods that have been used to expand upon these guidelines to collect and tabulate more granular data, when such expansions may be warranted, and the effects of data collection methodology on the representativeness of data from small racial-ethnic populations. In addition to discussing how, when, and why one should consider disaggregating racial-ethnic data, it will consider—on a conceptual, rather than statistical level—the ways in which methodological decisions, such as the language(s) in which a survey is administered, the method(s) used to oversample racial-ethnic groups, and weighting decisions can affect the generalizability of statistical estimates derived from this data and influence what we know about more granular racial-ethnic populations.
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