Population Research Discovery Seminars
Data Equity and Identity: A Qualitative Analysis of Public Feedback on Asian Racial Categories
Ninez Ponce, Professor and Endowed Chair of Health Policy and Management & Director of UCLA Center for Health Policy Research, University of California Los Angeles
Parrington Hall Room 360
To Join By Zoom: Register HERE
Follow this link to sign up for a 1:1 meeting with Dr. Ponce during their visit on April 24th
04/24/2026
12:30-1:30 PM PT
360 Parrington Hall
Co-Sponsor(s):
Proposed changes to the federal racial and ethnic classification system in the United States offer a unique opportunity to understand how the general public thinks about Asian American identity and how Asian populations should be classified in federal data. The Improving Asian Classification Typologies (ImpACT) project analyzes public comments submitted in response to two Federal Register Notices: (1) the OMB’s proposed revisions to Statistical Policy Directive 15, 2023, and (2) the U.S. Census Bureau’s draft race and ethnicity coding guidelines, 2024.
Using a mixed deductive-inductive coding framework, six coders working in pairs analyzed comments to develop key themes. Overall, we found the boundaries of the Asian category are contested in the comments, particularly at the intersections with the Middle Eastern and North African, White, and Native Hawaiian and Pacific Islander categories. The geographic subgroups used to define Asian communities, including East Asian, Southeast Asian, and South Asian, are similarly disputed, particularly for communities with identities that traverse regional boundaries. We also found disagreement over whether Census’ pre-defined regional categories should be retained or eliminated, with some commenters arguing that standardized groupings are essential for longitudinal research and reporting, while others contending that pre-defined categories introduce misclassification and can undermine community self-identification. Additional themes examine debates over terminology, data collection practices, and how classification decisions shape community visibility and health equity.