The Data Quality Movement for the Asian American and Pacific Islander Community: An Unresolved Civil Rights Issue (original) (raw)
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This article presents a case study of the 2006-2007 Asian American and Pacific Islander (AAPI) student-led Count Me In! (CMI) campaign. This successful campaign convinced the University of California (UC) to account for 23 AAPI ethnic identities in its data system. Celebrated as a victory for AAPI interests in discourses over racial equity in education, which are often defined by a Black- white racial paradigm, CMI should also be remembered as originating out of efforts to demonstrate AAPI solidarity with Black students and to counter racial wedge politics. In the evolution of the CMI campaign, efforts for cross-racial solidarity soon faded as the desire for institutional validation of AAPI educational struggles was centered. Our case study analysis, guided by sociological frameworks of racism, revealed key limitations in the CMI campaign related to the intricate relations between people of color advocating for racial justice. We conclude with cautions for research and campaigns for...
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What would data disaggregation for Asian Americans look like, and why does it matter? Disaggregating the broad category of "Asian" or "Asian American" into subgroups which take national or ethnic origin into account can help to illuminate the disparities present between different Asian American communities. This would allow for a more accurate assessment of need and thus equitable resource allocation for historically disadvantaged groups, for instance Southeast Asian refugee populations such as the Lao, Cambodian, Hmong, and Vietnamese. In this paper, I will discuss the concept of Asian American panethnicity and how it negatively impacts marginalized subgroups by perpetuating the "model minority" myth, masking the disparities revealed in disaggregated data on educational attainment, for example. I will then use Rhode Island's 2016 "All Students Count Act" as a case study to explore the debate surrounding this issue, arguing that data disaggregation to substantiate the need for affirmative action should not be considered race-based discrimination, but a race-conscious practice that can support and facilitate success in more disadvantaged Asian American communities.
Asian American and Pacific Islander Students: Equity and the Achievement Gap
The authors studied more than 1 million Asian American and Pacific Islander (AAPI) and White seventh graders in a statewide California testing program between 2003 and 2008, examining their reading and math achievement. AAPI student performance is often reported as an aggregate in discussions of the success of schoolchildren and issues of racial and ethnic achievement gaps. The authors disaggregated the performance of 13 AAPI subgroups and found significant achievement gaps between White Americans and their AAPI peers in reading and math. The data refuted the premise of the model minority myth. The evidence indicated that AAPI students are diverse in their achievements and demonstrate a continuum of academic performance.
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This report was made possible through generous funding from the ACT Center for Equity in Learning. Central to the collaboration between UCLA's Institute for Immigration, Globalization, and Education (IGE) and the ACT Center for Equity in Learning is the commitment to scholarship that examines racial inequity in education and offers research-based recommendations that address structural barriers to improve educational outcomes. In this report, we were intentional in our exploration of racial heterogeneity across racial groups, in order to shed light on the importance of data practices that represent the wide diversity of America's rapidly changing demography.