In June, the Institute for Immigration, Globalization, and Education at the University of California, Los Angeles, with support from the ACT Center for Equity in Learning, released The Racial Heterogeneity Project, which offers a conceptual lens and actionable steps for organizations, institutions, and states to improve data practices and more accurately capture and represent the nation’s racial and ethnic diversity. Learn more about this project and why it’s important for education equity.
Why is racial heterogeneity important?
Racial heterogeneity is the recognition of the vast diversity within racial groups and the disparities that may exist across those smaller sub-categories. For the purpose of the Racial Heterogeneity Project (RHP), racial heterogeneity refers to the diversity across ethnic sub-groups (e.g. Chinese, Vietnamese, Hmong within Asian American category), tribal affiliations (e.g. Aleut, Cherokee, Yaqui within Native American category) and generational status (e.g. native-born Black, first generation immigrant within Black category).
The United States population is changing rapidly. That is a numerical fact—U.S. public schools became majority non-White in 2014, half of the nation’s children will come from a racial or ethnic minority by 2020, and nearly 20 percent of the population will be considered foreign born by 2060. One could even observe these demographic shifts by looking at the students in public school classrooms and across college campuses, or walking through various neighborhoods in major metropolitan cities. It is undeniable that we look differently today than we did a decade ago, and there are no signs suggesting that this trend will decline. Due to these changes, the study of racial heterogeneity becomes consequential to our efforts to identify inequality, address opportunity gaps, and foster educational mobility.
One way through which we can better understand racial heterogeneity is improving how we collect data. The collection of representative data allows us the opportunity to make sense of the many racial and ethnic groups that reside in the U.S. It also opens up the possibility of identifying the challenges different communities face, helping us to better direct attention and resources to those individuals who are the most in need. Conversely, failing to collect data that reflects the great diversity of the population, as is largely practiced today, can lead to the harmful oversight of underserved communities and misinformed policymaking.
Why is this research particularly timely?
The increasing complexity of the nation’s demography is becoming more difficult to track by the day. As racial inequality continues to plague education at every step in the pipeline from primary school grades, to high school graduation, to postsecondary outcomes, more accurate data is required to address the source of these disparities. For example, while 74.1 percent of Taiwanese and 71.1 percent of Asian Indians have earned a bachelor’s degree, only 14.7 percent of Hmong and 12.4 percent of Lao have achieved that same status. Similarly, over a quarter (27 percent) of the Black student population enrolling at the most selective institutions are immigrants or children of immigrants, leaving a large gap in access for native-born Blacks students. Given these revealing data, the need for more representative data practices is urgent. Each academic year that passes without attention to racial heterogeneity represents another cohort of students who are overlooked and slipping through the cracks.
Are there any downfalls to disaggregating data in this way?
It has been suggested that the disaggregation of data may reduce the collective power of racial groups to advocate for shared needs. Data disaggregation has also brought to light concerns regarding the value of such data for informing decision-making. In California, Governor Brown vetoed a bill to collect disaggregated data on the Asian American and Pacific Islander populations to address health and education disparities stating that, “Dividing people into ethnic or other subcategories may yield more information, but not necessarily greater wisdom about what actions should follow.” The research of the RHP renders this argument flawed, as RHP scholars delineate both unseen inequalities facing sub-groups within larger racial groups—Asian American, Black, Latino, Native American, and Pacific Islander—and recommendations, or actions, that should follow to mitigate such barriers. It is precisely through disaggregated data that actions in policy and practice can be most informed.
Collective advocacy is only as powerful, and as productive, as the ability of the group to truly understand their collective challenges. That understanding is premised on the fact that not only the challenges of individuals for whom there is a platform to demand change are voiced, but that the barriers of all individuals are represented. In this way, disaggregating data offers the most accurate approach to identifying where advocacy efforts should be driven.
What are next steps to help advance this important work? First, the discussion about racial heterogeneity and data disaggregation must be broadened. Although the call for disaggregated data is well known within particular racial groups and among advocacy organizations, there is a need to raise awareness about the significance of this work and demand for change in data collection practices. This can be achieved by using disaggregated data that already exists or pushing for the collection of disaggregated data with tools such as the RHP report, or the other scholarly work of RHP scholars. Second, in pursuing changes in data practices, keep in mind that there are effective models for advocacy, collection, and utilization that may be used as a foundation for future action (see RHP report conclusion and implications). Finally, as disaggregated data is collected, there must be a firm commitment to using the data in a targeted manner—identifying unseen barriers and strategizing appropriate actions in response. In so doing, we can begin to unravel the unseen disadvantage that is hidden within groups and more tangibly address social inequality.
Dr. Bach Mai Dolly Nguyen is a research associate for the Institute for Immigration, Globalization, and Education (IGE) at the University of California, Los Angeles. She is the Project Manager for the Racial Heterogeneity Project (RHP) and lead author of the ACT-funded report, “The Racial Heterogeneity Project: Implications for Educational Research, Practice, and Policy”. She will transition to Lewis & Clark College as Assistant Professor of Education in fall of 2017.