College officials like to say they’re data driven. But without more detailed data on race and ethnicity, they won’t understand their students’ needs as well as they could.
That’s one implication of a new policy brief released on Thursday by the Southeast Asia Resource Action Center and the Institute for Higher Education Policy. Existing postsecondary data systems, it says, lump together Asian American and Pacific Islander (AAPI) students “in ways that mask inequities in outcomes.”
For instance, Southeast Asian Americans — including those from Cambodian, Hmong, Laotian, and Vietnamese backgrounds — are far less likely to have attended college than other Asian Americans. About one-quarter of Southeast Asian American adults did not graduate from high school, compared with 12 percent of all Asian Americans, according to the brief, “Everyone Deserves to Be Seen: Recommendations for Improved Federal Data on Asian Americans and Pacific Islanders (AAPI).”
Combining all AAPI students into one or two subgroups obscures cultural and historical differences that often shape students’ experiences and opportunities, says Anna Byon, author of the brief. Without that crucial context, she writes, policy makers “are essentially flying blind.”
Byon, education-policy manager at the Southeast Asia Resource Action Center, known as Searac, proposes that the education realm “disaggregate” racial and ethnic data by aligning reporting requirements with the categories used by the U.S. Census Bureau. The bureau reports data on at least 25 “distinct, self-identified” AAPI groups, each with what the brief describes as “unique linguistic, cultural, and historical differences.”
The University of California system, which collects data disaggregated by AAPI groups at the point of application, uses the information internally to better meet students’ academic and social needs, according to the brief: “By including a few additional fields in the race/ethnicity section of a student’s online application, institutions can collect data that better reflects the diversity of the AAPI community without dramatically increasing administrative burden.”
In an interview with The Chronicle, Byon shared her views on data equity.
(This interview has been edited for length and clarity.)
Some people might think, “Oh, this is just an issue for data geeks.” What would you tell them?
This isn’t just an issue that impacts data nerds. Every decision that a college makes — from coursework to financial aid to the availability of certain programming, or even whether to continue providing a program or service — is based on student data. Information on race and ethnicity helps dictate decisions made by institutions. As long as that data fails to capture the experiences of the students, then it’s not guiding decisions in a way that serves everybody.
How did we get here? Why aren’t the detailed categories you support more widely used?
In 1997 the Office of Management and Budget created a standard that all federal data had to be disaggregated by the terms we most commonly see [American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, and White; and for ethnicity: Hispanic or Latino, Not Hispanic or Latino].
The OMB never says in the regulations that agencies are limited to those categories. However, almost all federal agencies continue to collect and report data in those minimum categories. My guess is that when it comes to postsecondary data that colleges have to report — to the Integrated Postsecondary Education Data System, for example — they’re just following along with those minimum data categories.
There have been a handful of efforts to disaggregate postsecondary data in the past. None of those have made it very far. But there is a growing recognition of the importance of this issue in recent federal legislation.
You wrote in the brief that without more detailed data, policy makers might “unwittingly reinforce a status quo that perpetuates the marginalization of Asian American and Pacific Islander communities.” For one thing, you’re saying that two AAPI students might have vastly different stories.
The term “Asian American” encompasses an incredible diversity of stories and an incredible diversity of people. I would like to highlight a story about Eva, a high-school student in Minnesota who’s mentioned in our brief. Her parents are refugees who’ve had to fend for themselves and work odd jobs. They really pushed her to work hard and pursue higher education.
She wanted to take prep classes for the ACT, but her family couldn’t afford it. Her scores came back below average, and she was concerned about her higher-ed prospects. She really felt like her story, her back story, was constantly invalidated because of this myth of the model minority — the perception that Asian Americans always do well, that they must always fit into this paradigm of being self-sufficient.
Tell us a little more about the myth of the model minority, and why it matters.
The myth posits that Asian Americans continue to overcome racism and other challenges through hard work and education, and that they are models for how other minority groups can do the same thing. It diminishes the diversity that exists within the Asian American community. And it obscures the ways in which racism and inequities impact Asian Americans.
How might more detailed data help colleges better serve AAPI students?
Students find greater fulfillment and success in their postsecondary endeavors through programs that are specially tailored to their unique circumstances and needs. Having better, more specific data on the demographics of the student population can help colleges create and provide those services. It can also help them identify groups of students who might be struggling in school, and identify the kind of supports that might be most helpful.
To what extent, if at all, did any of your own experiences shape your interest in, or understanding of, this issue?
My commitment to data equity came in part from feeling silenced in my own training. When I pursued graduate studies in education policy, my program did not even once provide an AAPI perspective. Almost all of the research we looked at put AAPIs into an “other” category, if even that. I knew AAPIs had to be in data — I was a living, breathing person after all — so I’m grateful to be working through Searac as one of many voices on this issue.
On a human level, how does it feel to fill out a form and not see a race/ethnicity option that you personally identify with?
There was a young woman named Deijah who shared her story for this brief who identifies as biracial — Khmer and black. In filling out forms and applications where you’re required to check off something for the racial and ethnic category, she’s always checked off the “other” box. Not being able to check off something that is part of someone’s identity and say, “I am an other,” the cumulative effect of that is incredibly harmful to entire communities. Extrapolating that to a policy level, you’ve got hundreds of thousands of people who are this “other” who are not being seen and heard. That’s really heartbreaking.
Let’s say I’m an overwhelmed college leader scrambling to respond to the pandemic. Why should I stop and think about data disaggregation right now?
We know that the entire sector of higher education is going to be absolutely changed by this pandemic. There were already deep inequities being experienced by diverse, vulnerable communities — low-income people, people of color — that are going to be exacerbated by this crisis. A policy change like this can help colleges, researchers, and the public better understand that AAPI communities are more than just this vague group of Asian Americans.
