Disaggregating data on Asian Pacific Islanders reveals hidden stories of disparity

Chetanya Robinson December 7, 2015 0
On API Legislative Day 2015, members of SEA³eD gather in support of a bill on data disaggregation sponsored by Washington State Representative Sharon Santos. The bill has not passed in the Washington state legislature, though it led to efforts toward data disaggregation on the city level. • Photo courtesy of SEA³eD

On API Legislative Day 2015, members of SEA³eD gather in support of a bill on data disaggregation sponsored by Washington State Representative Sharon Santos. The bill has not passed in the Washington state legislature, though it led to efforts toward data disaggregation on the city level. • Photo courtesy of SEA³eD

When he graduated from high school, Ay Saechao felt like a lot of students—proud of his accomplishment. But he was also troubled.

Saechao’s parents were from the Mienh ethnic minority and witnessed the CIA’s Secret War in Laos, before joining tens of thousands of their fellow people to settle on the West Coast of the United States. Saechao grew up in an apartment complex in Northeast Portland home to a community of more than 500 southeast Asians, many of them refugees.

When high school ended, many of Saechao’s Mienh peers didn’t graduate with him.

“I just remember walking and grabbing that diploma and realizing that a lot of people I grew up with—they’re not walking,” he said. “They either had already dropped out or they were struggling to graduate.”

As he started college, Saechao couldn’t shake lingering questions about his peers’ lack of success in school.

“I didn’t have any answers, I didn’t know really what to think about it, I just had questions,” he said.

In college and graduate school, Saechao studied the Southeast Asian educational gap, and created a research paper and survey about educational issues among the Mienh. After earning a master’s degree in education from the University of Washington, he co-founded SEA³eD (Southeast Asian American Access in Education Coalition), a grassroots organization.

Among other things, SEA³eD advocates for disaggregation of data on Asian Pacific Islander Americans in Washington.

Ay Saechao speaking at South Seattle College Unite: Southeast Asian Education Summit, 2014. • Photo courtesy of SEA³eD

Ay Saechao speaking at South Seattle College Unite: Southeast Asian Education Summit, 2014. • Photo courtesy of SEA³eD

Glancing at the data, it might be easy to assume that Asian Pacific Islanders in the state face few major hurdles in education, income, health care, or housing compared to other groups. According to aggregated data, APIs lead in educational attainment, for example: according to data from the American Community Survey, 47 percent of Asian Americans in Seattle possess at least a bachelor’s degree, a higher percentage than for whites, African Americans, and Latinos.

But the way data is collected by the city and state can be misleading. While Asian Pacific Islanders in Washington comprise 25 countries of origin, they’re often treated as one category. Disaggregating the data—holding a magnifying glass to the numbers, zooming in on the sub-group level—can reveal large disparities. It can reveal entire communities who need better targeted services.

Asian Americans Advancing Justice, a national nonprofit based in Washington D.C., releases an annual report on APIs in the West, including Seattle. The data is drawn from a variety of government agencies and surveys, and much of it is disaggregated. As a result, disparities in education, healthcare, and housing among Asian Pacific Islander subgroups stick out. For example: while 71 percent of Taiwanese in Seattle possess a college degree, only 9 percent of Guamians do. While 60 percent of Asians in Seattle own their homes, only 19 percent of Mongolians do.

The Asian Pacific Islander community has long been calling for this disaggregation, but the issue has only recently gained wider traction. In late September 2015, Seattle became the first city to put data disaggregation into law after passing a City Council resolution to create a task force to advise on disaggregating city data.

Seattle mayor Ed Murray signs a resolution on data disaggregation, making Seattle the first city in the nation to pass such legislation. The resolution was sponsored by Councilmember John Okamoto (immediately right of Murray) and co-sponsored by Councilmembers Bruce Harrel (right of Okamoto) and Tim Burgess. • Photo courtesy of John Okamoto

Seattle mayor Ed Murray signs a resolution on data disaggregation, making Seattle the first city in the nation to pass such legislation. The resolution was sponsored by Councilmember John Okamoto (immediately right of Murray) and co-sponsored by Councilmembers Bruce Harrel (right of Okamoto) and Tim Burgess. • Photo courtesy of John Okamoto

This resolution, from Councilmember John Okamoto and co-sponsored by Councilmembers Bruce Harrell and Tim Burgess, was inspired by a Washington House of Representatives bill intended to mend disparities in education, itself sponsored by Washington State Representative Sharon Tomiko Santos. Santos’s bill hasn’t yet passed.

According to Okamoto, the purpose of his resolution was to get a handle on how Seattle collects and uses data, and how this can be improved. Though the city depends on demographic data to allocate resources and come up with policies, this data is messily organized. According to Okamoto’s chief of staff Audrey Buehring, different departments collect different kinds of data from different sources, aggregated and disaggregated in various ways.

Often, according to Burgess, the city doesn’t need more data—it just needs to take a proper look at it.

“We have a lot of data—it’s whether or not we are analyzing the data thoroughly,” said Burgess. “There’s an obligation on the government side to make sure that we’re using the data, to make sure that we are outcome-driven.”

Data disaggregation could serve many other communities besides APIs, Okamoto and Burgess agree. Seattle mayor Ed Murray points to East Africans in Seattle as an example of a group who would benefit from disaggregation by language and country of origin. The process of disaggregation, said Murray, is ongoing.

“We have the initial results where we’ve started to break out the Asian American community,” Murray said. “And we need to do this not just for Asian Americans, we need to do it for all groups.”

For APIs, disaggregating data challenges the stereotype that they are a “model minority”—upwardly mobile, self-sufficient and highly educated.

Daniele Meñez, director of the Pacific Islander Student Commission at the UW, finds that people are often unaware of the struggles many Pacific Islander students face. According to census data, the graduation rate for Pacific Islanders who entered the UW in 2008 was 76 percent, among the lowest of any ethnic group. In her experience, Pacific Islanders are often lumped in with Asians as a model minority.

Meñez said: “I have a lot of friends who are white, or who are not people of color, and they always ask me like, ‘Hey can you help me with my math homework? And math is my worst subject—I’m terrible at math. And they’re like, ‘Oh but you’re Asian, or Pacific Islander I guess, shouldn’t you be really good at math?”

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According to Diane Narasaki, executive director of Asian Counseling and Referral Service (ACRS), the model minority stereotype operates not just on a personal but an institutional level. It can seep into the way policy is made.

“Our community has suffered from lack of prioritization from policymakers, legislators, and funders in our data driven society because of the lack of adequate disaggregated data,” she said in an email. “Without [disaggregated data], the model minority stereotype can play into decision-making.”

The sheer diversity of the API community—including diversity within ethnic groups —makes any generalizations about APIs pointless, said Connie So, a lecturer in the UW’s American Ethnic Studies department.

“What is a median of an Asian? It’s like talking about the median of two thirds to three quarters of the world,” she said. “Really there is no such thing as a model minority.”

There are differences among Chinese groups of different national origins, said So, among Indians who are Sikh, Hindu, or Muslim, among Pacific Islanders who are Melanesians, Micronesians and Polynesians. And these are just a few examples. “The more disaggregated things are the better,” she said.

The API community in Seattle is made up of over half a million people, half of them foreign born. It’s a group with a multiplicity of of national origins, religions, languages, and huge differences in immigration status, English proficiency, reason for immigration and more. All these factors and variables, said So, can contribute to the disparities—or success stories—among the different groups.

“You come over as an international student, versus coming over as a refugee, versus coming over because your relatives sponsored you—you’re probably going to have pretty different experiences,” she said.

When it comes to Southeast Asian struggles in education, Saechao points to the fact that most Southeast Asians came to the United States fleeing government oppression, persecution, war, or genocide, and some were already marginalized ethnic minorities within their countries.

“They came to the U.S. with numerous traumas—traumas that still last today that are intergenerational,” Saechao said. “Many do not have access, due to the persecution or lack of resources to quality education back in their homeland.”

Many children of these immigrants were the first in their families to attend college. Add to this the stresses of navigating a dual identity as American and a member of their ethnic group.

“You have these maybe contrasting, or sometimes even conflicting, cultural expectations and roles that these students who are in our school system have to balance and maneuver and master,” said Saechao. “And with that you have educators who are not trained and don’t have the skillset to support this community.”

Saechao thinks the model minority stereotype contributes to a lack of targeted services for Southeast Asians in education.

Seattle’s latest resolution on data disaggregation will affect nearly a dozen departments across the city. The newly created demographic task force will release its recommendations in July. In the meantime, there’s more work to be done.

According to Buehring, one reason data disaggregation has been slow to gain traction—despite being called for by the community for years—is the cost of overhauling the data system of the city. Just to get started on the process of implementing the resolution’s recommendations, the city will have to raise $250,000.

But in her view, getting the resolution passed was an important step forward.

“I think getting to this step has been monumental, just to get government to actually agree, because it’s not an easy process to overhaul your data system,” she said.

Okamoto thinks that with more data disaggregation, new findings will come to light.

“I think there’s just a whole host of areas that we will find new things that will be uncovered,” he said. This will include, he believes, disparities in health, senior care, housing availability, and access.

According to Burgess, real progress in addressing the disparities highlighted by disaggregation goes beyond passing one resolution.

“Until those of us in government value and appreciate the importance of this kind of data analysis and focus on outcomes, not much will change,” said Burgess. “It’s about political will and it’s about … the rigor of wanting to do the analysis, to ask the questions, to challenge the status quo.”

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