Asian-Americans soar in pop but can’t escape pigeonhole
CHICAGO — It has been nearly a year since the Pew Research Center reported that Asian immigrants are elbowing Latin Americans aside and are projected to become the largest immigrant group by 2055. Policy analysis on the implications of this shift is beginning to trickle out.
There are two important issues that Asian-Americans have been trying to call attention to for years: The harm of the “model minority” myth and the invisibility of various Asian subgroups — and their unique needs — when they are all grouped together as an “Asian community.”
Gerard Robinson, an American Enterprise Institute fellow, recently highlighted how the stereotype of Asian students as academic superstars is not only indeed a myth. It also hides real achievement issues for at-risk populations.
This isn’t to say that many Asian students aren’t high achievers. As Robinson wrote in “A Tale of Two Disparity Gaps” on the blog of the Brookings Institution, “White students’ math and writing SAT scores were 64 and 18 points lower than Asians’ in 2015. In fact, the combined SAT score of 1654 for Asians in 2015 saw a 54-point increase since 2006. Whites and others saw a decline during the same time.”
The problem is that not all Asian students are alike.
It seems preposterous to even have to articulate this, but much like the so-called Latino community, the U.S. Asian population is wildly diverse in terms of country of origin, immigration status, education level, English-language proficiency and socioeconomic status.
Despite the folklore of the Tiger Mom overscheduling her cubs into success, Robinson notes that “many Asian students struggle in English-language learning, reading and math classes, including some from higher-income households. In regard to an intra-Asian dynamic, Hmong, Tongan and Vietnamese populations, for example, are among the most poorly educated communities in the United States — not just within the Asian community. In fact, some black and Hispanic students outperform these populations as well as some higher-achieving Asian students.”
Erroneously assuming that certain groups are high achievers inevitably results in other communities of need getting the short shrift on interventions and supports.
For instance, when policymakers look at the white-minority achievement gap, poor whites who live in the same type of poverty that stunts the academic growth of poor black and Hispanic students tend to get lost in the shuffle.
The blind spot is huge. According to Census figures, there is a 10 percent poverty rate among white non-Hispanics. In raw numbers of people, impoverished whites are approximately twice the size of African-Americans in poverty, the group with the highest rate of economic hardship (25.8 percent).
Similarly, when Asians are seen only as a homogenous group of academic high achievers — and not as a diverse population that includes immigrants from impoverished countries and refugees from war-torn regions — those who need support are overlooked. And because Asian students might not be concentrated in highly segregated or impoverished communities and school districts, they’re unlikely to be targeted for help the way Hispanic and black students are.
For Asians of all ages, the remedy lies in demographic data disaggregation, a clunky term that has not captured the general population’s imagination but is seen as an effective way to change the narrative of the prototypical Asian.
In California, where the Asian-American population grew by 34 percent between 2000 and 2010, Asian-American, Native Hawaiian and Pacific Islander civil rights organizations are advancing a bill that would require California’s public institutions of higher education and public health to collect, analyze and report data for up to 42 subgroups of those three broad categories.
Civil rights groups there know that the disparities among national-origin groups are stark. For example, without more nuanced collection and reporting of subgroup data, differences such as those between older adult Chinese and Vietnamese elders (who have the most chronic health conditions) and Japanese elders (who have the least) may potentially mask the reality that Japanese women are nearly twice as likely to die of cancer as Asian Indian women.
Correspondingly, adding more racial subcategories on nationwide standardized tests and breaking out performance data by subgroup could bring to light the diversity of the young Asian population’s academic successes and struggles.
Ultimately, fully understanding the fastest-growing racial population in the country isn’t some insurmountable dream. It’s not rocket science, but it does require a societal will to choose to see this collective of Asian ethnic groups as diverse and multifaceted, rather than as homogenous and monolithic.
Esther Cepeda’s email address is firstname.lastname@example.org. Follow her on Twitter, @estherjcepeda.
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