Politics, News

The “model minority” myth holds the needs of the diverse Asian American community hostage

Don't be fooled by the data you see these days. We aren't a monolith.

The New York State Assembly recently passed a bill, sponsored by Assemblywoman Yuh-Line Niou, that would require certain New York state entities to collect and publish data on Asian Americans, Native Hawaiians, and Pacific Islanders (AANHPI).

This legislation is once again inspiring the national conversation on the need for data aggregation in the AANHPI community. Data disaggregation breaks down information about different populations into smaller subpopulations.

For a community as diverse and expansive as Asian Americans, Native Hawaiians, and Pacific Islanders, this breakdown is crucial.

[bctt tweet=”The AANHPI community is no monolith.” username=”wearethetempest”]

The AANHPI community is no monolith.

There are nearly fifty ethnic groups speaking more than a hundred languages within the AANHPI community. The Asian American community alone is considered the most rapidly growing population in the United States.

Although the New York Senate has yet to take action on the data disaggregation bill, if passed, it will work to expose disparities among AANHPIs in areas such as education, poverty, language access and health care that often fly under the radar within this diverse group.

Why are these disparities so invisible?

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The term ‘model minority’ was coined in 1966 by a New York Times Magazine article entitled “Success, Japanese-American Style.” In the article, sociologist William Petersen attributed the perceived success of Japanese Americans 20 years after World War II internment to “cultural values, strong work ethic, family structure, and genetics.”

The model minority myth perpetuated the idea that Asian Americans are “good, educated, hardworking people” amid the adversities of being a racial minority and didn’t need help. It was purposefully used to create a dichotomy between Asian and Black Americans, painting Asian Americans as the “good minorities” versus Black Americans, who have a complex history of being disenfranchised and antagonized in this U.S.

[bctt tweet=”This myth is harmful because it homogenizes a diverse and expansive community.” username=”wearethetempest”]

Don’t be fooled: While many East and South Asians have historically shown success in educational and economic achievement, this myth was created solely as a tool to harm, even against Asian Americans.

It homogenizes a diverse and expansive community, excluding those who do not fit its stereotype, especially Southeast Asian Americans, Pacific Islanders and Native Hawaiians.

People often fail to see the unique needs of the Hmong, Cambodian, Vietnamese and Laotian community, who disproportionately experience a higher high school dropout rate and prevalence of poverty, as well as a lack of access to healthcare.

Because of the model minority myth, lawmakers and key stakeholders don’t see AANHPI folks as marginalized and therefore don’t need help. Data disaggregation is crucial to dismantling harmful stereotypes about Asian Americans as a whole by breaking down data on major ethnic groups, disability, language status, and poverty.

How successful has data disaggregation been in the U.S.?

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The push for data disaggregation for Asian Americans, Native Hawaiians, and Pacific Islanders has varying levels of success across the nation.

In California, the AHEAD Act (AB 1726) was passed and signed into law by Gov. Jerry Brown, requiring public health agencies to expand and report disaggregated data for AANHPI groups. The University of California and the California State University systems also committed to expanding data disaggregation and reporting for higher education institutions initially included under the measure.

[bctt tweet=”Data disaggregation is crucial to dismantling harmful stereotypes about Asian Americans.” username=”wearethetempest”]

Data disaggregation measures were also passed in the states of Washington and Minnesota, but on a national scale, broader recognition of the value of data disaggregation still has a long way to go.

Versions of the current New York State Assembly Bill on data disaggregation have been introduced before. Assemblyman Ron Kim sponsored a bill during the 2015-2016 legislative session that met the same fate as Assemblywoman Niou’s bill: Although it passed the Assembly, no action was taken in the Senate.

In 2015, a national measure to disaggregate and report AANHPI data was introduced as a provision to the Every Student Succeeds Act (ESSA).

Although it failed to pass, congresspeople included a section that offers technical assistance from the U.S. Department of Education to states that want to collect disaggregated AANHPI student data.

[bctt tweet=”Broader recognition of data disaggregation still has a long way to go.” username=”wearethetempest”]

Policymakers and advocacy groups across the nation are fighting for data disaggregation at public institutions and agencies to ensure visibility and justice for AANHPI communities.

Data disaggregation is a civil rights issue for the AANHPI community and holding institutions accountable for providing data about them is crucial to understanding its unique differences, needs, and experiences.