Hmong American PhD student rejected for prestigious fellowship for not being in ‘underrepresented’ group
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A Hmong American Ph.D. candidate studying neuroscience at the University of Wisconsin-Madison was refused a fellowship after it was determined that she was not from an “underrepresented” group because she’s Asian American.
“Model minority” myth: In a Twitter thread, doctoral student Kao Lee Yang said she was nominated for the prestigious Howard Hughes Medical Institute’s (HHMI) Gilliam Fellowship but was told by a committee that she didn’t fit its “Racial/Ethnic Underrepresentation” criteria.
“We are not a monolithic group,” she said. “While some Asian Americans are academically successful, others like the Hmong, are underrepresented in STEM and academia in general.”
Yang asked the fellowship committee and others in the scientific community to name a Hmong American woman neuroscientist: “I would love to connect with her if she is out there.”
“I am an example of the consequences resulting from the continued practice of grouping people with East /Southeast/South Asian heritages underneath the ‘Asian American’ umbrella,” she added.
Yang went on to explain how the “model minority” myth hurts Asians: “But studies making those claims are looking at aggregated data and are treating Asian Americans as a monolithic group.”
A letter to #AcademicTwitter: I am a Hmong American neuroscience PhD student who was recently nominated by my institution for the #HHMI Gilliam Fellowship. Today I was told by HHMI that I do not fit their eligibility criteria for "Racial/Ethnic Underrepresentation." 1/12
— Kao Lee Yang (@KaoLeeYang1) October 27, 2021
Underrepresentation in science: Under its eligibility criteria, HHMI defined “excluded groups to be persons who identify as Black or African American, Latinx or Hispanic American, American Indian, Native Hawaiian, Alaska Native, and from groups indigenous to the Pacific Island territories of the United States.”
But it does acknowledge that underrepresentation varies “from setting to setting.”
Yang pointed out a couple of ways fellowships like HHMI can do better. First, “Disaggregate Asian American data in studies.” Second, fellowships should broaden “perspectives on what it means to be an ethnic/racial minority who is underrepresented in science and how to support underrepresented students.”
#AcademicTwitter: Yang has received an outpouring of support from fellow scientists and academics since she first posted her thread on Oct. 27.
I think this is bc the definition of being underrepresented is due to severe exclusion &/or oppression in the US. For instance Black & Indigenous people have been oppressed & most affected in this country for over 400 years. We do need disaggregated data for African, Asian...1/2
— Mélise Marie (@Meliseymo) October 27, 2021
Feel free to PM me—there’s many of us in @AAAStudies who have been arguing to disaggregate data and recognize the ethnic-Asian communities that are under-represented in STEM. I’d be happy to write to this founder to help educate them on these issues bc Asian Am ppl are diverse
— Jennifer Ho (she/her/hers) (@DrJenHo) October 27, 2021
I’m so sorry this happened to you. There are major disparities b/t East & SE Asian groups & by categorizing us as this monolithic group, it invalidates those differences while still measuring us all with the same 📏
— Laurie Chin, M.A. (she/her) (@auroralaureaIis) October 27, 2021
The Hmong experience in America is completely different than other Asian experiences. The majority was brought to America due to war and for refuge. We did not originally seek opportunity like many other Asian folks did. Our people has lost alot through assimilation as well.
— Shengy💜 (@seevyeeg) October 28, 2021
Everyone bemoaning the apprent decline of meritocracy should realize that Kao isn’t saying she should get the fellowship just for being Hmong. All she’s saying is that she should have a chance to compete for a fellowship designed to benefit URMs, since Hmong are URMs.
— Abhijnan Chattopadhyay (@abhijnan) October 28, 2021
Featured Image via Howard Hughes Medical Institute (left), @KaoLeeYang1 (right)
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