Gifted Identification and Services for Asian Americans

Mun, Rachel U.; Yeung, Glorry

doi:10.4324/9781003265412-14

Cited by 1 publication

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“…To emphasize, the Asian American label represents a heterogeneous population from diverse cultural backgrounds with distinct languages, customs, religious, and philosophical differences (Kitano & DiJiosia, 2002; Lee & Zhou, 2015). This diversity continues to be swept under the model minority rhetoric (Mun & Yeung, 2022; Museus & Kiang, 2009). The body of research offers scant evidence of effort to distinguish subgroups within the population of their studies.…”

Section: Data Aggregationmentioning

confidence: 99%

A Renewed Call for Disaggregation of Racial and Ethnic Data: Advancing Scientific Rigor and Equity in Gifted and Talented Education Research

Yeung

Mun

2022

Journal for the Education of the Gifted

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Researchers in gifted and talented education (GATE) have increasingly taken on the role of advocating equity and access for minoritized populations. However, subgroups of racially and ethnically diverse students are rarely disaggregated from monolithic racial and ethnic categories. Studies on academic achievement of Asian American and White students, based on aggregated data, risk straying from scientific rigor and may lead to conclusions that further contribute to the masking of inequities and disparities of nested subgroups. The roots of this phenomenon can be traced to the practice of racial/ethnic data aggregation from the national level on down. We contend that fair and equitable access should be afforded to all students and call for the normalization of racial/ethnic data disaggregation in GATE research to increase scientific rigor in our scholarship and unmask intra-ethnic inequities.

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Section: Data Aggregationmentioning

confidence: 99%