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Hmong but Not Asian, Sāmoan but Not Pacific Islander: Tracing the ECLS-K Racial Data (Mis)Classification Journey. EdWorkingPaper No. 26-1486

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Bibliographic Details
Title: Hmong but Not Asian, Sāmoan but Not Pacific Islander: Tracing the ECLS-K Racial Data (Mis)Classification Journey. EdWorkingPaper No. 26-1486
Language: English
Authors: Wendy Castillo, Daranee Taychachaiwongse Teng, Kristine Jan Cruz Espinoza, Annenberg Institute for School Reform at Brown University
Source: Annenberg Institute for School Reform at Brown University. 2026.
Availability: Annenberg Institute for School Reform at Brown University. Brown University Box 1985, Providence, RI 02912. Tel: 401-863-7990; Fax: 401-863-1290; e-mail: annenberg@brown.edu; Web site: https://annenberg.brown.edu/
Peer Reviewed: N
Page Count: 49
Publication Date: 2026
Sponsoring Agency: National Center for Education Statistics (NCES) (ED/IES)
Document Type: Reports - Research
Descriptors: Children, Longitudinal Studies, Surveys, Race, Racial Identification, Ethnicity, Asian American Students, Hawaiians, Pacific Islanders, Classification, Educational Practices, Misconceptions, Critical Race Theory, Praxis
Assessment and Survey Identifiers: Early Childhood Longitudinal Survey
Abstract: Race is a socially and politically charged concept that remains contested in the United States. We examine racial data (mis)classification in the Early Childhood Longitudinal Studies (ECLS-K) dataset. Centering the racial data journey of Asian American, Native Hawaiian, and Pacific Islander (AA&NHPI) students, we find two types of racial data (mis)classification: (1) racial reformation related to the reconfiguration of parent/caregiver-reported racial data and (2) "categorical friction" when ethnicity was parent/caregiver-reported and race was not. Educational data practices and datasets like ECLS-K play a role in obscuring differentiated educational outcomes by operationalizing the myth that AA&NHPIs are a monolith. We offer recommendations for addressing racial data (mis)classification and engaging a critical race research praxis.
Abstractor: As Provided
IES Funded: Yes
Entry Date: 2026
Accession Number: ED681898
Database: ERIC
Description
Abstract:Race is a socially and politically charged concept that remains contested in the United States. We examine racial data (mis)classification in the Early Childhood Longitudinal Studies (ECLS-K) dataset. Centering the racial data journey of Asian American, Native Hawaiian, and Pacific Islander (AA&NHPI) students, we find two types of racial data (mis)classification: (1) racial reformation related to the reconfiguration of parent/caregiver-reported racial data and (2) "categorical friction" when ethnicity was parent/caregiver-reported and race was not. Educational data practices and datasets like ECLS-K play a role in obscuring differentiated educational outcomes by operationalizing the myth that AA&NHPIs are a monolith. We offer recommendations for addressing racial data (mis)classification and engaging a critical race research praxis.