@EdWorkingPaper{ai26-1486,
title = "Hmong but not Asian, Sāmoan but not Pacific Islander: Tracing the ECLS-K Racial Data (Mis)Classification Journey",
author = "Wendy Castillo, Daranee Taychachaiwongse Teng, Kristine Jan Cruz Espinoza",
institution = "Annenberg Institute at Brown University",
number = "1486",
year = "2026",
month = "May",
URL = "http://www.edworkingpapers.com/ai26-1486",
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.},
}