Ethnic identification from pre-birth to early adolescence: longitudinal patterns and methodological considerations

Esther S. Yao (), Polly Atatoa Carr (), Kane Meissel (), Pat Bullen (), Roshini Peiris-John (), Sam Manuela () and Terryann C. Clark ()
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Esther S. Yao: University of Auckland
Polly Atatoa Carr: University of Waikato
Kane Meissel: University of Auckland
Pat Bullen: University of Auckland
Roshini Peiris-John: University of Auckland
Sam Manuela: University of Auckland
Terryann C. Clark: University of Auckland

Journal of Population Research, 2025, vol. 42, issue 3, No 18, 25 pages

Abstract: Abstract Ethnicity is a dynamic construct that can be expressed differently depending on the respondent, time point, context, and measurement method, thus resulting in intra-individual ethnic mobility. However, little is known about how ethnic mobility varies by ethnic classification method, despite cross-sectional evidence showing the impact of ethnic classification decisions on research. This study examines the stability and change in ethnic identification from pre-birth to early adolescence using four ethnic classification. Total response grouping, single/combination grouping, administrative-prioritisation, and self-prioritisation. We utilised five data waves from the Growing Up in New Zealand birth cohort study (antenatal, 9-months, 4.5-years, 8-years, 12-years; N = 3,625). Longitudinal changes in ethnic identification were examined using alluvial plots and descriptive statistics (e.g., frequencies, number of distinct states, common sequences, transition rates). Results showed that ethnic mobility was noticeable over time and across classification methods. Depending on the ethnic classification method, the proportion of participants who remained in a single ethnic grouping across five data waves ranged from 39% (single/combination grouping) to 83% (total response grouping). Stability levels also varied by ethnic groupings within each classification method. Given the dynamic and complex nature of ethnicity, researchers should treat ethnicity as a time-varying variable, collect ethnicity data at every data wave, ensure ethnic classification decisions are made with care, and consider the implications of these decisions.

Keywords: Ethnicity; Race; Multiple ethnicities; Ethnic mobility; Ethnic classification; Longitudinal research; Quantitative methods (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s12546-025-09392-z

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