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Classifying multiple ethnic identifications: Methodological effects on child, adolescent, and adult ethnic distributions

Author

Listed:
  • Esther S. Yao

    (University of Auckland)

  • Kane Meissel

    (University of Auckland)

  • Pat Bullen

    (University of Auckland)

  • Polly Atatoa Carr

    (University of Waikato)

  • Terryann Clark

    (University of Auckland)

  • Susan Morton

    (University of Auckland)

Abstract

Background: The burgeoning global multi-ethnic population, in conjunction with the importance of accurate ethnic group counts for research and policy purposes, make classification of multiple ethnic responses a complex but important issue. There are numerous possible classification approaches, differing in ethical implications and ease of statistical application. Objective: This study empirically examines the validity and consistency of three comparatively accessible ethnic classification methods (total response, administrative-prioritisation, and self-prioritisation) in increasingly ethnically diverse age cohorts (adults, adolescents, and children). Methods: We utilised secondary data from two large-scale studies in Aotearoa/New Zealand which asked children (N = 6,149; responded via mother proxy), adolescents (N = 8,464), and adults (N = 11,210) to select (1) all the ethnicities they identified with, and (2) their main ethnicity. The data were coded, then analysed using descriptive statistics and z-tests for proportional differences. Results: The majority of multi-ethnic participants were able to select a main ethnic group when required, but around 20% could not or refused to do so, and there was over 60% discrepancy between self-prioritised ethnicity and administrative-prioritised ethnicity. Differences by age group and ethnic combination were apparent. Comparison of overall ethnic group proportions outputted by the three classification methods revealed within-group variation, particularly where there were higher rates of multi-ethnic identification. Contribution: This study empirically demonstrates that researchers’ choice of ethnic classification method can have a strong influence on ethnic group proportions. Researchers should therefore select the classification method most appropriate for their research question and clearly report the method employed.

Suggested Citation

  • Esther S. Yao & Kane Meissel & Pat Bullen & Polly Atatoa Carr & Terryann Clark & Susan Morton, 2021. "Classifying multiple ethnic identifications: Methodological effects on child, adolescent, and adult ethnic distributions," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(21), pages 481-512.
  • Handle: RePEc:dem:demres:v:44:y:2021:i:21
    DOI: 10.4054/DemRes.2021.44.21
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    References listed on IDEAS

    as
    1. Ann Morning, 2008. "Ethnic Classification in Global Perspective: A Cross-National Survey of the 2000 Census Round," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 27(2), pages 239-272, April.
    2. Anthony Daniel Perez & Charles Hirschman, 2009. "The Changing Racial and Ethnic Composition of the US Population: Emerging American Identities," Population and Development Review, The Population Council, Inc., vol. 35(1), pages 1-51, March.
    3. Carlotta Balestra & Lara Fleischer, 2018. "Diversity statistics in the OECD: How do OECD countries collect data on ethnic, racial and indigenous identity?," OECD Statistics Working Papers 2018/09, OECD Publishing.
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    More about this item

    Keywords

    ethnicity; race/ethnicity; methods; multiple ethnicities; ethnic classification; ethnic measurement;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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