Classifying Ethnicity in Multi-Ethnic Contexts : Implications of Methodological Decisions on Quantitative Research

Abstract

Ethnicity is an important variable in health and social science research, but classifying ethnicity is complex because of the construct’s fluidity and multiplicity. There are several possible ethnic classification methods, each with strengths and limitations. Existing literature suggests that researchers’ decisions on ethnic classification method can influence research findings. However, there is little empirical research on how these classification methods affect quantitative research in samples with higher multi-ethnic prevalence (e.g., >10%). Situated within a critical quantitative paradigm, the current thesis addresses this gap by utilising largescale datasets from increasingly multi-ethnic cohorts (adults, adolescents, and children) in Aotearoa New Zealand to examine the effects of ethnic classification method on reported ethnic group size, demographic composition, and substantive outcomes. The corresponding three studies found that, first, ethnic classification method can substantially impact outputted ethnic group sizes, especially when there are higher rates of multi-ethnic identification (e.g., among children and adolescents). Second, there was a high rate of discrepancy between the two popular methods of administrative-prioritisation and selfprioritisation in each age cohort (≥60%). These discrepancies were systematically associated with contextual characteristics such as neighbourhood ethnic composition and socioeconomic deprivation. Third, using adolescent mental health outcomes as a case study, it was found that ethnic classification method can affect substantive outcomes, both within nominal ethnic groups (by an effect size of up to d = 0.12), and between nominal ethnic groups (by an effect size of up to d = 0.25). Together, the results indicate that researchers’ choice of ethnic classification method affects who is included or excluded from ethnic groups, the demographic composition of these ethnic groups, and conclusions about the extent of ethnic disparities. This, in turn, influences knowledge construction, practice, and policy. Given that each ethnic classification method has strengths and limitations, the studies in this thesis highlight the importance for researchers to critically and transparently select the most appropriate ethnic classification method for their research question and context. The power of the researcher, combined with the subjectivity of ethnicity measurement, also emphasises the need for researchers to be critical and reflexive throughout the wider research process.