Shiao, Jiannbin Lee (2019). Mapping Racial/Ethnic Multiplicity and Inconsistency in Add Health. American Sociological Association 114th Annual Meeting.
New York, NY.
Research on racial identities has expanded from using personal race data as indicators of group salience, e.g. the average effect of being black relative to being white, to using multiple observations of race data to substantiate a more differentiated conception of racial experience. Using the National Longitudinal Study of Adolescent Health (Add Health), I explore the consequences of different specifications of race/ethnicity for modeling three outcomes: educational attainment, self-rated health, and interracial-relationship history. First, I map the relative multiplicity and consistency of race/ethnicity data across four Add Health panels. Second, I use the model-fit criteria of AIC and BIC to compare methods of assigning a single category to multiple, changed, and other-race (MCO) respondents and of operationalizing heterogeneity among them. I find substantial variation across outcomes in the specifications preferred, with consequences primarily for MCO respondents. I conclude with recommendations for sociologists of race/ethnicity, the interpretive limitations of self-classification data, and the scope of future data collection needed for more comprehensive investigations.
American Sociological Association 114th Annual Meeting
Shiao, Jiannbin Lee
City of Publication
New York, NY