Dissertation
(Re)Modeling Race: Incorporating Racial Theory into Survey Research on Inequality
Over the past decade, debates have raged inside and outside the American academy about whether race should be included in survey research and governmental data gathering. The consensus position - that collecting racial data is necessary in order to monitor racial inequality - is admirable but fails to address the substantial gap between social science theory about race and actual research practice. While racial theory stresses complexity, contingency and a dynamic relationship between race and inequality, standard survey research practice continues to use a single, self-reported measure of race, as if it were a question to which there is only one "correct" answer. (read more ...)
Peer-reviewed Publications
Social
constructivist theories of race suggest no two measures of race will
capture the same information, but the degree of "error" this creates
for quantitative research on inequality is unclear. Using unique data
from the General Social Survey, I find observed and self-reported
measures of race yield substantively different results when used to
explain income inequality in the United States. This occurs because
inconsistent racial classification is correlated with other respondent
characteristics such as immigrant generation, educational attainment
and age.
Work in Progress (Please do not quote or cite manuscripts without permission)
presented at the 2006 Population Association of American Annual Meeting, March 30, Los Angeles