2005 University of Michigan Poverty Research Grants
Funded research
Anthony Daniel Perez, Doctoral Candidate, University of Michigan Department of Sociology & Ford School of Public Policy.
One Drop, No Rule: Correlates of Multiracial Classification and the Effects of Alternative Race Measures on Child Poverty Estimates.
Description
This project explores patterns of classification among multiracial children in the U.S. and considers the extent to which the racial distribution of child poverty is sensitive to alternative race measures.
Unlike singe race children, whose identities almost always correspond with those of their parents, biracial children can be identified in several different ways. Though many biracial children are in fact identified as mixed, many others are identified simply as white or non-white. These identity decisions are far from arbitrary, however, given the pernicious legacy of the one-drop rule as well as the frequent though contentious history of "white passing" among individuals of mixed race heritage. Utilizing recent census microdata, I will compare the distributions of identity choices across mixed race sub-groups (white/black children vs. white/Asian, e.g.) and further consider the extent to which these choices are associated with other family background characteristics such as SES and social context.
By linking child records with those of their parents, I can allow the multiracial population to be defined in different ways. One definition (the official one) is simply the population of children identified on the Census as having two or more races. An alternative definition includes all biological children of interracial couples, regardless of how they were actually identified. Given the imperfect link between child/parent identities, this latter conceptualization of the multiracial child “universe” produces a population that is much larger in size than the population actually enumerated. The next logical question to ask is if these two different definitions yield populations with dissimilar characteristics as well. It is in this vein that I consider the sensitivity of racial poverty estimates to the choice of race measure used.
The implications of this research are potentially far reaching. To the extent that measurement sensitivity may limit our ability to assess poverty differentials by race and ethnicity, care in the choice of how and where multiracial children are included will become increasingly necessary component of poverty research. Racial classification also poses a mounting concern to policy makers, as no less than eleven federal agencies and over two dozen Acts, programs, and legislation pieces employ racial data for a variety of purposes ranging from civil rights enforcement to legislative redistricting. As the Multiracial population continues to grow in importance, so too will the issues surrounding the measurement and classification of this emergent population. In undertaking a comprehensive assessment of both the intricacy and the magnitude of these racial measurement issues, I hope to advance identification research beyond the purview of academic curiosity.
