Aliya Saperstein

Racial Fluidity and Inequality in the United States1

The authors link the literature on racial fluidity and inequality in the United States and offer new evidence of the reciprocal relationship between the two processes. Using two decades of longitudinal data from a national survey, they demonstrate that not only does an individual’s race change over time, it changes in response to myriad changes in social position, and the patterns are similar for both self-identification and classification by others. These findings suggest that, in the contemporary United States, microlevel racial fluidity serves to reinforce existing disparities by redefining successful or high-status people as white (or not black) and unsuccessful or low-status people as black (or not white). Thus, racial differences are both an input and an output in stratification processes; this relationship has implications for theorizing and measuring race in research, as well as for crafting policies that attempt to address racialized inequality.

How social status shapes race

We show that racial perceptions are fluid; how individuals perceive their own race and how they are perceived by others depends in part on their social position. Using longitudinal data from a representative sample of Americans, we find that individuals who are unemployed, incarcerated, or impoverished are more likely to be seen and identify as black and less likely to be seen and identify as white, regardless of how they were classified or identified previously. This is consistent with the view that race is not a fixed individual attribute, but rather a changeable marker of status.

New Categories Are Not Enough Rethinking the Measurement of Sex and Gender in Social Surveys

Recently, scholars and activists have turned their attention toward improving the measurement of sex and gender in survey research. The focus of this effort has been on including answer options beyond “male” and “female” to questions about the respondent’s gender. This is an important step toward both reflecting the diversity of gendered lives and better aligning survey measurement practice with contemporary gender theory. However, our systematic examination of questionnaires, manuals, and other technical materials from four of the largest and longest-running surveys in the United States indicates that there are a number of other issues with how gender is conceptualized and measured in social surveys that also deserve attention, including essentialist practices that treat sex and gender as synonymous, easily determined by others, obvious, and unchanging over the life course. We find that these understandings extend well beyond direct questions about the respondent’s gender, permeating the surveys. A hyper-gendered world of “males” and “females,” “brothers” and “sisters,” and “husbands” and “wives” shapes what we can see in survey data. If not altered, surveys will continue to reproduce statistical representations that erase important dimensions of variation and likely limit understanding of the processes that perpetuate social inequality.

Capturing complexity in the United States: which aspects of race matter and when?

Abstract The experience of race in the United States is shaped by both self-identification and ascription. One aspect reflects personal history, ancestry, and socialization while the other draws largely on appearance. Yet, most data collection efforts treat the two aspects of race as interchangeable, assuming that the relationship between each and an individuals life chances will be the same. This study demonstrates that incorporating racial self-identification and other-classification in analyses of inequality reveals more complex patterns of advantage and disadvantage than can be seen using standard methods. These findings have implications for how racial data should be collected and suggest new directions for studying racial inequality in the United States and around the world.

Engendering Racial Perceptions: An Intersectional Analysis of How Social Status Shapes Race

Intersectionality emphasizes that race, class, and gender distinctions are inextricably intertwined, but fully interrogating the co-constitution of these axes of stratification has proven difficult to implement in large-scale quantitative analyses. We address this gap by exploring gender differences in how social status shapes race in the United States. Building on previous research showing that changes in the racial classifications of others are influenced by social status, we use longitudinal data to examine how differences in social class position might affect racial classification differently for women and men. In doing so, we provide further support for the claim that race, class, and gender are not independent axes of stratification; rather they intersect, creating dynamic feedback loops that maintain the complex structure of social inequality in the United States.

A “Mulatto Escape Hatch” in the United States? Examining Evidence of Racial and Social Mobility During the Jim Crow Era

Racial distinctions in the United States have long been characterized as uniquely rigid and governed by strict rules of descent, particularly along the black-white boundary. This is often contrasted with countries, such as Brazil, that recognize “mixed” or intermediate racial categories and allow for more fluidity or ambiguity in racial classification. Recently released longitudinal data from the IPUMS Linked Representative Samples, and the brief inclusion of a “mulatto” category in the U.S. Census, allow us to subject this generally accepted wisdom to empirical test for the 1870–1920 period. We find substantial fluidity in black-mulatto classification between censuses—including notable “downward” racial mobility. Using person fixed-effects models, we also find evidence that among Southern men, the likelihood of being classified as mulatto was related to intercensal changes in occupational status. These findings have implications for studies of race and inequality in the United States, cross-national research on racial classification schemes in the Americas, and for how demographers collect and interpret racial data.

Beyond the Looking Glass: Exploring Fluidity in Racial Self-identification and Interviewer Classification

Research has demonstrated the fluidity of racial self-identification and interviewer classification, but how they influence each other over time has not been systematically explored using national, longitudinal data. A typical theoretical prediction, consistent with theories of a “looking-glass self,” is that people calibrate their self-identification in accordance with how they are perceived by others. We examine the degree to which this and other symbolic-interactionist processes account for the dynamics of racial categorization among young adults in the United States. To do so, we deploy a conceptual framework focused on three key dimensions of variation—concordance, stability, and influence—that capture both inconsistency in racial categorization at a given point in time and fluidity in either measure of race over time. We find that while the standard looking-glass self-perspective accounts for the majority of racial fluidity, a substantial proportion of changes in both measures of race remain unexplained by existing theory.

Race, Ethnicity and Ancestry in Unrelated Transplant Matching for the National Marrow Donor Program: A Comparison of Multiple Forms of Self-Identification with Genetics.

We conducted a nationwide study comparing self-identification to genetic ancestry classifications in a large cohort (n = 1752) from the National Marrow Donor Program. We sought to determine how various measures of self-identification intersect with genetic ancestry, with the aim of improving matching algorithms for unrelated bone marrow transplant. Multiple dimensions of self-identification, including race/ethnicity and geographic ancestry were compared to classifications based on ancestry informative markers (AIMs), and the human leukocyte antigen (HLA) genes, which are required for transplant matching. Nearly 20% of responses were inconsistent between reporting race/ethnicity versus geographic ancestry. Despite strong concordance between AIMs and HLA, no measure of self-identification shows complete correspondence with genetic ancestry. In certain cases geographic ancestry reporting matches genetic ancestry not reflected in race/ethnicity identification, but in other cases geographic ancestries show little correspondence to genetic measures, with important differences by gender. However, when respondents assign ancestry to grandparents, we observe sub-groups of individuals with well- defined genetic ancestries, including important differences in HLA frequencies, with implications for transplant matching. While we advocate for tailored questioning to improve accuracy of ancestry ascertainment, collection of donor grandparents’ information will improve the chances of finding matches for many patients, particularly for mixed-ancestry individuals.

Disentangling the Effects of Racial Self-identification and Classification by Others: The Case of Arrest

Scholars of race have stressed the importance of thinking about race as a multidimensional construct, yet research on racial inequality does not routinely take this multidimensionality into account. We draw on data from the U.S. National Longitudinal Study of Adolescent Health to disentangle the effects of self-identifying as black and being classified by others as black on subsequently being arrested. Results reveal that the odds of arrest are nearly three times higher for people who were classified by others as black, even if they did not identify themselves as black. By contrast, we find no effect of self-identifying as black among people who were not seen by others as black. These results suggest that racial perceptions play an important role in racial disparities in arrest rates and provide a useful analytical approach for disentangling the effects of race on other outcomes.

Making the Most of Multiple Measures Disentangling the Effects of Different Dimensions of Race in Survey Research

The majority of social science research uses a single measure of race when investigating racial inequality. However, a growing body of work demonstrates that race shapes the life chances of individuals in multiple ways, related not only to how people self-identify but also to how others perceive them. As multiple measures of race are increasingly collected and used in survey research, it becomes important to consider the best methods of leveraging such data. We present four analytical approaches for incorporating two different dimensions of race in the same study and illustrate their use with data from the U.S. National Longitudinal Study of Adolescent to Adult Health. The approaches range from tests of specific hypotheses to the most exploratory description of how different measures of race relate to social inequality. Although each approach has its strengths and weaknesses, by accounting for the multidimensionality of race, they all allow for more nuanced patterns of advantage and disadvantage than standard single-measure methods.