Suchergebnisse

For multiracial, Hispanic, and Native Americans, norms for racial and ethnic self-identification are less well established than they are for other population groups. There is considerable variation and fluidity in how multiracial, Hispanic, and Native Americans self-identify, as well as how they are classified by others. This presents challenges to researchers and analysts in terms of consistently and accurately estimating the size and population dynamics of these groups. I argue that for analytic purposes, racial/ethnic self-identification should continue to be treated as a statistical numerator, but that the challenge is for researchers to establish the correct denominator—the population that could identify as members of the group based on their ancestry. Examining how many people who could identify with these groups choose to do so sheds light on assimilation and emerging racial classification processes. Analyses of the larger potential populations further avoid bias stemming from nonrandom patterns of self-identification with the groups.

Official statistics are political creations more than theoretically-guided concepts. The papers in this panel make this exceptionally clear, as does the work of many others (e.g., Loveman 2014; Nobles 2000; Prewitt 2013). This means that official measures of race in countries around the world are unlikely to be guided by theoretical concern for distinguishing the different dimensions that are all embedded under the umbrella term: "race". Furthermore, categories created for official statistics or national censuses can take on a life of their own. They can be applied to new contexts and inform public debates beyond their original demographic or political purposes. Here, I argue that the need for theoretical clarity across dimensions of race is magnified by comparisons across national contexts. I also discuss, using the example of the Canadian measure of "visible minorities" how the repurposing of statistical categories can create its own methodological pitfalls in measuring distinct dimensions of race. ; Arts, Faculty of ; Sociology, Department of ; Reviewed ; Faculty

Objectives.A primary justification for collecting U.S. racial statistics is the need to monitor racial discrimination. This article aims to show how analyses of Hispanics—who may officially be of any race—tend to miss discrimination based on racial appearance by relying on data that instead capture racial self‐identification, a different aspect of race that often does not correspond.Methods.The study analyzes 60 qualitative interviews with Dominican and Puerto Rican migrants in the New York metropolitan area. It employs multiple measures to represent theoretically distinct aspects of the lived experience of race.Results.Respondents interpret the Census race question in different ways corresponding to different aspects of race, which often do not match one another. Although respondents experience discrimination on the basis of phenotype, their racial self‐identification is a poor proxy for measuring their racial appearance.Conclusions.Scholars need to develop a language of race that communicates the multiplicity of social processes involved. Social surveys must provide measures of these multiple components, including interviewer observations of racial appearance, to monitor discrimination on the basis of phenotype within Hispanic groups.

How does skin color shape the social networks and integration pathways of phenotypically diverse immigrant groups? Focusing on Dominicans and Puerto Ricans, groups with considerable diversity across the Black-White color line, the authors explore whether migrants to the United States have greater color homophily in their primary social networks than nonmigrants in the sending societies. The authors analyze egocentric network data, including unique skin color measures for both 114 respondents and 1,702 alters. They test hypotheses derived from ethnic unifier theory and color line racialization theory. The data show evidence of color homophily among Dominicans but suggest that these patterns may be imported from the sending society rather than fostered by the U.S. context. Furthermore, the authors find that migrants' skin color is associated with having ties to White or Black Americans but with different patterns for each ethnic group. The authors discuss the implications of these findings for economic mobility and U.S. racial hierarchies.

This paper explicates a central conflict that can affect science research organizations, the conflict between the anti-bureaucratic stance believed to advance science and concerns for gender equity rooted in the universalist ethos of science. We present a case study of a science research organization, using employment and publication records, a survey of 308 employees, and qualitative interviews with 60 employees. We show how anti-bureaucratic organizational structures perpetuate gender inequities for both female scientists and non-scientists.

Immigration is changing the racial composition of many societies. Yet leading theories of racial prejudice, even in a multiracial context, focus on dynamics in a single nation-state and fail to account for the experiences of the foreign-born. We adopt a transnational approach that incorporates processes creating prejudice from both inside and outside the receiving society and that shows how attitudes move across borders through immigration, transnationalism, and globalization. We draw upon two in-depth studies of immigrants and those who stay in the home countries, focusing on Koreans' and Dominicans' attitudes toward Black Americans. By situating existing theories of racial prejudice within a transnational framework, we illustrate how models of transnationalism are relevant not just within immigration scholarship, but to more general processes of social change.