219,382 research outputs found

    A MAJORITY-MINORITY NATION: RACING THE POPULATION IN THE TWENTY-FIRST CENTURY

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    This article explores the factors that affect the creation of racial classifications and how they are reflected in the Census categories, particularly in regard to the classification of Hispanics. The article argues that an increase in racial minorities will not solely stop white racial domination of political power structures because of entrenched racial policies and practices. To end this domination, racial minorities must organize and collaborate to take down these racially oppressive structures

    A MAJORITY-MINORITY NATION: RACING THE POPULATION IN THE TWENTY-FIRST CENTURY

    Get PDF
    This article explores the factors that affect the creation of racial classifications and how they are reflected in the Census categories, particularly in regard to the classification of Hispanics. The article argues that an increase in racial minorities will not solely stop white racial domination of political power structures because of entrenched racial policies and practices. To end this domination, racial minorities must organize and collaborate to take down these racially oppressive structures

    2003 Multilingual Survey of California Voters

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    Provides an analysis of the views of California's major racial and ethnic groups on the gubernatorial recall, Governor Gray Davis' performance in office, the candidates seeking to replace him, and the racial classification initiative

    Identity matters: inter- and intra-racial disparity and labor market outcomes

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    Standard analysis of racial inequality incorporates racial classification as an exogenous binary variable. This approach obfuscates the importance of racial self-identity and clouds our ability to understand the relative importance of unobserved productivity-linked attributes versus market discrimination as determinants of racial inequality in labor market outcomes. Our examination of identity heterogeneity among African Americans suggests racial wage disparity is most consistent with weak colorism, while genotype disparity best describes racial employment differences. Further, among African Americans, the wage data are not consistent with the hypothesis that black-mixed race wage disparity can be explained by differences in unobserved productivity-linked productive attributes.racial discrimination, racial inequality, identity, African American, African Diaspora, wage discrimination, employment discrimination, Hispanic, acting white, multi-racial, skin shade

    Cause of Death Affects Racial Classification on Death Certificates

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    Recent research suggests racial classification is responsive to social stereotypes, but how this affects racial classification in national vital statistics is unknown. This study examines whether cause of death influences racial classification on death certificates. We analyze the racial classifications from a nationally representative sample of death certificates and subsequent interviews with the decedents' next of kin and find notable discrepancies between the two racial classifications by cause of death. Cirrhosis decedents are more likely to be recorded as American Indian on their death certificates, and homicide victims are more likely to be recorded as Black; these results remain net of controls for followback survey racial classification, indicating that the relationship we reveal is not simply a restatement of the fact that these causes of death are more prevalent among certain groups. Our findings suggest that seemingly non-racial characteristics, such as cause of death, affect how people are racially perceived by others and thus shape U.S. official statistics

    The Shade of a Criminal Record: Colorist, Incarceration, and External Racial Classification

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    Recent high-profile research suggests that social indicators like incarceration influence racial categorization. Yet, this research has largely ignored colorism—intraracial differences in skin tone that matter for stratification outcomes. In two experiments, we address how skin tone interacts with criminal background to produce external racial classification and skin tone attributions. We find no evidence that criminal history affects external racial classification or skin tone attribution. However, we find that skin tone is a strong and consistent predictor of external racial classification and skin tone attribution

    The Shade of a Criminal Record: Colorism, Incarceration, and External Racial Classification

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    Recent high-profile research suggests that social indicators like incarceration influence racial categorization. Yet, this research has largely ignored colorism—intraracial differences in skin tone that matter for stratification outcomes. In two experiments, we address how skin tone interacts with criminal background to produce external racial classification and skin tone attributions. We find no evidence that criminal history affects external racial classification or skin tone attribution. However, we find that skin tone is a strong and consistent predictor of external racial classification and skin tone attribution

    Racial categories in machine learning

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    Controversies around race and machine learning have sparked debate among computer scientists over how to design machine learning systems that guarantee fairness. These debates rarely engage with how racial identity is embedded in our social experience, making for sociological and psychological complexity. This complexity challenges the paradigm of considering fairness to be a formal property of supervised learning with respect to protected personal attributes. Racial identity is not simply a personal subjective quality. For people labeled "Black" it is an ascribed political category that has consequences for social differentiation embedded in systemic patterns of social inequality achieved through both social and spatial segregation. In the United States, racial classification can best be understood as a system of inherently unequal status categories that places whites as the most privileged category while signifying the Negro/black category as stigmatized. Social stigma is reinforced through the unequal distribution of societal rewards and goods along racial lines that is reinforced by state, corporate, and civic institutions and practices. This creates a dilemma for society and designers: be blind to racial group disparities and thereby reify racialized social inequality by no longer measuring systemic inequality, or be conscious of racial categories in a way that itself reifies race. We propose a third option. By preceding group fairness interventions with unsupervised learning to dynamically detect patterns of segregation, machine learning systems can mitigate the root cause of social disparities, social segregation and stratification, without further anchoring status categories of disadvantage

    "Reflecting the Changing Face of America, Multiracials Racial Classification, and American Intermarriage"

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    On the U.S. census form American citizens told they may list any ethnic ancestries with which they identify, but are instructed to "mark one only" in the question on race. Joel Perlmann asserts that it is in the public interest to allow people to declare themselves as having origins in more than one race. To do otherwise is to deny that interracial marriages exist. This denial distorts our understanding of race data whether we are discussing projections of the composition of the American population or the definition of racial and minority status involved in discrimination legislation, affirmative action, and hiring and firing practices. If racial barriers are to be broken down, racial intermarriage should be treated in the same way any other form of ethnic intermarriage is treated, while ensuring that civil rights legislation, which rests on racial classification and counts, is not hobbled by ambiguities.

    Racial Classification and Ascriptive Injury

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