Reconsidering wealth, status, and power: Critical Demography and the measurement of racism

Horton, Hayward Derrick; Sykes, Lori Latrice

doi:10.1016/s1090-9524(03)00010-x

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…This use of race as variable fails to engage race as a social construction by obscuring the social processes that produce racial categories and racial inequality and reproducing the notion of race as an innate, flat variable (Zuberi, 2008). For example, the continued use of the "race effect" to examine performance differences between racial groups asserts an almost causal role to race in outcomes (Holland, 2008;Horton & Sykes, 2008;Stewart, 2008). However, CRT asserts that race is not just a variable to control but a structuring agent of society.…”

Section: Implementing a Critical Race Frame In Urban Sociologymentioning

confidence: 99%

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Reproducing race in the gentrifying city: A critical analysis of race in gentrification scholarship

Fallon

2020

Journal of Race, Ethnicity and the City

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While the term gentrification in an American context often incorporates racial turnover, the role of race in gentrification remains undertheorized. Employing a critical race lens, this study explores the historical relationship between race and gentrification in academic studies. I conduct a systematic review and a discourse analysis of 331 empirical studies of gentrification from 1970-2019. Findings show that although studies frequently employ racial categories, they do so in imprecise ways, subsuming race under class. Race-based theory is rare; race is primarily used as a variable of measure to examine conflict-oriented outcomes, such as displacement. This creates oppositional and homogenizing racialized typologies of "poor minority incumbents" and "wealthy White newcomers," which remain steady despite an increasingly complex urban landscape. I argue that this limits our ability to understand how race, class, and power operate in space and underscores the need for a more clearly defined role of race within gentrification that focuses on positionality and power in lieu of a groupist emphasis on antagonistic racial categorization.Gentrification as a concept emerged in the 1960s to describe the combination of reinvestment and repopulation that occurred in similar fashion across many cities. Since its emergence, gentrification has come to occupy an increasingly large position in both media and academic scholarship (Helms, 2003;Tolfo & Doucet, 2020), with substantial numbers of academic studies focused on gentrification over time (Figure 1).With the growing prominence of the concept, there is substantial debate about how gentrification should be defined and measured. Meta-analyses have found that while definitions vary broadly, gentrification most consistently refers to a change in the socioeconomic status of neighborhood residents. At times studies may also emphasize changes in infrastructural quality, cultural identity, market values, ownership rates, and/or displacement (see Atkinson, 2000;Redfern, 2003). While economic change is paramount, racial turnover is also often included in descriptions of gentrification (Boyd, 2008;Kirkland, 2008). This is particularly true within an American context, where the housing landscape has been shaped by racialized processes of segregation and discrimination that link race, class, and housing in complex ways (Massey, 2016;Massey & Denton, 1993;Wilson, 1987). Despite this frequent connection between race and gentrification, the role of race as a component of gentrification remains undertheorized (Boyd, 2008;Kirkland, 2008).

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Section: Implementing a Critical Race Frame In Urban Sociologymentioning

confidence: 99%

“…Likewise, if the factors limiting housing access are due to discriminatory practices, studies should focus on racism rather than using race as a proxy. Horton and Sykes (2008) provide an example of how scholars can tie a theory of race to methods by measuring racism rather than just race in isolation.…”

Section: Moving Past Race As a Stable Traitmentioning

confidence: 99%

Reproducing race in the gentrifying city: A critical analysis of race in gentrification scholarship

Fallon

2020

Journal of Race, Ethnicity and the City

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“…Numbers help "maintain and reproduce social processes … they can entrench power relations even while appearing to transform them" (Lynch 2017), including processes and power relations underlying racial stratification. The collection and production of social statistics, demographic data, and the social sciences have emerged from, reify, and justify racial categories, inequalities, and White supremacy (e.g., Gutiérrez 2008;Horton and Sykes 2008;Zuberi 2001). The U.S. Census Bureau, the primary supplier of data about the U.S. population, and the counts it produces are embedded in these larger racial and social projects (e.g., Mora 2014; Omi and Winant 2014;Porter 1986;Rodríguez 2000;Strmic-Pawl, Jackson, and Garner 2018;Zuberi 2001).…”

mentioning

confidence: 99%

Numbers, Narratives, and Nation: Mainstream News Coverage of U.S. Latino Population Growth, 1990–2010

McConnell

2018

Sociology of Race and Ethnicity

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Ideologies that support racial domination and White supremacy remain foundational in U.S. society, even as the nation becomes increasingly diverse and progressively focused on quantitative measurement. This study explores how a prominent mainstream news outlet represents the growth of the nation’s second largest population, Latinos, within this changing demographic and numeric environment. Drawing from two frameworks, the Latino Threat Narrative and Color-Blind Racism, quantitative and qualitative analyses are conducted with 174 Los Angeles Times ( LAT) articles about 2000 and 2010 census results. Reporters for the LAT, located in the single most important U.S. location for Latinos, frame Latinos and their population dynamics in line with the overtly racist narrative of Latino threat and the covertly racist ideology of color-blind racism. Moreover, the analyses reveal that quantitative logics circulating in the present evaluative climate further the view that Latinos pose cultural-demographic threats to the nation. Quantification also enhances color-blind frames and rhetorical strategies justifying present-day racial stratification and the subordinate locations of non-White groups. This suggests how White supremacy retains its power as the populations and metrics of evaluation change. Finally, given recent research linking demographic trends and media representations with attitudes, policy positions, and political partisanship, these representations have implications for the well-being of Latinos, other populations, and the nation.

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“…Given that race is a social construct, inferred racial categories should only be used in the study of group-level social dynamics underlying these categories, and not as individual-level traits. Census classifications are founded upon the social construction of race and reality of racism in the U.S., which serves as “a multi-level and multi-dimensional system of dominant group oppression that scapegoats the race and/or ethnicity of one or more subordinate groups” [ 28 ]. Self-identification of racial categories continue to reflect broader definitional challenges, along with issues of interpretation, and above all the amorphous power dynamics surrounding race, politics, and science in the U.S.…”

Section: Introductionmentioning

confidence: 99%

Avoiding bias when inferring race using name-based approaches

et al. 2022

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Racial disparity in academia is a widely acknowledged problem. The quantitative understanding of racial-based systemic inequalities is an important step towards a more equitable research system. However, because of the lack of robust information on authors’ race, few large-scale analyses have been performed on this topic. Algorithmic approaches offer one solution, using known information about authors, such as their names, to infer their perceived race. As with any other algorithm, the process of racial inference can generate biases if it is not carefully considered. The goal of this article is to assess the extent to which algorithmic bias is introduced using different approaches for name-based racial inference. We use information from the U.S. Census and mortgage applications to infer the race of U.S. affiliated authors in the Web of Science. We estimate the effects of using given and family names, thresholds or continuous distributions, and imputation. Our results demonstrate that the validity of name-based inference varies by race/ethnicity and that threshold approaches underestimate Black authors and overestimate White authors. We conclude with recommendations to avoid potential biases. This article lays the foundation for more systematic and less-biased investigations into racial disparities in science.

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Reconsidering wealth, status, and power: Critical Demography and the measurement of racism

Cited by 4 publications

References 11 publications

Reproducing race in the gentrifying city: A critical analysis of race in gentrification scholarship

Reproducing race in the gentrifying city: A critical analysis of race in gentrification scholarship

Numbers, Narratives, and Nation: Mainstream News Coverage of U.S. Latino Population Growth, 1990–2010

Avoiding bias when inferring race using name-based approaches

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