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Record W2150615437 · doi:10.1093/socpro/spv028

Are Smart People Less Racist? Verbal Ability, Anti-Black Prejudice, and the Principle-Policy Paradox

2016· article· en· W2150615437 on OpenAlexaff
Geoffrey T. Wodtke

Bibliographic record

VenueSocial Problems · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentUniversity of MichiganNational Science Foundation
KeywordsPrejudice (legal term)PsychologySocial psychologyRacismSociologyGender studies

Abstract

fetched live from OpenAlex

It is commonly hypothesized that higher cognitive abilities promote racial tolerance and a greater commitment to racial equality, but an alternative theoretical framework contends that higher cognitive abilities merely enable members of a dominant racial group to articulate a more refined legitimizing ideology for racial inequality. According to this perspective, ideological refinement occurs in response to shifting patterns of racial conflict and is characterized by rejection of overt prejudice, superficial support for racial equality in principle, and opposition to policies that challenge the dominant group’s status. This study estimates the impact of verbal ability on a comprehensive set of racial attitudes, including anti-black prejudice, views about black-white equality in principle, and racial policy support. It also investigates cohort differences in the effects of verbal ability on these attitudes. Results suggest that high-ability whites are less likely than low-ability whites to report prejudicial attitudes and more likely to support racial equality in principle. Despite these liberalizing effects, high-ability whites are no more likely to support a variety of remedial policies for racial inequality. Results also suggest that the ostensibly liberalizing effects of verbal ability on anti-black prejudice and views about racial equality in principle emerged slowly over time, consistent with ideological refinement theory. Comúnmente se plantea la hipótesis de que las habilidades cognitivas superiores promueven la tolerancia racial y un mayor compromiso con la igualdad racial, pero un marco teórico alternativo sostiene que las habilidades cognitivas superiores simplemente permiten a los miembros de un grupo racial dominante articular una ideología legitima más refinada de la desigualdad racial. De acuerdo con esta perspectiva, el refinamiento ideológico se produce en respuesta a los patrones cambiantes de los conflictos raciales y se caracteriza por el rechazo de los prejuicios abiertos, el apoyo superficial por la igualdad racial, en principio, y la oposición a las políticas que cuestionan el estatus del grupo dominante. Este estudio estima el impacto de la capacidad verbal en un amplio conjunto de actitudes raciales, incluyendo el prejuicio anti-negro, puntos de vista sobre negros-blancos la igualdad, en principio, y de apoyo a políticas raciales. También investiga las diferencias de grupo en los efectos de la habilidad verbal en estas actitudes. Los resultados sugieren que los blancos de alta capacidad son menos propensos que los blancos de baja capacidad a reportar actitudes prejuiciosas y más propensos a apoyar la igualdad racial en principio. A pesar de estos efectos liberalizadores, los blancos de alta capacidad no son más propensos a apoyar una variedad de políticas correctivas de la desigualdad racial. Los resultados también sugieren que los efectos supuestamente liberalizadores de la capacidad verbal sobre los prejuicios anti-negro y puntos de vista acerca de la igualdad racial en principio surgieron lentamente con el tiempo, en consonancia con la teoría de refinamiento ideológico.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.059
GPT teacher head0.344
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations38
Published2016
Admission routes1
Has abstractyes

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