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Record W2904058278 · doi:10.1177/0190272518804145

The Effects of Education on Beliefs about Racial Inequality

2018· article· en· W2904058278 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSocial Psychology Quarterly · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational and Educational Inequality Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInequalityPerspective (graphical)SiblingIndividualismSocial psychologyConfoundingPsychologyRace (biology)Social inequalityGeneral Social SurveySet (abstract data type)White (mutation)SociologyDevelopmental psychologyGender studiesEconomicsMedicine

Abstract

fetched live from OpenAlex

It is commonly hypothesized that education promotes more “enlightened” beliefs about racial inequality, and many prior studies document that white Americans with higher levels of education are more likely to agree with structural rather than individualist explanations for black disadvantages. Nevertheless, an alternative perspective contends that the ostensibly liberalizing effects of education are highly superficial, while yet another perspective cautions that any association observed between education and racial attitudes may be due to unobserved confounding. This study evaluates these perspectives by estimating the effects of education on beliefs about racial inequality from a set of cross-sectional, sibling, and panel models. Consistent with prior research, results from cross-sectional models fit to the General Social Survey (GSS) suggest that education promotes a genuine belief in structural over individualist explanations for racial inequality. However, results from sibling and individual fixed-effects models fit, respectively, to the 1994 Study of American Families and to the 2006–2010 GSS three-wave panels suggest that these effects may be superficial and are likely inflated by unobserved confounding.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.439
Teacher spread0.404 · 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