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Record W4408567949 · doi:10.1080/01419870.2025.2477748

Determinants of genetic essentialist beliefs about race: a comparison of Canada and the United States

2025· article· en· W4408567949 on OpenAlexafffundabout
Şule Yaylacı, Derek Robey, Wendy D. Roth

Bibliographic record

VenueEthnic and Racial Studies · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRace, Genetics, and Society
Canadian institutionsUniversity of New Brunswick
FundersSocial Sciences and Humanities Research Council of CanadaCanada Foundation for Innovation
KeywordsEssentialismRace (biology)GenealogyPolitical scienceDemographySociologyGender studiesHistory

Abstract

fetched live from OpenAlex

With the rise of genomics, beliefs about the relationship between race and genetics are increasingly important. Genetic essentialist beliefs – the idea that races have core essences determined by their genes – are associated with prejudice and justification of racial inequalities. Yet research to understand these beliefs is hampered by a lack of measures across nations. This exploratory study uses the newly-developed Genetic Essentialism Scale for Race to compare genetic essentialist beliefs and their determinants in samples of native-born White Canadians and Americans. We find higher average genetic essentialism among Canadian respondents than their American counterparts. However, examining subdimensions of genetic essentialism shows some of the views that contribute to it are held more strongly in the U.S., and others in Canada. We compare the determinants of genetic essentialism and its subdimensions across these national contexts and suggest further research into the role of multiculturalist policies, educational curricula, and religiosity.

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)0.004
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 score0.026
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0060.002
Scholarly communication0.0020.000
Open science0.0010.002
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 head0.015
GPT teacher head0.328
Teacher spread0.314 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

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