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Record W2259917670 · doi:10.1086/428959

Racial Science in Social Context

2004· article· en· W2259917670 on OpenAlexaff
Michael G. Kenny

Bibliographic record

VenueIsis · 2004
Typearticle
Languageen
FieldArts and Humanities
TopicMedical History and Research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEugenicsSociologyRace (biology)PoliticsIndividualismContext (archaeology)Sociology of scientific knowledgeRelation (database)EpistemologyEnvironmental ethicsSocial scienceLawGender studiesPhilosophyPolitical scienceHistory

Abstract

fetched live from OpenAlex

In 1974 a British biologist, John Randal Baker (1900-1984), published a large and controversial book simply entitled Race that reiterated persistent eugenicist themes concerning the relation between race, intelligence, and progress. The history of Baker's book is a case study in the politics of scientific publishing, and his ideas influenced scholars associated with later works such as The Bell Curve. Baker, a student of Julian Huxley, was a longtime participant in the British eugenics movement and opponent of what he took to be a facile belief in human equality. In 1942, together with Michael Polanyi, he founded the Society for Freedom in Science to oppose those who advocated the central planning of scientific research. Baker's eugenics, political activities, and views on race express an elitist individualism, associated with the conservative wing of the eugenics movement, that this paper explores in the context of his career as a whole.

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)0.009
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0250.073
Scholarly communication0.0130.008
Open science0.0010.009
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.076
GPT teacher head0.316
Teacher spread0.240 · 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.

Study designTheoretical or conceptual
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

Citations25
Published2004
Admission routes1
Has abstractyes

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