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Record W4318573531 · doi:10.32920/21979706.v1

How diversity makes science work better

2023· preprint· en· W4318573531 on OpenAlexaboutno aff
Imogen R. Coe

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsnot available
Fundersnot available
KeywordsSurpriseDiversity (politics)Work (physics)Political scienceSociologyEnvironmental ethicsLawPsychologyPhilosophySocial psychologyEngineering

Abstract

fetched live from OpenAlex

[p.1]: " Just over 25 years ago, the Canadian Journal of Physics published an article by Dr. Gordon Freeman, a chemistry professor, in which he asserts that “women who work outside the home contribute to the moral degeneration of their children.” This piece was submitted as a scientific paper (it wasn’t) and published after (alleged) rigorous peer-review by experts in the field (physics?), which is the gold standard for the reporting of science. Not surprisingly, this misogynistic opinion piece published as “science” generated considerable debate across the country. In the last half of the 20th century, some scientists in Canada were still remarkably sexist, which probably doesn’t surprise anyone — and even unethical, which should surprise everyone."

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)0.038
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Open science
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.998
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.051
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0130.064
Scholarly communication0.0270.038
Open science0.0020.016
Research integrity0.0100.012
Insufficient payload (model declined to judge)0.0230.007

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 head0.745
GPT teacher head0.473
Teacher spread0.272 · 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
DomainIncentives
GenreCommentary

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

Citations0
Published2023
Admission routes1
Has abstractyes

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