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Record W2626791359 · doi:10.1525/hsns.2017.47.3.423

“Neither a confession nor an accusation”

2017· article· en· W2626791359 on OpenAlexaff
Alan Richardson

Bibliographic record

VenueHistorical Studies in the Natural Sciences · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Medicine
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsExpansivePoliticsHistory of scienceConfession (law)SociologyPhilosophy of scienceIntellectual historyHistory and philosophy of scienceEpistemologySocial scienceHistoryPhilosophyLawPolitical scienceArchaeology

Abstract

fetched live from OpenAlex

Mary Jo Nye is one of our great historians of chemistry, especially of the nineteenth and twentieth centuries. Her work has been consistent and diligent in connecting the scientific research of the figures she studies to its larger intellectual and cultural contexts. Given the significance and the breadth of the historical figures she studies, this broad focus brings into her histories of chemistry and physics an expansive array of concerns, influences, cultural and political contexts. Of special interest to those of us whose research focuses on the history of philosophy of science, several of the figures substantially illuminated by Nye’s work are scientists who played important roles in the development of (history and) philosophy of science. Among these figures, J. D. Bernal and Michael Polanyi are only the most significant. This essay is part of a special issue entitled THE BONDS OF HISTORY edited by Anita Guerrini.

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)0.004
metaresearch head score (Gemma)0.029
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.020
Scholarly communication0.0070.011
Open science0.0010.003
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0080.006

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 head0.263
GPT teacher head0.399
Teacher spread0.135 · 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 designQualitative
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

Citations2
Published2017
Admission routes1
Has abstractyes

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