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Record W2000249211 · doi:10.1086/521160

Murky Waters

2007· article· en· W2000249211 on OpenAlexaff
Grace Shen

Bibliographic record

VenueIsis · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Natural History
Canadian institutionsYork University
Fundersnot available
KeywordsAsideChinaHistory of scienceMythologyRelevance (law)DisciplineChinese scienceOrder (exchange)SociologyEpistemologyQuality (philosophy)Environmental ethicsSocial sciencePolitical scienceHistoryPhilosophyLawClassics

Abstract

fetched live from OpenAlex

Historians of science in modern China have tried to challenge misconceptions that late nineteenth- and early twentieth-century Chinese were slow to master science or, worse, that they missed the point of science altogether. In so doing, we have often put aside basic questions-like why Chinese were interested in modern science in the first place or how they found modern science useful for their own purposes-in order to demonstrate the quality and advancement of scientific work in China. But overlooking these underlying issues not only strengthens the myth of science as an obvious and inevitable step in development; it also limits the relevance of the Chinese case to the history of science more broadly. If, instead, the spread of science is reconceptualized as a problem of desire and utility, the Chinese example may suggest interesting new avenues for the study of cultural innovation across geographic and disciplinary frameworks.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.992
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.018
Scholarly communication0.0060.008
Open science0.0010.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0460.007

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 head0.022
GPT teacher head0.208
Teacher spread0.186 · 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

Citations7
Published2007
Admission routes1
Has abstractyes

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