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Record W1577080398 · doi:10.4000/noesis.1683

De la représentation à l’interaction : les figures d’énonciateur dans les textes scientifiques

2010· preprint· fr· W1577080398 on OpenAlexaff
Lucile Gaudin-Bordes

Bibliographic record

VenueNoesis · 2010
Typepreprint
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsCanadian Linguistic Association
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

L’éloquence est dans les sciences ce que le soleil est dans le monde. Les sciences ne sont que ténèbres, si ceux qui les traitent ne savent pas écrire. (B. Lamy, La rhétorique ou L’art de parler, PUF, 1998, p. 15) Il en est des sciences comme des viandes, dit saint Augustin ; il faut tâcher de rendre agréable ce qui est utile. (Ibid., p. 267) 1. Introduction La question des rapports entre savoir et rhétorique prend d’abord la forme au xviie siècle d’un problème de délimitation notionnelle. D...

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)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0070.025
Scholarly communication0.0110.015
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0090.002

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 head0.035
GPT teacher head0.329
Teacher spread0.294 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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