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Record W1976895826 · doi:10.4000/ethiquepublique.1008

L’appropriation des connaissances scientifiques à l’ère numérique

2012· article· fr· W1976895826 on OpenAlexvenueno aff
Antoine Latreille

Bibliographic record

VenueÉthique Publique · 2012
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

À l’heure où les pouvoirs publics français viennent de mettre en service leur plate-forme d’ouverture des données publiques et que la plupart des établissements d’enseignement ou de recherche, publics ou privés, se lancent dans l’aventure des archives ouvertes, les réseaux numériques s’imposent définitivement comme principal vecteur de dissémination des connaissances, notamment dans le domaine scientifique.Si les informations ne sont pas appropriables en tant que telles, les productions sont fréquemment objet de protection par un droit de propriété littéraire et artistique consacrée par les lois nationales comme les conventions internationales. Les créateurs de contenus, notamment les enseignants et les chercheurs, ne subissent pas « d’expropriation pour cause d’utilité publique ». Or, l’accès à la connaissance scientifique requiert le plus souvent le recours à ces productions protégées. D’où la nécessité d’analyser le droit positif tel qu’il s’applique en France pour vérifier si le respect des droits des créateurs est conciliable avec la connaissance scientifique.

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)0.018
metaresearch head score (Gemma)0.043
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 score0.994
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.008
Science and technology studies0.0060.014
Scholarly communication0.0220.016
Open science0.0020.009
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0370.007

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 head0.192
GPT teacher head0.314
Teacher spread0.121 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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