Lexique, catégorisation et représentation : les reformulations métalinguistiques dans le discours animaliste
Bibliographic record
Abstract
Cet article se propose d’explorer la relation entre lexique, reformulations métalinguistiques non savantes et représentations en s’appuyant sur un corpus de discours animalistes constitué de pétitions en ligne, d’extraits de sites d’associations engagées dans la cause animale, de commentaires d’internautes, d’articles de presse et d’interviews de militant·e·s. Il s’inscrit dans le cadre d’une linguistique populaire axée sur des questions de sémantique. L’analyse des énoncés de militant·e·s a permis de dégager la notion d’axiolexème qui s’applique à des mots ordinaires du lexique auxquels les énonciateurs tentent d’ajouter en discours une dimension morale. Ils cherchent ainsi à changer les représentations associées à ces mots en mettant en exergue certains traits distinctifs par des énoncés à forme définitionnelle.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".