De l’animalisation à la neutralisation : fonctionnement des verbes de bruit associés aux animaux
Bibliographic record
Abstract
L’article met au centre des investigations les verbes associés aux cris d’animaux et tente de démontrer, en s’appuyant sur des exemples empruntés à des langues diverses que, même si au départ il y a une part d’animalisation du lexique lorsque le domaine cible de la métaphore est l’homme, le côté animal tend à s’estomper et à se neutraliser – au point de perdre son expressivité –, lorsque le domaine cible n’est pas l’homme (partie du corps, objet, élément naturel). Ces deux voies correspondent à deux différents types de métaphorisation (métaphores de ressemblance et de corrélation). L’article met en évidence les trois composants-sources qui sont à la base de métaphorisations vers le domaine des hommes : la capacité à produire des sons, à se mouvoir et à éprouver des émotions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".