La multiplicité des chemins dénominatifs
Bibliographic record
Abstract
Dans cet article, nous examinons le rôle clé qu’exerce la motivation dans la dénomination en terminologie et nous suggérons que la synonymie présente dans les textes spécialisés peut être expliquée comme le résultat d’une motivation multiple accompagnant l’acte dénominatif. En premier lieu, nous reprenons quelques idées sur la formation des concepts, la dénomination et le rapport concept-terme formulées par les différents courants terminologiques. En second lieu, nous réalisons une analyse sémantique des variantes dénominatives détectées dans un corpus textuel bilingue français-galicien du domaine de la conchyliculture afin de montrer de quelle manière la dénomination ouvre l’accès à la compréhension du concept et comment les différentes variantes dénominatives constituent des points de vue complémentaires sur un même concept. Finalement, nous présentons les possibilités qu’une telle analyse peut offrir pour avancer dans la description et l’explication de la dénomination et de la variation dénominative.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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.
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".