Défigement et traduction intralinguale et interlinguale1
Bibliographic record
Abstract
La reformulation, au même titre que la recherche d’équivalents de séquences figées, pose des problèmes. L’un des recours linguistiques sollicité dans ces cas est le défigement en ce sens qu’il ouvre des paradigmes qui favorisent justement le « dire autrement ». En fait, chaque mot construit et chaque unité polylexicale offrent un dédoublement potentiel par voie de défigement. L’économie du défigement permet, entre autres, à ce procédé d’agir en remontant à chaque fois à l’encodage de l’expression pour en « déverrouiller » les items lexicaux. Dans la pratique de la traduction intra- et interlinguale, le rendement du défigement se vérifie dans des domaines aussi différents que ceux de l’étymologie populaire, de la paraphrase et du jeu de mots par défigement ludique.
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 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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".