Bibliographic record
Abstract
Pour traduire, il faut d'abord comprendre. Maisÿÿomprendre quoi ? Il est loin d'être suffisant de comprendre uniquement les signifiés car, appartenant à la langue et faisant partie d'un ensemble structuré, les signifiés ne nous fournissent que des virtualités sémantiques. C'est plutôt le sens qu'il faut comprendre et traduire. Le sens est la base de la fidélité authentique d'une traduction. La compréhension du sens se fait généralement par une analyse des contextes : contexte verbal immédiat, qui aide à lever la polysémie des signes ; contexte verbal élargi, qui permet de désigner le sens d'un énoncé, et contexte situationnel, qui est indispensable pour saisir le vouloir-dire du traducteur. Ces contextes sont nécessaires pour la compréhension, mais aussi pour la traduction. Le traducteur doit donc dépasser la limite de la langue et effectuer ses analyses dans le domaine de la parole.
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 | 0.002 | 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 | 0.002 | 0.007 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".