Bibliographic record
Abstract
Cette communication est l’oeuvre d’un praticien devenu enseignant, puis chercheur. Parce qu’il existe des traductions sans traducteurs et que les traducteurs se limitent de moins en moins à la traduction, nous pensons qu’une traductologie proactive doit choisir entre ces deux pôles et, en l’occurrence, se construire autour des problèmes concrets rencontrés par les traducteurs : comment s’agencent, pour les praticiens, les questions de la confiance, des différentiels de savoir, de l’erreur, de la transparence des textes. En assumant l’impureté consubstantielle à cette profession, on parviendra ainsi à une réflexion opératoire sur la mise en cycle des savoirs, l’hybridation et le dialogue des disciplines. Nous explorons, exemples à l’appui, deux de ces dialogues possibles entre, d’une part, la traduction pragmatique et, d’une part, la terminologie et narratologie. Familier des espaces liminaires, le traducteur est ainsi idéalement placé pour se livrer à un ensemble de raisonnements aux limites, qui pourront à bon droit sembler simplistes, mais dont le caractère opératoire est attesté par une pratique.
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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.030 |
| Scholarly communication | 0.017 | 0.018 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".