Paratraduire l’imaginaire : approche méthodologique du sous-titrage espagnol des films ocelotiens
Bibliographic record
Abstract
Cet article présente une nouvelle perspective de l’utilisation pratique de la paratraduction comme outil méthodologique et est construit autour de trois axes principaux. Dans un premier temps, nous aborderons la notion de paratraduction et son rapport avec l’imaginaire, puis nous démontrerons l’importance de l’image et des liens intersémiotiques qui se tissent entre les éléments visuels, sonores, verbaux et filmiques dans le texte audiovisuel afin de construire le sens symbolique. Dans le cadre de la paratraduction, nous proposerons une approche méthodologique holistique du traitement de l’image à l’écran apte à rendre compte de la complexité sémiotique du message audiovisuel et du sens symbolique. Finalement, nous appliquerons cette analyse au sous-titrage espagnol d’un corpus de films d’animation.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 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".