Comment le sous-titrage et le doublage peuvent modifier la perception d’un film
Bibliographic record
Abstract
Avec les longs métrages célèbres, devenus même parfois films-cultes, la question de la traduction (principalement sous la forme de versions sous-titrées ou doublées) se pose de façon d’autant plus pertinente que les critiques et les spectateurs ont souvent tendance à amalgamer film original et versions traduites. Il semble donc important de réévaluer ces traductions et leur influence sur la réception d’un film. À partir d’une analyse contrastive détaillée de la version originale du film de Kazan, A Streetcar Named Desire (1951) et deux de ses versions (sous-titrée et doublée en français), je me propose d’exposer les répercussions des choix respectifs faits par les traducteurs sur deux aspects majeurs dans la signification esthétique et symbolique du film, à savoir la présentation des personnages et leurs relations ainsi que les questions de transferts culturels.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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 teacher head, 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".