TRANSLATION STRATEGIES IN EUROPEAN AND CANADIAN FRENCH VERSIONS OF AN ANIMATED MOVIE’S ORIGINAL SOUNDTRACK
Bibliographic record
Abstract
RÉSUMÉ. Comme un processus qui implique plusieurs langues, traduction peut être appliquée à diverses formes de médias, tels que des films, des livres et des chansons. Dans les traductions de film, ce processus parfois inclut non seulement les dialogues, mais aussi les chansons (bande originale). Cette étude vise à décrire l’application de stratégies de traduction dans deux versions françaises (européenne et canadienne) de bande-son de The Lion King II: Simba’s Pride. Les chercheurs utilisent deux théories de stratégies d’application : traduction de la poésie (Lefevere, 1975) et traduction sur le plan lexical (Baker, 1992). Après l’analyse, les auteurs prennent une conclusion que les résultats variés de la traduction sont fortement influencés par interprétation et aucun problème de non-équivalence ne se trouve. Mots-clés : bande-son, dessins animés, paroles, stratégies de la traduction. ABSTRACT. As a process that involves more than one language, translation can be applied in various forms of media, such as film, books and songs. In movie translations, this process sometimes includes not only the dialogues, but also the songs (original soundtrack). This study aims to describe the application of translation strategies in two French versions (European and Canadian) of The Lion King II: Simba’s Pride’s original soundtrack. The authors use two theories of translation strategies: Lefevere’s poetry translation (1975) and Baker’s word-level translation (1992). After the analysis was done, the author concluded that the various results of translation were heavily influenced by interpretation, but that no non-equivalence problem was found however. Keywords: cartoon, lyrics, soundtrack, translation strategies.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".