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On English and Chinese Movie Title Translation

2009· article· en· W2123565459 on OpenAlexvenueno aff
Ke-lan Liu, Wei Xiang

Bibliographic record

VenueCanadian social science · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsAlienationEntertainmentMovie theaterHollywoodArgument (complex analysis)Assimilation (phonology)GlobalizationImitationComputer scienceSociologyLiteratureLinguisticsMedia studiesAdvertisingHistoryArtPolitical sciencePsychologyVisual artsLawPhilosophySocial psychologyArt history

Abstract

fetched live from OpenAlex

Movie is not only a popular form of entertainment but also an important medium in inter-cultural communication. More and more communication between Chinese and English movies goes with the globalization. As a result, movie translation has become more and more important, especially title translation. However, there are many problems in movie title translation. In the hope of improving the present situation, this paper makes a study on how to translate English and Chinese movie titles. With many title translations as examples, the paper analyzes the characteristics of movie titles and focus on the problems in Chinese and English movie title translation, and concludes that there are three main problems, the messy and low-quality situation, the argument between alienation and assimilation, and over-imitation to Hollywood blockbusters’ translation modes. This paper analyzes the examples and tries to find the reasons for each problem. Finally, suggestions are given on how to solve the problems, that translators should consider the individuality and characteristics of the original movie and consult the cultural backgrounds to keep the informatic, aesthetic and commercial functions in balance. So that readers can get a general idea about the situation of movie title translation and pay enough attention to movie title translation, and to improve the situation. Key words: movie title translation, alienation and assimilation, over-imitation Resume: Le cinema est non seulement une forme artistique preferee des gens, mais aussi un media tres important des echanges interculturels. Sous l’influence de la globalisation, les echanges internationaux de films deviennent de plus en plus frequents, la traduction des films parait alors de plus en plus importante, en particulier celle des titres des films. Mais il existe aujourd’hui beaucoup de problemes dans le domaine de la traduction des titres des films. L’auteur a fait des recherches sur la traduction. En citant de nombreux exemples, on a analyse les caracteristiques des titres des films chinois et anglais, les problemes qui existent dans la traduction dont les trois problemes principaux : celui de la confusion et de la mauvaise qualite de la traduction ; celui du debat de l’assimilation et de la dissimilation ; celui de l’imitation excessive du modele de la traduction des films hollywoodiens. On a aussi analyse selon ces exemples leurs origines. Enfin, on a donne quelques propositions pour resoudre ces problemes, c’est-a-dire, les traducteurs doivent, pour maintenir l’equilibre des fonctions informatique, esthetique et commerciale des titres traduits, trouver la meilleure traduction en tenant compte des caracteristiques individuelles des films et de la difference des circonstances culturelles chinoise et anglaise. Cet article a pour le but d’aider a mieux comprendre la situation actuelle de la traduction des titres des films, de susciter l’attention de sa traduction et d’elever la qualite de la traduction. Mots-Cles: traduction des titres des films, assimilation et dissimilation, imitation excessive, fonctions informatique, esthetique et commerciale

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.030
GPT teacher head0.266
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2009
Admission routes1
Has abstractyes

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