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Record W2295785894 · doi:10.5539/ijel.v6n1p38

Problems in English to Arabic Subtitles Translation of Religious Terms—Bruce Almighty and Supernatural on MBC & Dubai One: A Case Study

2016· article· en· W2295785894 on OpenAlexvenueno aff
Ahmed Abdel Azim ElShiekh

Bibliographic record

VenueInternational Journal of English Linguistics · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsComicsArabicSpace (punctuation)LinguisticsSociologyLiteratureHistoryPsychologyPhilosophyArt

Abstract

fetched live from OpenAlex

<p>This paper attempts to shed light on some cultural and/or technical problems in the translation of religious terms from English into Arabic in the subtitles of movies, with particular reference to some Arab Gulf countries channels. Due to limitations of time and space, the researcher has taken two particular channels as representative, namely MBC Channel group and Dubai One. The data of the research have been collected from one film and one TV series as quite typical examples of works that may lead to serious problems in the subtitles translation with regard to religious terms. In both cases, the use of religious terms is not only obligatory but also focal. The researcher points the discrepancies in the choice of Arabic equivalents for the English religious terms in question as well as explores the possible reasons of and recommended solutions to such cultural problems in translation. The film, <em>Bruce Almighty</em>, is a light and comic treatment of the phenomenon of well-educated yet vain young men, doubting the wisdom of God Almighty. Jim Cary plays the role of the young man, while Morgan Freeman actually plays God! Hence, there is no easy way out of the necessity of tackling the problem of translating the religious terms involved. As for the TV series, <em>Supernatural</em>, the whole episode deals with God, angels, demons and Satan. It remains to be said that this paper does not claim to give decisive answers to the questions posed by the research, but only aspires to pave the way before further research on the topic and related issues.</p>

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)0.005
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: Empirical
Teacher disagreement score0.982
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
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)0.0000.000

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 head0.052
GPT teacher head0.302
Teacher spread0.249 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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