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Record W4392815708 · doi:10.5430/wjel.v14n3p347

Subtitling Cross-Cultures: Unveiling Audience Reactions to the Subtitling of the Iraqi Action Movie "Mosul" into English

2024· article· en· W4392815708 on OpenAlexvenueno aff
Shaima Alrais, Zakaryia Almahasee

Bibliographic record

VenueWorld Journal of English Language · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicSubtitles and Audiovisual Media
Canadian institutionsnot available
Fundersnot available
KeywordsAction (physics)Computer scienceAdvertisingComputer securityPolitical scienceBusinessPhysics

Abstract

fetched live from OpenAlex

This study scrutinizes how the viewers reacted to the Iraqi Action Movie "Mosul," subtitled into English. The study designed a questionnaire of 22 items and disseminated it to undergraduate and postgraduate students who are specialists in English Language and Translation studies at three Iraqi Universities. They were asked to watch the subtitled version of the Iraqi dialect movie Mosul. They responded to a 21-item questionnaire of five constructs, mainly movie-watching habits, Iraqi vernacular, technical aspects, Comprehensibility, attitudes, and future recommendations. The analysis revealed that the participants responded positively to the interlingual subtitling of Iraqi vernacular action movies into English. The study analysis showed statistically significant evidence that people prefer to watch Iraqi movies subtitled interlingually into English than those subtitled interlingually in Modern Standard Arabic.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.896
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0000.001
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 head0.025
GPT teacher head0.308
Teacher spread0.283 · 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 designQualitative
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

Citations1
Published2024
Admission routes1
Has abstractyes

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