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Record W2998434888 · doi:10.5539/elt.v13n1p190

Translating the Islamic Religious Expressions in Taha Hussein’s Novel ‘Al Ayaam’ by E. H. Paxton

2019· article· en· W2998434888 on OpenAlexvenueno aff
Ibrahem Bani Abdo, Banan Manzallawi

Bibliographic record

VenueEnglish Language Teaching · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Linguistic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArabicIslamDomesticationDomestication and foreignizationIslamic cultureRendering (computer graphics)Equivalence (formal languages)SociologyPsychologyLinguisticsTheologyPhilosophyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Translating religious expressions from Arabic into English seems problematic where the cultural backgrounds must be known for the translator to choose the appropriate equivalence and to help bridging the cultural gap between two cultures. As a result, this paper investigates to what extent have Venuti’s strategies (domestication and foreignization) been successfully implemented in rendering the religious expressions in Taha Hussein’s The Days (الأيام alʾayām) by E. H. Paxton in the translating process. It also asserts the challenges involved in translating the Islamic religious expressions in this novel. Consequently, this paper has randomly chosen, discussed, and compared 10 Islamic expressions of Hussein’s novel with their English equivalents. In addition, two Arabic raters were consulted. Venuti’s (2004) domestication and foreignization method was used to analyse these examples. The study concludes that the translator uses the two methods in rendering the religious expressions. The foreignization strategy was used more than domestication. Six examples have been foreignized; whereas, four of them were domesticated. The study also reveals that the use of both strategies supplements and supports the translation accuracy. Finally, the different cultural backgrounds, religions, expressions, costumes, traditions have to be the ultimate concerns of the translators in translating the Arabic religious expressions into English language.

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)0.003
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 score0.510
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.284
Teacher spread0.275 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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