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Record W1567833041

Translating Contextualized Arabic Euphemisms into English: Socio-Cultural Perspective

2014· article· en· W1567833041 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCross-cultural communication · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSwearing, Euphemism, Multilingualism
Canadian institutionsnot available
Fundersnot available
KeywordsEuphemismArabicContext (archaeology)LinguisticsPropositionMeaning (existential)Perspective (graphical)SociologyPoint (geometry)PsychologyHistoryComputer sciencePhilosophyArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

This study examines the role context plays in determining the translation strategies pursued by translators of Arabic euphemisms into English. Due to different cultural backgrounds, adherence to the employment of euphemism in a social context may differ in both Arabic and English. While some situations call for the use of euphemism in one culture, the other culture finds no point in using such euphemisms for such situations; preserving the original Arabic euphemisms when rendered into English in this case could lead to misunderstanding and may deprive the Source Language (SL) from a cultural trait. The study derives evidence from 11 Arabic euphemistic expressions taken from five literary masterpieces written by the Egyptian novelist and Noble Prize winner Najib Mahfouz, and it looks into the English translation of these euphemisms. The present study attempts to advance the proposition that Arabic euphemisms in their context  exhibit fluctuating, unstable meaning, which emanates from various contextual factors such as speakers, addressees, shared knowledge and background information, and hence these factors combined dictate on translators the chosen translation strategy.

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.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.217
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.002
Scholarly communication0.0010.002
Open science0.0010.000
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 head0.039
GPT teacher head0.404
Teacher spread0.365 · 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