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Record W2146170710 · doi:10.5539/ijel.v3n4p107

Color Idiomatic Expressions in the Translation of Naguib Mahfouz’s Novel “The Thief and the Dogs”: A Case Study

2013· article· en· W2146170710 on OpenAlexvenueno aff
Jamal Azmi Salim, Mohammad Issa Mehawesh

Bibliographic record

VenueInternational Journal of English Linguistics · 2013
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
FundersZarqa University
KeywordsMeaning (existential)LinguisticsArabicWhite (mutation)Translation (biology)Color termAssociative propertyPsychologyCommunicationComputer scienceMathematicsPhilosophyPure mathematicsChemistryMessenger RNA

Abstract

fetched live from OpenAlex

Colors play a vital role in people’s communication. They do not only express the colors themselves, but are also endowed with cultural characteristics of each nation. In other words, colors in different languages and cultures may convey different associative meaning and people from different cultures react to colors in different ways. The aim of this study is to investigate the translation of color idiomatic expressions from Arabic into English in Naguib Mahfouz’s novel “The Thief and the Dogs” and to what extent is color idiomatic expressions retained, wasted and distorted. Moreover, the study aims at exploring the different translation strategies applied in translating color idiomatic expressions in this novel and finding out the similarities and differences between their meaning in both languages. The study mainly focuses on the most common colors: black, white, yellow, red, green and blue. For the purpose of the study, a number of Arabic idiomatic expressions along with their equivalents in English were gathered from the novel and were contrastively studied side-by-side with their translations.

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)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.011
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 head0.032
GPT teacher head0.331
Teacher spread0.299 · 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.

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

Citations19
Published2013
Admission routes1
Has abstractyes

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