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Record W4283171104 · doi:10.5430/wjel.v12n5p356

The Religiosity of Translator: Is it an Echo of the Heart or the Mind?

2022· article· en· W4283171104 on OpenAlexvenueno aff
Ahmad Mustafa Halimah

Bibliographic record

VenueWorld Journal of English Language · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicJewish Identity and Society
Canadian institutionsnot available
Fundersnot available
KeywordsReligiosityPerspective (graphical)IslamArabicEcho (communications protocol)LinguisticsEpistemologyPsychologySociologyComputer scienceSocial psychologyPhilosophyArtificial intelligenceTheology

Abstract

fetched live from OpenAlex

This article offers a critical appraisal of the daynunah [religiosity] of the mind and its manifestation in the work of the English-Arabic-English translator. It is an attempt to provide a novel concept of the mind and its religiosity from an Islamic socio-cultural-psychological perspective and then apply it to a translator and investigate whether their translation is the echo of the heart or mind. English-Arabic-English translation examples from media translated texts were used for analysis and discussion. Results of the analysis and discussion have indicated that the religiosity of the translator resonates the echoes of the heart more than those of the mind and that there is an urgent need for guidelines to allow translators to work in a more balanced and unbiased manner. Researchers in other fields of knowledge could also apply this new concept to, for example, the religiosities of academics, doctors, scientists, lawyers, businessmen and politicians.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.022
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.071
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0070.025
Scholarly communication0.0080.009
Open science0.0010.004
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.302
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2022
Admission routes1
Has abstractyes

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