The Translation of Near-Synonymous Names of Allah in the Holy Qur’an: A Comparative Study
Bibliographic record
Abstract
This study aimed to investigate the lexical choices of the near-synonymous names of Allah in the Holy Quran, namely, (الوهّاب ، الرزّاق) , (البارئ ، المصوّر ، الخالق) , (الرءوف ، الودود ، اللطيف) in five English translations which include Muhammad Sarwar's (2011), Pickthall's (1930), Yusuf Ali's (1982), Arberry's (1955), Al-Hilali and Khan's (2018). The meanings of the names of Allah were checked based on the Qur'anic exegeses and the English equivalents selected by the five translators were looked up in Cambridge and Merriam-Webster's Dictionary in order to determine the translation that best provided the closest meanings to the Qur’anic interpretations. The study found that the slight differences in the meanings of the names of Allah were not reflected in the English lexical choices of some translators. The study recommends that translators of religious books should take into account the minor differences between words of similar meaning which are intended for specific purposes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".