A Critique of Jabra’s Arabic Translation of Shakespeare’s The Tempest
Bibliographic record
Abstract
This study critiques and evaluates Jabra's translation of The Tempest into Arabic. This translation poses a lot of problems stemming from the differences between English and Arabic, the difficulty and ambiguity of the original text, and the translator's approach. The discussion demonstrates the great efforts made by the translator to convey the equivalent meanings of the text. It also clearly shows that Jabra's translation is literal, that the translator sometimes uses colloquial, inaccurate, and nonpoetic words that add to the ambiguity of the text, that he sometimes gives good translations, that he makes slight mistakes, and that he sometimes deletes or drops words or lines from the text, which represents a flagrant violation of the ethics of translation. Despite the pitfalls, Jabra's translation of The Tempest is the fruit of hard work deserving of praise and appreciation. The mistakes made are ascribed to the difficulty of translating literature whose language consists of figures of speech that defy translation.
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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 | 0.016 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.024 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".