The Untrodden Way: Unexplored Challenges in Poetry Translation
Bibliographic record
Abstract
While much ink has been spilled over the various issues involved in poetry translation by both Western and Eastern translation theorists, it seems no attention has been given to the unknown obstacles a translator may encounter in rendering Arabic literary texts in general and Omani poems in particular. To this end, the current paper sheds light on unknown and unfamiliar problems translators face in translating Omani poetry and maintains that—in addition to the linguistic, cultural, and aesthetic problems of poetry translation—literary translators also encounter difficulties in the translation of unnoticeable religious and cultural meanings and aspects in poems. For this purpose, an interview with an Omani translator and a questionnaire to 35 students with a Translation major (10 males and 25 females) at Sultan Qaboos University served as research instruments to identify unknown problems in translating Omani poetry. Given the results, the paper concludes with a recommendation that poetry translators provide footnotes to translate religious terms and explain unclear or unfamiliar religious phrases.
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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 | 0.066 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.035 |
| Scholarly communication | 0.020 | 0.028 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".