(Un)translatability of (Yemeni) Arabic Oath Expressions into English
Bibliographic record
Abstract
Oaths are mostly a culture-embedded linguistic component and this to such an extent that their translation to other languages may be questionable. This study investigates the translation potential or translatability of (Yemeni) Arabic oath expressions into English. It tries to answer whether (Yemeni) Arabic oath expressions (un)translatable into English by examining the syntactic formula of oaths from linguistic and cultural angles in relation to (Yemeni) Arabic and their (closely translated) English oath expressions. A corpus of 1169 oath expressions was created through an online questionnaire. Findings showed that linguistically, there is a very close equivalence between English and Arabic, with respect to oath-making, in both particles and expressions. At the cultural level, there is also some equivalence, which is evident in the original effect that (Yemeni) Arabic oaths retain in their English translation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".