Translation Strategies Applied in English-Arabic Translation: A Case of a Website Article
Bibliographic record
Abstract
The current study investigates some distinctive translation strategies applied in the translation of an article about the World Arabic Language Day from English into Arabic. By reviewing literature in that field, the number of studies searching the application of such strategies in translating website articles are few. The applicability of such strategies in the translation of website articles is an important point that is answered in the current study. The analysed document is an article issued by the United Nations Educational, Scientific and Cultural Organization (UNESCO) on 18th December 2021 for the celebration of the Arabic Language Day internationally. The current website article is a sample of articles issued by international organisations in various official languages where English and Arabic are two of them. The researcher investigates the application of Baker's strategies for translation during the translation process. The current research proves that distinctive strategies for translation are applied during the translation process from English into Arabic in website articles genre to enhance comprehensibility. The study also indicates that applied strategies for translation do not change the meaning of the translated text in comparison to the source text. On the contrary, translation strategies enhance explicitness in translated texts.
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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) | 0.002 | 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".