The Translation of Al-Haramain (the Two Holy Mosques) Fridays’ Sermons Is Unplanned Language Planning (Management)
Bibliographic record
Abstract
This research has studied the project of translating Al -Haramain Al Shareefain (the Two Holy Mosques) Fridays’ sermons (Jomaa Khutbahs) from Arabic into English from language planning perspectives with its relation to translation, which has been launched by the General Presidency of the Two Holy Mosques and Al- Imam Muhammad Ibn Saud Islamic University represented by the College of Languages and Translation in May 2013. This study has investigated these sermons from the language planning perspectives with its relation to translation. It has identified that the translation of Fridays’ sermons has resulted in an unplanned (indeliberate) language planning process by reviving the archaic and obsolete Arabic words. Translating Fridays’ sermons has led to reusing and disseminating these obsolete words that have not been used for along time.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".