“Ahyaanan I text in English ‘ashaan it’s ashal ”: Language Crisis or Linguistic Development? The Case of How Gulf Arabs Perceive the Future of their Language, Culture, and Identity
Bibliographic record
Abstract
Gulf Arabs are perceived as the most advanced of the Arabs in terms of state wealth, living standards, quality of life, education, and literacy levels for both men and women and overall opportunities availed to them by virtue of being citizens. In order for this advancement to have taken place the Gulf had to find a way of educating its people to international standards. One such way was the introduction of English in the education system at all levels and most importantly in higher education. Foreign workers from Europe, America, Canada, and Australia were brought in to assist in this moderni- zation process and the language of common communication became English. After two or three decades, there are now calls to revive Arabic and reduce the ef fect and impact of English, not only in the education system but in the everyday lives of Gulf Arabs, where the use of English in non-formal situations has become the norm. Some quarters are claiming that the Arabic language is at the beginning of its death and soon will have no speakers, if English continues to be promoted over Arabic, in the media, through domestic South Asian maids and nannies, and in the education system.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".