Anglicisms in Omani Arabic: A Study on the Use, Status, and Perception of English Loanwords
Bibliographic record
Abstract
The growing dominance of English in fields such as education, technology, business, culture, and politics across the globe has contributed to the existence and spread of Anglicisms in world languages. The use of anglicisms, English loanwords, is a global phenomenon that has a significant impact not only on international communication exchanges but also on people's native languages. Modern varieties of Arabic, including Omani Arabic, are no exception to this growing trend. This research is an attempt to investigate the status of Anglicisms in Omani Arabic. The aim is to determine the factors promoting the use of Anglicisms in day-to-day interactions and people's attitudes towards them. As a method of data collection, the study used focus group discussions that included seventy undergraduate students. The findings of the study showed that anglicisms are consistently used by young Omanis in face-to-face and virtual interactions. Furthermore, the findings revealed that a large number of anglicisms have undergone morphological and phonological adaptation and thus been incorporated into the lexicon of Omani Arabic. This rising trend of anglicisms can be attributed to certain factors including a) the influence and prestige of Anglo-American culture, b) the influence of information and communication technology, c) the internationalization of education, d) lexical voids in the native language, and e) conciseness and expressiveness of English loanwords. Finally, apart from some voices against the unnecessary use of anglicisms in the language, the younger generation seems to accept and have a positive attitude towards the use of English loanwords in day-to-day interactions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".