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Record W4396966917 · doi:10.5430/wjel.v14n5p505

Anglicisms in Omani Arabic: A Study on the Use, Status, and Perception of English Loanwords

2024· article· en· W4396966917 on OpenAlexvenueno aff
Ali Algryani, Syerina Syahrin

Bibliographic record

VenueWorld Journal of English Language · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsnot available
Fundersnot available
KeywordsArabicPerceptionLinguisticsComputer sciencePsychologyPhilosophy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.029
GPT teacher head0.249
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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