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Record W4293548562 · doi:10.5430/wjel.v12n6p352

The Frequency of the English Language Used in Social Media by Undergraduate English Majors in Jordan

2022· article· en· W4293548562 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWorld Journal of English Language · 2022
Typearticle
Languageen
FieldPsychology
TopicLanguage Acquisition and Education
Canadian institutionsnot available
Fundersnot available
KeywordsArabicSocial mediaCompetence (human resources)English languageMathematics educationComputer scienceSample (material)PsychologyLinguisticsWorld Wide WebSocial psychology

Abstract

fetched live from OpenAlex

The study aims at investigating the frequency and willingness of undergraduate English majors to use English language in social media and informal context. It also aims at discovering frequently used expressions and exploring their functions. The study utilized a questionnaire developed by the researchers based on samples of students’ chats and posts collected from Facebook groups. The questionnaire was distributed to a sample of 100 students majoring English in Al-Hussein bin Talal University to elicit aspects of their views on the use of some common types of English expressions transliterated into Arabic on social media platforms. The results of the study show that transliterated English expressions were widely and commonly used in students’ posts and comments to express different functions, often replacing Arabic alternatives, as English expressions were found to be more expressive. The study concluded with some implications highlighting the role of social media in improving and developing English competence and skills in this technological era.

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.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.276
Teacher spread0.267 · 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