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Record W2046547812 · doi:10.5539/ijel.v3n2p54

The Generic and Registerial Features of Facebook Apology Messages Written by Americans and Jordanians

2013· article· en· W2046547812 on OpenAlexvenueno aff
Basem Ibrahim Malawi Al-Raba’a

Bibliographic record

VenueInternational Journal of English Linguistics · 2013
Typearticle
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsnot available
Fundersnot available
KeywordsParagraphArabicPsychologyLinguisticsSociocultural evolutionDiglossiaVariation (astronomy)PerceptionUniversality (dynamical systems)Social psychologyComputer scienceSociologyWorld Wide Web

Abstract

fetched live from OpenAlex

This paper aims at investigating the generic and registerial features of Arabic and English apology messages written on Facebook by Jordanian and American university students. The data collected by means of distributing a simulated written paragraph to the participants via Facebook consist of one hundred Arabic and English messages (fifty Arabic and fifty English). The results demonstrate that Arabic and English apology messages written on Facebook share the same communicative purposes, but differ with respect to the number of moves and the lexical and stylistic choices employed by both the Jordanian and American students. The findings of this study have been attributed to the universality of expressing apology, diglossia of Arabic, and to a variation in the subjects’ linguistic and sociocultural backgrounds and perceptions.

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)0.000
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.904
Threshold uncertainty score0.697

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.006
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.263
Teacher spread0.251 · 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 designNot applicable
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

Citations0
Published2013
Admission routes1
Has abstractyes

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