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Record W3078831761 · doi:10.5539/ijel.v10n6p54

Gender Differences in Using Apology Strategies in Jordanian Spoken Arabic

2020· article· en· W3078831761 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

VenueInternational Journal of English Linguistics · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsArabicPsychologyRealization (probability)UtteranceSpeech actQualitative propertySocial psychologyLinguisticsComputer scienceStatistics

Abstract

fetched live from OpenAlex

This study investigated apology strategies used in Jordanian spoken Arabic. The main purpose was to find whether gender plays a role in selecting apology strategies related to different situations. A modified version of Harb’s discourse questionnaire was employed for collecting the data. The participants included 20 males and 20 females. The data were codified and classified using Cross-Cultural Speech Act Realization Patterns (CCSARP), by Blum-Kulka and Olshtain (1984). Both qualitative and quantitative approach was used in analysing the collected data. The findings of the study demonstrate that there are more similarities than differences between females and males in the use of apology strategies. In addition, it was found that both groups tend to use multiple apology strategies in the same utterance; however, their strategies vary in frequency. The results demonstrated that there is no substantial quantitative difference in the use of apology strategies between Jordanian males and females. Further research employing a multi-factor framework (age, gender, education) of addressees is needed.

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)0.000
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score0.894

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.007
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 head0.105
GPT teacher head0.330
Teacher spread0.224 · 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