Gender Differences in Using Apology Strategies in Jordanian Spoken Arabic
Bibliographic record
Abstract
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.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".