Bibliographic record
Abstract
This study investigated the strategies monolingual Saudi Arabian adults (MSAAs), Saudi EFL adult learners (SEFLALs), and native speakers of English (ENSs) used when complaining. Another related aim was investigating whether SEFLALs displayed pragmatic transfer when using complaint strategies. A total of 183 written responses were collected from MSAAs, SEFLALs, and ENSs via a three-item discourse completion task (DCT) were analyzed. Findings revealed the strategies used by the study participants when performing the speech act of complaints. First, hints, request and annoyance were the most frequently used strategies by MSAAs, SEFLALs, and ENSs. Second, there were no statistically significant differences among MSAAs, SEFLALs, and ENSs in using the strategy of direct accusation which consistent with the concept of positive pragmatic transfer. Third, hints, behavioral blame, request and indirect accusation were cases of weak negative pragmatic transfer as employed the SEFLALs in the current study. Fourth, modified blame was consistent with concept of strong negative pragmatic transfer. Finally, the last two strategies; annoyance and threat were consistent with no transfer, that is, SEFLAL employed these two strategies as ENSs.
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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 | 0.005 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".