Apologies in EFL: An Interlanguage Pragmatic Study on Moroccan Learners of English
Bibliographic record
Abstract
This study explores the strategies Moroccan Learners of English (MLEs), American English Speakers (AEs)), and Moroccan Arabic speakers (MAs) use when performing the speech act of apology. The study basically investigates the interlanguage of MLE as compared to other groups. Equally important, the aim is to study whether MLEs displayed pragmatic transfer when using apology strategies. To this end, A written discourse completion test/ task was administered to the participants both native and English as a Foreign Language (EFL) learners in order to elicit apologies through five hypothetical situations. The productions of Moroccan EFL learners were analyzed to see where they stand between native speakers norms and Moroccan Arabic norms in terms of strategies choices. In the analysis of the data, all responses were categorized according to Trosborg’s (1995) apology speech act set. The results show that Learners of English in higher education significantly deviated the overall desired strategies as compared to American native speakers of English. Meanwhile, some developmental patterns towards native like norms were perceived.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".