Strategies in Forming the Speech Act of Refusals of Non-Native English Speakers and Native English Speakers in Entry-Level Customer Service Positions in Canada
Bibliographic record
Abstract
Being able to refuse -decline requests, offers, invitations or suggestions -is necessary in the workplace.Native English speakers (NES) and non-native English speakers (NNES) often use different strategies to form the speech act of refusals (Riddiford & Holmes, 2015).This study investigates the refusal strategies of NESs (n=5) and NNESs (n=5) in Canadian customer service.Six role-plays were conducted to determine the refusal strategies of both groups.Stimulated recall interviews (SRI) provided insights into the participants' use of these strategies.Role play analysis show both groups use reason/explanation the most.NES formed successful refusals more often than NNES.During the SRIs NES were concerned about workplace expectations, and the difficulty of refusing while NNES voiced justifications for refusing.SRIs also uncovered that NNES and NES may use the same strategy for different reasons.Pedagogical implications for language learners working in customer service are given.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".