The Pragmatics of Making Requests in the L2 Workplace: A Case Study of Language Socialization
Bibliographic record
Abstract
The workplace is one of many sociocultural contexts where novices within a culture, like immigrant women, become socialized into new discourse systems and cultures. As second language (L2) speakers, the process of language socialization in the workplace involves double socialization: as a novice in a new work environment and as novice operating within a new language and culture. Focusing on L2 requesting behaviour, this ethnographic case study deals with the important issue of the pragmatics of higher-stakes social communications. The contextualized examples provided here illustrate how, through exposure and participation in social interactions and with the assistance of experts or more competent peers, an immigrant woman came to internalize target language and cultural norms and develop communicative competence in ESL in the workplace. More specifically, she learned to make requests more directly than she had been accustomed by adopting certain sociolinguistic strategies and expressions. The research on which this paper is based represents a new direction in TESOL workplace-oriented research, combining interlanguage pragmatics, ethnography, and language socialization.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.017 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.004 |
| 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".