Teaching Pragmatic Competence: A Journey from Teaching Cultural Facts to Teaching Cultural Awareness
Bibliographic record
Abstract
Pragmatic competence is one of the essential competences taught in the second language classroom. The Canadian Language Benchmarks (CCLB, 2012a), the standard document referred to in any federally funded program of ESL teach- ing in Canada, acknowledges the importance of this competence, yet at the same time notes the limited resources available to help ESL teachers address it in the classroom. Informed by the theoretical construct of communicative competence and its application to second language learning, the article offers an exemplar of the whats and hows of teaching pragmatics in the ESL classroom. The article stresses the importance of making explicit to the learners the sociolinguistic and sociocultural variables that underlie native speakers’ linguistic choices. It is hoped that ESL learners will thus develop a better understanding of the reasons that make native speakers choose one linguistic expression rather than others when performing a certain linguistic act. The speech act of complimenting is used here as an exemplar.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.017 | 0.047 |
| Scholarly communication | 0.026 | 0.015 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.012 |
| 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".