Pragmatics in the Post-TESL Certificate Course "Language Teaching for Employment"
Bibliographic record
Abstract
For those immigrants to Canada who need some language training in order to access employment in their field, occupational ESL classes have been available in Ontario for several years. Recent additions to Occupation-Specific Language Training and Bridging programs, as well as a new emphasis on work-related content in LINC classes, have created a need for trained instructors for this area of ESL. The Language Training for Employment (LTE) is a Post-TESL Certificate course that addresses this need. Within the course, Pragmatics is 1 of 12 units— one that participants have little knowledge of or practice with before the course, and 1 of 2 units that receive unanimously positive feedback from participants at the end. This article explains the conceptual framework of LTE, the content of the Pragmatics Unit, its implementation and participant feedback.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".