Bibliographic record
Abstract
This chapter focuses on the role of the mentor the context of a modern language institution. It looks at two strands of mentorship: within the organization and while interacting with the wider ELT world. In the first context the authors look at the various functions a mentor is expected to perform with a particular focus on the scheme as it exists in Centre of English Studies in the UK and Ireland. Here we have a comprehensive mentor program in operation for the summer quarter of the year with weekly sessions and comprehensive support provided. For the other three quarters of the year, the mentor role is more ad-hoc, with a flexible program and timetable dictated by the teachers' needs. In both of these situations, the mentor has to play a number of key roles and be relatively proficient in these. In terms of the role of the mentor in an external context, this chapter looks at the role of mentor in the Irish Research Scheme for Teaching, a national research scheme aimed at promoting academic quality through research in Ireland.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.020 | 0.013 |
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".