Work-integrated learning and professional accreditation policies: An environmental health higher education perspective
Bibliographic record
Abstract
Free to read on publisher website The introduction of a new work-integrated learning (WIL) policy for university environmental health education programs seeking professional accreditation identified a number of problems. This included how to evaluate the acceptability of differing approaches to WIL for course accreditation purposes and a need to develop an agreed understanding of what constitutes WIL in environmental health. This paper describes a Participatory Action Research (PAR) approach undertaken as an initial step towards addressing these problems. The key recommendation from this research is the need to develop a framework to evaluate approaches to WIL in environmental health. In such a framework, it is argued that a shift in focus from a specified period of time students are engaged in WIL, to greater consideration of the essential pedagogical features of the WIL activity is required. Additionally, input from all stakeholder groups, universities, students, employers and the professional body, is required.
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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 | 0.044 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.033 |
| Scholarly communication | 0.018 | 0.012 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.010 | 0.008 |
| 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 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".