Bibliographic record
Abstract
BACKGROUND: Despite its relevance to medical practice, occupational medicine has been poorly represented in undergraduate training. This article describes a model for the teaching of occupational medicine to student doctors. METHODS: The model comprises two didactic lectures, a student-selected component (SSC) of five interactive two-hour sessions and one occupational medicine objective structured clinical examination (OSCE) station in the final MB ChB clinical exam. Interested final-year students are invited to join the SSC. In session 1, students discuss the scope of occupational medicine practice, which includes a job title-occupational illness quiz, the use of environmental measurements and audiovisual recordings of selected workplaces. Sessions 2-4 involve visits to workplaces such as a laundry, a foundry and a bakery, during which students are asked to record relevant hazards to health, their controls, health effects and how occupational causality might be determined. The final session allows students to present their findings and gain feedback from the occupational physicians and their peers. Occupational medicine has been poorly represented in undergraduate training RESULTS: Twenty-seven student doctors chose to undertake the SSC in three cycles. Students appreciated the relevance of the specialty and the opportunity to systematically evaluate workplaces. Eighty per cent of all final-year medical students (n = 250) passed the occupational medicine station in the OSCE in 2014. CONCLUSIONS: This model for the teaching of occupational medicine links work and medical practice at three stages of undergraduate training and could be adopted by all medical schools. The SSC gave students skills for undertaking illness prevention, workplace evaluation and risk assessment that they had not previously encountered.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 0.008 |
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".