Bibliographic record
Abstract
Incorporating occupational health content into the medical school curriculum is an ongoing challenge. In 1994, the Ontario Medical Association Section of Occupational and Environmental Medicine gathered together groups with an interest in clinical workplace health including government, universities, hospitals, research organizations and organized labour. A needs assessment was conducted and documented gaps in knowledge, skills and training related to workplace health. An occupational medicine physician (G.L.) was appointed and funded through a provincial educational project, the Physician Education Project in Workplace Health. The Workplace Safety and Insurance Board (WSIB) undertook a survey that documented the lack of educational activities in several of the five medical schools in Ontario. As a result of the needs assessment and survey of medical schools, the WSIB developed the Workplace Health Champions Program (WHCP). The WHCP supports Ontario medical schools to enhance and expand their curricula in occupational health. Starting in 1999 the five (and then six) medical faculties in Ontario signed agreements with the WSIB agreeing to: (i) develop and implement a workplace health curriculum to support medical training in workplace health issues primarily at the undergraduate education level, (ii) select a physician as Workplace Health Champion (WHC) to assist in the development and implementation of a workplace curriculum, (iii) keep the WSIB informed of the progress and impacts of the curriculum in the training programme and (iv) participate with the WSIB in an evaluation of the curriculum and its impact on the training of new physicians.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.004 |
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".