Evaluation of the Outcomes of an Occupational Health and Safety Training Program
Bibliographic record
Abstract
We are evaluating the outcomes of an occupational health and safety training program provided by a Quebec union whose objective is to increase member's ability to participate in injury prevention through union action. In a previous exploratory study we identified the 32 themes of the OHS training program and the learning outcomes pertaining to each of these themes. We used a pretest posttest control group design in order to evaluate the program's outcomes. Questionnaires were distributed to intervention (n=40) and control groups (n=47) whose respective response rates were 100% and 89.4%. We used logistic regression in order to measure the respective effects of OHS program exposure and of the pretest results on the posttest results. In addition, we controlled for the potential confounding effects of the following variables: length of experience as a union delegate or as a member of occupational health and safety committee, previous exposure to an OHS training program, and presence in the delegate's firm of other workers previously exposed to the OHS training program under study. We report on one of the themes of the OHS training program that we identified: the legal right for a worker to refuse to execute a dangerous working activity. The results show that the training on that theme produced most of its expected outcomes.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".