Health and safety of students in vocational training in Quebec: a gender issue?
Bibliographic record
Abstract
Health and safety issues in a vocational training center were explored in this study. Several sources and methods were used: group interviews with students in traditionally female [F] and male [M] trades, i.e. hairdressing (7 F) and automated systems electromechanics (8 M, 1 F); self-administered questionnaires on injuries sustained at the school; observations of activities in these programs; and analysis of ministerial documents. Findings indicate that the partially divergent ways that OHS is addressed in these programs cannot be explained only by the specific characteristics of the two trades. Some aspects put female students in hairdressing at a disadvantage: status accorded to OHS in the study programs, learning activities, and conditions for learning and managing prevention and injuries. The discussion focuses on a gender-differentiated analysis, the importance of improving the way OHS is addressed in the programs, in particular, those primarily involving female students, and the need to pursue research. In addition, the results from individual interviews with women (5 F) training for non-traditional trades lead to discussion on the interrelated effects of sex-based gender and professional gender.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".