Reported harassment and mental ill-health in a Canadian prospective cohort of women and men in welding and electrical trades
Bibliographic record
Abstract
OBJECTIVES: Experience of psychosocial environments by workers entering trade apprenticeships may differ by gender. We aimed to document perceived harassment and to investigate whether this related to mental ill-health. METHODS: Cohorts of workers in welding and electrical trades were established, women recruited across Canada and men from Alberta. Participants were recontacted every 6 months for up to 3 years (men) or 5 years (women). At each contact, they were asked about symptoms of anxiety and depression made worse by work. After their last regular contact, participants received a "wrap-up" questionnaire that included questions on workplace harassment. In Alberta, respondents who consented were linked to the administrative health database that recorded diagnostic codes for each physician contact. RESULTS: One thousand eight hundred and eighty five workers were recruited, 1,001 in welding trades (447 women), and 884 in electrical trades (438 women). One thousand four hundred and nineteen (75.3%) completed a "wrap up" questionnaire, with 1,413 answering questions on harassment. Sixty percent of women and 32% of men reported that they had been harassed. Those who reported harassment had more frequently recorded episodes of anxiety and depression made worse by work in prospective data. In Alberta, 1,242 were successfully matched to administrative health records. Those who reported harassment were more likely to have a physician record of depression since starting their trade. CONCLUSIONS: Tradeswomen were much more likely than tradesmen to recall incidents of harassment. The results from record linkage, and from prospectively collected reports of anxiety and depression made worse by work, support a conclusion that harassment resulted in poorer mental health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".