Reported harassment and mental-ill health in a Canadian prospective cohort of women and men in welding and electrical trades
Bibliographic record
Abstract
Abstract Introduction 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 re-contacted every six 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 which recorded diagnostic codes for each physician contact. Results 1885 workers were recruited, 1001 in welding trades (447 women) and 884 in electrical trades (438 women). 1419 (75.3%) completed a ‘wrap up’ questionnaire, with 1413 answering questions on harassment. 60% 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 1242 were successfully matched to administrative health records. Those who reported harassment were more likely to have a physician record of depression since starting in 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. What is important about this paper? In this study we show that the majority of women entering the male-dominated trades of welding and electrical work report harassment, particularly during their apprenticeship, that is largely from co-workers and has a sexual component. Through its longitudinal design and linkage to an administrative health database, the study has reduced the impact of reporting bias and produced credible evidence that reported harassment is associated with anxiety and depression made worse by work and with physician reported depression. There is increasing recognition that workplace harassment of any worker is unacceptable, with obligations on the employer to take action to eliminate it. Evidence of ongoing mental health impacts reinforces this obligation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".