O1E.4 Electronic waste recycling in québec, canada: hiring practices and occupational health and safety management
Bibliographic record
Abstract
Background and objective Electronic waste recycling (e-recycling) has received little attention from an occupational health and safety (OHS) perspective. Our objective was to describe hiring and OHS management practices in a sample of formal e-recycling facilities. Methods Within a cross-sectional study of exposure of e-recycling workers to various contaminants, we conducted semi-structured face-to-face interviews with a sample of 26 workers and 6 managers, employed in four companies. Thematic analyses, followed by a matrix analysis based on the companies’ missions were conducted on the recorded interviews. Results Three companies are small enterprises: one receives young offenders/ex-prisoners for up to six months of vocational internships; another is a private company recruiting its workforce through governmental programs integrating people with chronic health problems; the third, a family business, mainly employs workers within neighbouring communities. Lastly, a medium-sized unionized company recruits its employees through staffing agencies, offering permanent jobs to the best candidates after a three-month trial period. Most participants were male, aged between 20–50 years old, and had not completed high school, except for a few recent immigrants with graduate degrees. Regarding occupational hazards in their workplace, 40% of interviewees reported chemicals, 31% mentioned the danger of being struck by lift trucks, and less than 25% identified toxic vapours, inappropriate protective personal equipments (PPEs), cuts, dusts, musculoskeletal or back pain. Some workers expressed concern about the pace of work (and resulting stress), which they identified as an injury risk factor. None of the participants received any mentoring upon entering the job. Agency workers had inferior wages and did not have access to the same OHS preventive practices or PPEs as regular workers. Conclusions In our sample, OHS management practices varied according to the employment relationship, although workers are exposed to similar working conditions. Working conditions in the growing e-recycling industry need our attention.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".