Ironclad work overload: Prevention of psychosocial hazards among union counsellors in Quebec
Bibliographic record
Abstract
The role of labour union staffers-as-workers, crucial to the functioning of a union, involves a growing number of increasingly complex demands and requirements. A Quebec union concerned about the health of its members, union counsellors employed by another union, commissioned a study of a prominent psychosocial risk factor: work overload. A case study based on a mixed exploratory participatory design (qual→QUAN; 25 semi-structured interviews, 82 questionnaires) identified individual, interpersonal and organisational determinants, consequences, strategies and possible solutions for the prevention of work overload. The study specifies the workload associated with certain tasks, which are perceived as being more demanding both quantitatively and emotionally. High emotional exhaustion and poor work-life balance underline the urgency of preventing overload. The results point to solutions that mitigate collateral impacts and adopt approaches differentiated by sex/gender, career stage and work-life situation. These reflections on the prevention of a type of psychosocial hazard in trade union action emphasise the importance of understanding the components of workload, and may apply to other professional jobs involving care functions and the management of complex cases.
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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 | 0.001 | 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 | 0.006 | 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".