Invisible Workplaces and Forgotten Workers? A Case Study of occupationaL Safety and Health and Workers’ Compensation Coverage in Canadian Non-Profit Organisations
Bibliographic record
Abstract
Non-profit organisations are important mechanisms for the delivery of many social and health services, as well as places where people work. In Canada, 1.3 million people do paid work in non-profit organisations, and many more are involved in a voluntary capacity. However, occupational safety and health systems, originally set up in response to the hazards of factory-based work, may not adequately protect those working in NPOs. In this paper, I argue that workers delivering social and health services in Canadian non-profit organisations can face a number of work-related hazards, including exposure to infectious disease, secondhand smoke, violence and stress. My examination of provincial legislation that was designed to protect the health of workers and provide compensation when workers have been injured at work found that, at times, it is not well-suited to workers in non-profit organisations or to the organisational configurations (eg mixing paid and voluntary labour) found in this sector. I examine these legislative gaps and discuss the implications they can have for workers’ health in this growing sector.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.068 | 0.016 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.006 | 0.006 |
| 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".