Action Research for the Health and Safety of Domestic Workers in Montreal: Using Numbers to Tell Stories and Effect Change
Bibliographic record
Abstract
In 2007, a Filipina organization in Quebec (PINAY) sought the help of university researchers to document the workplace health and safety experiences of domestic workers. Together, they surveyed 150 domestic workers and produced a report that generated interest from community groups, policy-makers, and the media. In this article, we-the university researchers-offer a case study of community-university action research. We share the story of how one project contributed to academic knowledge of domestic workers' health and safety experiences and also to a related policy campaign. We describe how Quebec workers' compensation legislation excludes domestic workers, and we analyze the occupational health literature related to domestic work. Striking data related to workplace accidents and illnesses emerged from the survey, and interesting lessons were learned about how occupational health questions should be posed. We conclude with a description of the successful policy advocacy that was possible as an outcome of this project.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.020 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".