"À faire un peu de Poussière": Environmental health and the asbestos strike of 1949
Bibliographic record
Abstract
In Mid-February 1949, Workers at the Jeffrey Mine in Asbestos, Québec, voted to strike against the American-owned Johns-Manville Company. This work stoppage precipitated a provincial industry-wide strike that lasted for almost five months. The 1949 Asbestos strike has been incorporated into Québec's broader political historiography, and is generally regarded as a critical turning point in the history of labour and social relations in French- speaking Canada. Yet the environmental health aspects of the conflict in Asbestos remain largely unexamined. Showing how environmental health issues were a trigger for the strike and a sustained goal of the Asbestos workers seeking improvements in their conditions of work, this article demonstrates how central dust and disease were in the negotiations and arbitration hearings involving unionized workers and the company, both in 1949 and in the years that followed. It also accents the extent to which these environmental issues became health concerns that spread throughout the community. In looking at the Asbestos strike of 1949 through the lens of environmental concerns, fresh insight is gained about the nature of one of Canada's major labour conflicts, expanding our understanding of how health issues emerging in the workplace but extending well past it can affect the nature of everyday life and well being in a resource community.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.043 | 0.034 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".