How Canada Changed from Exporting Asbestos to Banning Asbestos: The Challenges That Had to Be Overcome
Bibliographic record
Abstract
Less than ten years ago, the asbestos industry enjoyed the support of every Quebec and Canadian political party. The Chrysotile Institute and the International Chrysotile Association, both located in Quebec, aggressively marketed asbestos around the world, claiming scientific evidence showed that chrysotile asbestos could be safely used. The industry created a climate of intimidation. Consequently, no groups advocating for victims of asbestos or campaigning for its outright ban existed in Quebec to challenge the industry. A campaign was launched to mobilize the scientific community to speak out. Working with scientists, activists, and asbestos victims around the world, a small group of Quebec scientists exposed the false arguments of the asbestos industry. They publicly and repeatedly challenged the unscientific and unethical asbestos policy of the government. By appealing to Quebec values and holding those in power accountable, the campaign won public support and succeeded against all odds in defeating the asbestos industry.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.027 | 0.012 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".