Exposing the “Myth” of ABC, “Anything But Chrysotile”: A critique of the Canadian asbestos mining industry and McGill University chrysotile studies
Bibliographic record
Abstract
BACKGROUND: Beginning in the 1930s, the Canadian asbestos industry created and advanced the idea that chrysotile asbestos is safer than asbestos of other fiber types. METHODS: We critically evaluate published and unpublished studies funded by the Quebec Asbestos Mining Association (QAMA) and performed by researchers at McGill University. RESULTS: QAMA-funded researchers put forth several myths purporting that Quebec-mined chrysotile was harmless, and contended that the contamination of chrysotile with oils, tremolite, or crocidolite was the source of occupational health risk. In addition, QAMA-funded researchers manipulated data and used unsound sampling and analysis techniques to back up their contention that chrysotile was "essentially innocuous." CONCLUSIONS: These studies were used to promote the marketing and sales of asbestos, and have had a substantial effect on policy and occupational health litigation. Asbestos manufacturing companies and the Canadian government continue to use them to promote the use of asbestos in Europe and in developing countries. Am. J. Ind. Med. 44:540-557, 2003.
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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 | 0.044 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.028 | 0.096 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.009 | 0.005 |
| Research integrity | 0.015 | 0.019 |
| 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".