Asbestos, Quebec: The Town, the Mineral, and the Local-Global Balance Between the Two
Bibliographic record
Abstract
From the late 19th to the late 20th century, the cities and industries of the world became increasingly reliant on fireproof materials made from asbestos. As asbestos was used more and more in building materials and household appliances, its harmful effect on human health, such as asbestosis, lung cancer and mesothelioma, became apparent. The dangers surrounding the mineral led to the collapse of the industry in the 1980s. While the market demand and medical rejection of asbestos were international, they were also experienced in the mining and processing communities at the core of the global industry. In the town of Asbestos, Quebec, home of the largest chrysotile asbestos mine in the world, we can see how this process of market boom and bust shaped a fierce local cultural identity. This dissertation examines the global asbestos industry from a local perspective, showing how the people of Asbestos, Quebec had international reach through the work they did and the industry they continue to support today. This thesis explores how the boundaries between humans and the environment were blurred in Asbestos as a strong cultural identity was created through the interaction between people and the natural world. This work advances our understanding of the interdependence of the local-global relationship between resource industries and international trade networks, illustrating the ways it shapes communities and how communities shape it. Bringing bodies of land, human bodies, and the body politic of Asbestos, Quebec into the history of the global asbestos trade helps demonstrate how this local cultural identity grew to influence national policy and global debates on commodity flows, occupational health, and environmental justice.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".