Review of "Smelter Smoke in North America: The Politics of Transborder Pollution"
Bibliographic record
Abstract
If you live in the West Kootenay valley, then you've seen the Trail Metallurgical Operations Plant owned by Cominco.Cominco is a huge integrated smelter and refinery producing zinc, lead, silver, several other metals, and incongruously, fertilizer.You've heard the stories of a subterranean gold-filled vault, heavy water for the Manhattan Project and a dispute between Canada and the USA over air pollution.All of these are facts not fiction."Smelter Smoke in North America: The Politics of Transborder Pollution" by John D. Wirth, published in 2000, examines the story of Cominco's atmospheric emissions.Wirth is a history professor at Stanford and a White House appointee serving on the NAFTA Commission for Environmental Cooperation.His scholarly, thorough book leads through a maze where grassroots public action, corporate interests, government involvement, and science intertwine.These strands strain the balance between economic needs, protecting citizens' health and the cross-border issues between Canada and the USA.Wirth describes the evolution of accepting environmental protection as a legitimate, necessary cost of business.He provides examples of resistance to this perspective and some erratic progress towards sustainable development.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".