Smelter Fumes, Local Interests, and Political Contestation in Sudbury, Ontario, during the 1910s
Bibliographic record
Abstract
During the second half of the 1910s the problem of sulphur smoke in Sudbury, Ontario, pitted farmers against the mining-smelting industry that comprised the dominant sector of the local economy. Increased demand for nickel from World War I had resulted in expanded activities in the nearby Copper Cliff and O’Donnell roast yards, which in turn produced more smoke and destroyed crops. Local business leaders, represented by the Sudbury Board of Trade, sought to balance the needs of the agriculture and mining-smelting sectors and facilitate their coexistence in the region. Among the measures pursued, farmers and some Board of Trade members turned to nuisance litigation, with the objective of obtaining monetary awards and injunctions affecting the operation of the roast yards. While the amounts of the awards were disappointing for the farmers, the spectre of an injunction was sufficient to convince the provincial government to ban civil litigation in favour of an arbitration process accommodating industry. This article provides an account of the political activism over Sudbury’s smoke nuisance that failed to bring about emission controls, highlighting the contextual factors contributing to this failure.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.017 | 0.017 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".