Mining Ontario: Corporate Power, the Mining Industry, and Public Policy in Ontario
Bibliographic record
Abstract
This dissertation critically examines the history of the government of Ontarios policies towards the mining industry to analyze the impact of concentrated economic power on political processes in liberal democracies. It is the first comprehensive study of the political power of one of the provinces largest and most influential industries. Drawing on critical theories of business power, this dissertation examines policy developments across four contentious issue areas, namely fiscal policy, air pollution control, occupational health and safety, and access to mineral lands. Employing a qualitative historical narrative, the study draws on data collected from the Public Archives of Ontario, newspapers, published reports and secondary academic literature. Challenging those theoretical perspectives that downplay the direct influence of large business enterprises over public policy, this dissertation argues that the mining industry has exercised a predominant influence over the government of Ontarios public policies. While the industry disposes of several political resources that privilege it in relation to its opponents, two in particular deserve special attention: First, minings commanding economic presence in the provincial North where alternative investment opportunities are generally absent, and second, the industrys deep-seated linkages with the provincial mining ministry in terms of personnel and ideology. In sum, the mining industrys structural power over the Northern economy together with its close working relations with the provincial ministry of mines have rendered provincial policymakers particularly vulnerable to the industrys lobbying, allowing the industry to play a predominant, though not monolithic, role in shaping provincial public policy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".