A Comparison of Different Regulatory Appraoches, Analysis of the Relative Benefits of Command and Control, Reflexive Law and Social Licencing in Ensuring Oil Industry Compliance with Environmentally Sustainable Practices and Obligations
Bibliographic record
Abstract
This paper explores the relative benefits of command and control, reflexive law and social licensing in ensuring oil industry compliance with environmentally sustainable practices and obligations. Recognizing why oil sands and their development are significant, the background and development are reviewed first, and then the focus is shifted to look at its economics including the benefits, uncertainties and environmental costs of development. \n \nThis paper examines how lawmakers in Canada have failed to meet their respective obligation. Drawing on environmental provisions, case law and legal scholars’ articles, books and reports, this paper examines the very problematic issue of oil sands regulation. It proposes to provide an in depth analysis of each regulatory forms and their application to the oil sands. It concludes that in order to solve the oil sands regulation challenges, a collaborative stringent enforcement of regulation from both federal and provincial governments, oil industry and public Pressure is required.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".