Review of Approaches to and Best Practices in the Regulation of Hydraulic Fracturing in Canada: Appendix M of the Final Report of the Newfoundland & Labrador Hydraulic Fracturing Review Panel
Bibliographic record
Abstract
This report was commissioned by the NLHFRP Water Quality Review Project at Memorial University on behalf of the Western NL Hydraulic Fracturing Panel. The terms of reference called for research on “approaches taken to the regulation of hydraulic fracturing in other jurisdictions, paying particular attention to the identification of regulatory best practices, with a view to coming to conclusions on what changes should be made in the law and regulatory practices of Newfoundland & Labrador as regards the activity of hydraulic fracturing”. The areas of regulatory practice to be considered included regulations on: ... how wells are drilled, completed, stimulated, produced, suspended and abandoned in a manner that assures well bore integrity, considers the risk imposed by the unique reservoir characteristics of the play and the technologies being used (such as inter-wellbore communication) The areas of regulation to be researched included regulation on the approval process, filing requirements and design of hydraulic fracturing, including the chemicals used. The specific research questions to be addressed were as follows: 1. What are the regulatory oversight mechanisms in other Canadian jurisdictions where hydraulic fracturing operations occur? 2. How does the current regulatory framework in Newfoundland & Labrador compare? 3. What are the best practices to ensure appropriate oversight for hydraulic fracturing operations? 4. Should there be ongoing environmental monitoring during and after hydraulic fracturing operations? 5. What actions/regulations/best practices will ensure appropriate regulatory oversight and responsibility? This report provides answers to each of these questions. It uses the answer provided to the first question – on the regulatory oversight mechanisms used in other Canadian jurisdictions – as foundational to the answers given to the other four questions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".