Examining the Effects of Environmental Policy on Shale Gas Production: The Case of Alberta, Canada
Bibliographic record
Abstract
The increase in natural gas production in North America resulting from the implementation of new technologies related to the fracturing (fracking) of natural gas-bearing shale reservoirs has enhanced the security of supply and lowered energy costs in the continent. Yet the environmental impact associated with shale gas development has raised concerns and debate among energy and environmental policy makers as to how best to address these concerns. As Canada’s largest producer of natural gas, the Province of Alberta is an example of a jurisdiction with numerous regulations for dealing with such environmental risks. This paper applies the CO/RE model of Konschnik and Bolingin examining Alberta’s environmental regulatory framework and the impact; it will have on further shale gas production in the province. Aside from the identification of risks associated with increased seismicity, the results of this examination suggest that the current regulatory environment does not appear to have any adverse effect on current and future shale gas production within the province. Furthermore, Alberta’s environmental regulation has influenced shale gas producers to pursue innovation in technology and engineering practice and has helped establish a collaborative approach to mitigating environmental risk.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".