Comparative Perspective of the Impact of Canadian and United States Oil Regulation Differences on Approving Use of New Petroleum-Based Energy Sources, A
Bibliographic record
Abstract
The race to find alternative energy to fuel the American economy and save it from reliance on the Middle East oil supply fails to reflect that the United States has a ready source of oil from Canada.In terms of proven petroleum reserves, Canada ranks third after Saudi Arabia and Venezuela.'Canada's oil reserves are eight times larger than the United States. 2 Although the United States and Canada have similar governing structures due to their shared heritage, and both countries are committed to working together, their energy policies are not completely congruent.United States energy policy overemphasizes security and environmental concerns consequently disadvantaging its economy; alternatively, Canada's economy-focused energy policy gives its economy an advantage in energy matters.I. BACKGROUND Security and environmental concerns are the 'rock and hard place' in the American race to find alternative energy sources.The risk to United States energy security mandates that the United States find energy sources outside of the Middle East.Experts have determined that a potential terrorist attack on the Saudi Arabian oil infrastructure can be easily carried out and have devastating effects on the United States economy.4 As the State Department sits poised to approve the Keystone XL Pipeline Project that would allow 1 Notes for a Speech by The Honourable Joe Oliver, P.C., MP.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 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".