High prices may soften Ottawa's approach to oil sector
Bibliographic record
Abstract
Significance Following its re-election last year, the Liberal government appeared set to take a stronger line on reducing fossil fuel use as part of efforts to mitigate climate change. However, the hydrocarbons sector may now get more support amid the shifting dynamics of the global market. Impacts The federal government will see a windfall in revenues from oil and gas prosperity in Alberta, using the money for new spending. Alberta’s conservative government should now head into provincial elections, due in April or May 2023, in a stronger position. First Nations will continue to oppose new pipelines, and the legal and regulatory landscape will continue to favour this position. A Conservative victory at the next general election, not expected before 2025, would change the outlook for the energy sector.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.127 | 0.016 |
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".