Government Spending on Canada’s Oil and Gas Industry: Undermining Canada’s Kyoto Commitments
Bibliographic record
Abstract
Abstract Governments in Canada subsidize a number of socially beneficial services, including health care, education, and energy services. Subsidies to the energy sector that are for oil and gas production, however, are not all socially benefi cial. In part, they contribute to negative environmental impacts and hinder the development of environmentally friendly alternative energy options. Indeed, Canada’s implementation of the Kyoto Protocol is seriously threatened by continued government support for oil and gas production, a sector with large and rapidly growing greenhouse gas (GHG) emissions. This chapter examines the extent and type of government support provided to the oil and gas sector in Canada between 1996 and 2002 within the context of GHG emission trends and Kyoto commitments. We begin with a discussion of what constitutes a subsidy, at what point subsidies are ‘perverse’, and the need for an evaluation of subsidies in Canada, especially in 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".