Climate policymaking in crisis: the impact of declining oil prices, COVID-19, and the Ukraine war in Canada
Bibliographic record
Abstract
Public support for environmental policy historically has declined at times of economic crisis. We consider the impact of three economic shocks – a crash in global oil prices, the COVID-19 pandemic, and the war in Ukraine – on climate policy in a highly carbon-intensive country. One might expect Canada to be especially vulnerable to policy retreat given a history of economic crises weakening electoral support and amplifying carbon-intensive industries’ opposition, yet Canada strengthened its climate policies in the wake of each of the three crises. Policy change was primarily attributable to domestic factors, especially policymakers’ personal commitments. External economic shocks had negligible impacts on regulatory policy, though COVID-19 did amplify green spending. The Canadian experience underscores that retreat is not inevitable: governments maintain considerable domestic independence even amid global crises, though how they respond is contingent on the preferences of the government of the day.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.004 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".