Climate and Energy Politics in Canada and Germany: Dealing with Fossil Fuel Legacies
Bibliographic record
Abstract
Canada and Germany are both pursuing major energy transitions and far-reaching climate programs but differ in terms of policies towards some energy sources and their preferred policy instruments. Both countries have committed to large scale emission reductions despite the challenge of regional divestment from fossil fuels: hard coal in North Rhine Westphalia and the Saarland; lignite in the Rhineland, on the German-Polish border in the Lusatsia (Lausitz) region, and in central Germany; coal in Alberta, Saskatchewan and Nova Scotia; and oil in Western Canada. We contrast the current Pan Canadian framework (PCF) on Clean Growth and Climate Change to the German Climate Law and the European Green Deal setting targets to become climate neutral by 2050. Germany has plans for a dual phase out of nuclear energy by 2022 and coal by 2038. In contrast, Canada differs by province in terms of policies on fossil fuels and nuclear energy. Both are leaders in renewable energies, but differ in the type of renewable energy which dominates. We further examine the international action components of the PCF and its implications for collaboration with Germany and the EU. We discuss potential partnerships and strategic alliances between Canada and Germany in the context of their mutual interest to enable an energy transition and to lead to the implementation of the Paris agreement for climate change action. We identify political challenges within each federation, and especially the approach to impacted coal regions in Germany and Poland as well as the Canadian oil sands. Barriers to progress for meeting identified targets and timelines are considered. We conclude with insights on the possibility and likelihood of linking policies and regulatory measures across the Atlantic, and the political threats of advancing towards decarbonization and an energy transition away from fossil fuels in each jurisdiction.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.026 | 0.009 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| 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".