Climate Change Politics in Canada and the EU—from Carbon Democracy to a Green Deal?
Bibliographic record
Abstract
The idea of a green deal transforming industrialized societies’ climate policies in a sustainable manner has become highly popular in various countries. The study takes up this notion focusing on climate policy initiatives in Canada and the EU, raising three interrelated issues: (i) on a descriptive level, the study asks where we stand and what has so far been achieved regarding climate policy; (ii) analytically, the study provides a theoretical explanation of why progress has been slow in the EU and hardly visible in Canada, making use of the concept of carbon democracy; (iii) on a prescriptive level, the study explores what will be needed to make a green deal successful, arguing that one has to accept that a green deal is a deeply political project that will create winners and losers and that not all losers can be compensated under the label of a “just transition”. The argument advanced is that the EU and Canada represent a form of carbon democracy in which the extensive use of carbon laid the foundation for establishing democratic institutions and strongly shaped them. The paper shows that the extensive influence of carbon-related activities not only empowers specific non-state agents but is rather deeply enmeshed in the societal and political genome of both regions’ polities. The claim that follows is that climate politics in Canada and the EU will have to be deeply transformative and therefore disruptive in order to be successful.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".