Will We Ever Have Paris? Canada's Climate Change Policy and Federalism 3.0
Bibliographic record
Abstract
Global climate change is at the point where politics as usual is not sufficient to combat it. The author argues that a new conceptualization of constitutionalism and federalism will be required to respond to this change. What the author calls federalism 3.0 will be a bottom-up approach to politics, where individuals are empowered by governments and institutions to shape climate policy. This bottom-up approach is encapsulated in the Paris Climate Change Agreement. Canadian Prime Minister Justin Trudeau has publicly declared Canada’s commitment to climate leadership through mobilizing all elements of Canadian society. However, the author argues Trudeau’s policies to date are merely an example of formalistic, check-the-box constitutionalism, rather than substantive, federalism 3.0.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.012 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 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".