Polyjural and Polycentric Sustainability Assessment: A Once-in-a-Generation Law Reform Opportunity
Bibliographic record
Abstract
The Canadian environmental assessment (EA) regime is broken. At a time when the Canadian economy is both increasingly sluggish and unsustainable, we have an obligation – and perhaps a once-in-a-generation opportunity – to fundamentally reform EA to enable it to finally live up to its promise of promoting sound and sustainability-based decisions. This task is even more pressing in light of the global commitment under the Paris Climate Change Agreement to rapidly transition to greenhouse gas emissions neutrality. Among the many priorities of meaningful EA reform – moving beyond project-level assessments, focusing on net positive contributions to sustainability, avoiding costly trade-offs among interdependent economic, ecological, and social objectives – we focus on the overarching need for polyjural collaboration and polycentric consensus-based decision-making. We argue that any serious effort to move from project-level EAs focused exclusively on adverse biophysical impacts towards a fully integrated, sustainability-based assessment (SA) regime requires a polyjural and polycentric approach capable of facilitating collaborative experimentation among multiple jurisdictional actors, including the federal government, provinces, territories, municipalities, Indigenous peoples, NGOs, academia, project proponents and industry groups, and the Canadian public. After examining the constitutional and political dimensions of the federal and provincial governments’ role in EA, we provide two compelling rationales for transitioning to a SA regime. The paper concludes by setting out a series of possible forms of SA for the purpose of informing the federal government’s review of its EA regime. In particular, we identify and analyze the competing options for jurisdictional cooperation, collaboration, and consensus-based assessment processes along with the constitutional and practical policy implications of each. co-authors: Jason MacLean, Chris Tollefson
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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 | 0.039 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.051 |
| Scholarly communication | 0.020 | 0.011 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".