Compliance Committees and Recent Multilateral Environmental Agreements: The Canadian Experience with Their Negotiation and Operation
Bibliographic record
Abstract
Summary In order to enhance and encourage compliance with obligations in multilateral environmental agreements (MEAs), states have agreed to the creation of compliance committees for all of the recent MEAs. Canada has been a strong supporter of the compliance committee experiment and an active participant in the negotiation and operation of numerous MEA compliance committees. This article does three things. First, it examines the international legal nature of the MEA compliance committees. Second, the key issues of the structure of the committees are explored. Finally, the article look at the development and operation of compliance committees pursuant to: the Montreal Protocol; the LRTAP Convention; the Espoo Convention; the Basel Convention; the Cartagena Protocol; the Rotterdam Convention; the Stockholm Convention; and the Protocol to the London Dumping Convention.
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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 | 0.024 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.041 | 0.020 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 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".