Early Experience with the Kyoto Compliance System: Possible Lessons for MEA Compliance System Design
Bibliographic record
Abstract
Regardless of the future of the Kyoto compliance system, much of its work will continue to be important both for the climate change regime and for other MEAs. While it is impossible to make accurate predictions about the substance of the climate change regime after 2012, it is nevertheless important to reflect on the experience with the Kyoto compliance system to date for MEA compliance generally. Adjustments to the Kyoto compliance system necessitated by post 2012 changes to the substantive obligations can, of course, only be considered once those changes are known. The central question posed in this article is therefore the following: Assuming the obligations under the climate change regime were to remain unchanged, what adjustments to the Kyoto compliance system would be warranted in light of the experience to date? In addressing this central question, the aim of this article is to help inform the design of future compliance systems under any MEAs that recognize the value of seeking to combine facilitative compliance strategies with enforcement.
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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 | 0.041 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".