Bibliographic record
Abstract
Introduction Much theoretical debate and effort in practice has been devoted to the question how best to promote compliance with multilateral environmental agreements (MEAs). At the theoretical level, it seems fair to say that no compliance theory can claim universal validity. Indeed, the experience gained with MEA compliance systems over the last fifteen years or so makes clear that a range of approaches, both facilitative and enforcement-oriented, must be harnessed. Perhaps most importantly, for a compliance system to be effective, it has to be designed with the context and particular characteristics of a specific MEA in mind. The design parameters include the substance of the MEA, the parties involved, the past experience, and the political context within which the compliance system is negotiated. The climate change regime is no exception. As it stands at the moment, the regime boasts one of the most elaborate and multifaceted compliance systems in any MEA. Under the convention, parties have extensive monitoring and reporting obligations. The United Nations Framework Convention on Climate Change (FCCC) also provides for a facilitative compliance assessment process, the multilateral consultative process. However, due to the negotiation of the Kyoto Protocol, this process was never activated. The Kyoto parties negotiated additional inventory and reporting commitments, along with an expert review process and procedures and mechanisms relating to compliance. The procedures and mechanisms, which have been in operation since 2006, feature a facilitative stream and an enforcement stream. This compliance system was developed with the particular features of the climate regime, as well as the context in which it operates, very much in mind. For example, the compliance system distinguishes between legally soft, procedural, and policy-oriented commitments and hard, target-related commitments. For the latter, the Kyoto Protocol’s compliance procedures and mechanisms provide an enforcement-oriented approach, intended to help level the competitive playing field among parties with onerous emission reduction commitments. The enforcement branch (EB) of the compliance procedure is also designed to help ensure the functioning of the Kyoto Protocol’s emissions trading mechanisms, a unique feature of the regime,
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.163 | 0.051 |
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".