Minimum participation requirements and the role of co-benefits in international climate policy
Bibliographic record
Abstract
Effective combat of international environmental problems regularly necessitates a minimum number of participating countries. Some international environmental treaties like the Paris Agreement combating global warming and the Montreal Protocol protecting the ozone layer required that a minimum participation threshold be met before they entered into force. Albeit the immense challenge to protect the global climate, the Paris Agreement additionally demands to address sustainable development and therefore seeks to take advantage of potential co-benefits of climate protection measures. This article is, to the authors' knowledge, the first to investigate in 3 × 3 normal form games the prospects for effective international cooperation on climate protection if effectiveness requires a minimum number of participating countries. The main findings are, first, that sustainable development co-benefits from mitigation might increase the chance that the minimum participation threshold is met and climate policy will be effective in the end; and second, if domestic ancillary benefits from mitigation are rather small, new organizational designs could create additional sustainability benefits that are limited to mitigating countries. For example, a win-win situation – regarding climate and sustainability – could be achieved by international policy designs that create additional co-benefit spilloversviathe establishment of a club pursuing sustainable innovations (in line with UN Sustainable Development Goal 9).
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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 | 0.015 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 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".