Game theory: building up cooperation
Bibliographic record
Abstract
Can we achieve the ambitious mitigation targets needed to avert dangerous global warming? Research now shows that local sanctioning institutions may succeed where global agreements fall short. In spite of some 18 Conferences of the Parties, global efforts to curb emissions have failed to achieve tangible results (Fig. 1). Although participation is broad — there are 192 parties to the Kyoto Protocol under the United Nations Framework Convention on Climate Change (UNFCCC) — only a handful of nations are actually bound to reduce emissions. Furthermore, the lack of a supranational sanctioning institution means that countries are effectively free to disregard their commitments or to withdraw from the agreement (as Canada did). Due to the inherent trade-off between the breadth of the treaty, in terms of number of acceding countries, and the depth of the emission-reduction commitments, game theorists have come up with the dismal prediction that little will be achieved by a self-enforcing agreement. Either the number of signatories will be small, or many countries will partake in a shallow agreement and achieve only modest reductions. In Nature Climate Change, Vasconcelos and colleagues provide reasons for optimism: local climate governance may be less riddled with barriers to cooperation than international agreements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".