Overlapping Climate Clubs: Self-Enforcing R&D Networks to Mitigate Global Warming
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Free riding incentives make it difficult to control climate change. To improve the chances of the Paris Agreement’s ambitious goal, many nations are forming scientific networks in carbon capture and storage (CCS). These networks take many forms (bilateral, hub-and-spoke, and multilateral). Studies of social interactions among scientists demonstrate that research networks are limited because of relational issues, such as lack of trust. This paper provides a rationale for the formation of various types of international CCS networks and examines their impacts on climate change. Our concept of stability focuses on Nash equilibria that are immune to coalitional deviations in overlapping networks. Players may belong to various research networks. A particular research network is a climate club. We show that in the absence of top-down coordination in clubs, the type of global network that forms depends on relational attrition. The complex task is to mitigate free riding while enhancing trust.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it