Social norms and international environmental agreements: A natural solution to environmental problems?
Bibliographic record
Abstract
We analyze the role of social norms on the size and effectiveness of international environmental agreements. Social norms lead single agents (the countries’ delegates) to make their individual decisions by accounting for the decisions of others, as they might wish to conform to or to deviate from others’ behavior, introducing an additional welfare-effect for individual emission decisions. We show that social norms promote the formation of large stable coalitions, and if social considerations are sufficiently strong it may even be possible to achieve the grand coalition with full participation. However, whether this effectively benefits the environment is not so obvious, as this ultimately depends on whether social considerations are driven by conformism or anti-conformism motives along with the specific configuration of other key parameters. Indeed, (i) if a coalition forms this could be alternatively characterized by pro-environmental or anti-environmental features, in which members end up emitting less or more than non-members, respectively; and (ii) regardless of the characteristics of the coalition, it could happen that members (non-members) increase their emissions more than non-members (members) reduce their own, resulting in an increase in total emissions with respect to what would have happened in the absence of social considerations. Although social norms are often presented as a natural solution to environmental problems, our results suggest that this may not always be the case; in some instances, social considerations may even lead to detrimental environmental outcomes.
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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 | 0.000 | 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 | 0.000 |
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".