Adaptation and the Allocation of Pollution Reduction Costs
Why this work is in the frame
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Bibliographic record
Abstract
We consider a game of abatement of a transboundary pollutant. We use a time-consistent Shapley value allocation of the cost of pollution reduction, and study the sensitivity of such an allocation to countries' adaptation to pollution. A country's adaptation to pollution is captured by a change in its damage function. We show that if there is a reduction in the damage cost of one country only, this can harm the other countries. Some countries may end up worse o¤ even in the case where all countries experience a uniform decrease in their damage from pollution. An important policy implication of our analysis is that the Shapley value approach to the allocation of abatement costs doesn't necessarily provide the right incentives for all players to act on reducing pollution damage. We determine conditions under which a uniform fall in all countries'pollution damage benefits all countries.
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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 | 0.002 | 0.001 |
| 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 it