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Record W3021212051

Adaptation and the Allocation of Pollution Reduction Costs

2013· article· en· W3021212051 on OpenAlex
Hassan Benchekroun, Farnaz Taherkhani

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCahiers de recherche · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsMcGill University
Fundersnot available
KeywordsIncentivePollutionHarmNatural resource economicsShapley valueEconomicsValue (mathematics)Adaptation (eye)PollutantEnvironmental economicsGame theoryMicroeconomicsComputer science
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.272
GPT teacher head0.307
Teacher spread0.036 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it