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Record W3133052046 · doi:10.1017/s0266267120000449

What do climate change winners owe, and to whom?

2021· article· en· W3133052046 on OpenAlex

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

VenueEconomics and Philosophy · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Geoengineering
Canadian institutionsCenter for Interuniversity Research and Analysis on OrganizationsHEC Montréal
FundersPrinceton University
KeywordsExternalityBeneficiaryEconomicsPolluter pays principleAppealClimate justiceClimate changeEconomic JusticeMicroeconomicsCompensation (psychology)Public economicsLaw and economicsLawPolitical scienceSocial psychologyPsychology

Abstract

fetched live from OpenAlex

Abstract Climate ethics have been concerned with polluter pays, beneficiary pays and ability to pay principles, all of which consider climate change as a single negative externality. This paper considers it as a constellation of externalities, positive and negative, with different associated demands of justice. This is important because explicitly considering positive externalities has not to our knowledge been done in the climate ethics literature. Specifically, it is argued that those who enjoy passive gains from climate change owe gains not to the net losers, but to the emitters, just as the emitters owe compensation to the net losers for the negative externality. This is defended by appeal to theoretical virtues and to the social benefits of generating positive externalities, even when those positive externalities are coupled with far greater negative externalities. We call this the Polluter Pays, Then Receives (‘PPTR', or ‘Peter') Principle.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.027
GPT teacher head0.216
Teacher spread0.189 · 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