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Record W2110214742 · doi:10.1142/s0219198908001984

A CLASS OF GAMES WITH COUPLED CONSTRAINTS TO MODEL INTERNATIONAL GHG EMISSION AGREEMENTS

2008· article· en· W2110214742 on OpenAlex
Olivier Bahn, Alain Haurie

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Game Theory Review · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsGroup for Research in Decision AnalysisHEC Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGreenhouse gasNegotiationConstraint (computer-aided design)Nash equilibriumYield (engineering)Kyoto ProtocolPareto principleEconomicsClass (philosophy)Mathematical economicsMicroeconomicsMathematicsComputer scienceOperations managementEcologyPhysics

Abstract

fetched live from OpenAlex

This paper deals with the design of equilibrium solutions with coupled constraints in dynamic games of greenhouse gas (GHG) emissions abatement. Self enforcing International Environmental Agreements (IEA) among different groups of countries call for Nash equilibrium solutions when the abatement strategies of the countries are defined. In this paper we study the effect of having another party, like e.g. the United Nations which would impose to all players a coupled constraint on the total emissions allowed over the 21st century, or on the concentration of carbon reached at the end of the century. We show, using different formulations of environmental game, that the normalized equilibria obtained under a coupled constraint on emissions or concentration is close to Pareto optimality. This gives a clue on the way the post Kyoto negotiations could yield an agreement which could be close to efficiency.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0030.000

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 head0.107
GPT teacher head0.294
Teacher spread0.187 · 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