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Record W2405655945 · doi:10.2495/eq-v1-n2-192-205

A new paradigm of governance for a carbon-pricing system

2016· article· en· W2405655945 on OpenAlexaff
S. Quéré, G. Delmas-patterson, Andrey Berezin

Bibliographic record

VenueInternational Journal of Energy Production and Management · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsMcMaster UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsCorporate governanceBusinessCarbon fibersComputer scienceFinance

Abstract

fetched live from OpenAlex

Throughout its life, the United Nations has played a pioneering role in the world of ideas.COP21 -also known as Paris 2015 -shows the path for the United Nations to establish a new governance that will enforce the compliance of a new planetary carbon-pricing system.Maintaining global warming below 2 °C means implementing an efficient carbon-pricing system, supported by effective measures promoting a green energy transition.A planetary carbon governance yields a number of new insights that include the following: (1) a bonus-malus system with a fixed signal price for carbon, (2) a planetary carbon market that will gather existing regional carbon markets, (3) a hybrid carbon-pricing system linking a carbon tax and a carbon market for advanced countries and (4) a support mechanism for emerging and developing countries to assist them with a carbon-pricing system.This new governance will promote an energy transition plan.In the COP21 context, responsible policymaking requires key characteristics for the enforcement of a successful planetary carbon-pricing system.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.013
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.019
Scholarly communication0.0130.015
Open science0.0020.005
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0080.001

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 head0.040
GPT teacher head0.238
Teacher spread0.198 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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