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Elements for a Robust Climate Regime Post‐2012: Options for Mitigation

2007· article· en· W1531975767 on OpenAlexaff
Soledad Aguilar

Bibliographic record

VenueReview of European Community & International Environmental Law · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsInternational Institute for Sustainable Development
Fundersnot available
KeywordsGreenhouse gasCarbon marketNegotiationUnited Nations Framework Convention on Climate ChangeKyoto ProtocolClimate changeClimate change mitigationCarbon sinkConference of the partiesConventionBusinessNatural resource economicsEnvironmental resource managementEnvironmental scienceEconomicsPolitical scienceEcology

Abstract

fetched live from OpenAlex

This article addresses the current state of negotiations within the international climate change regime (including the United Nations Framework Convention on Climate Change and its Kyoto Protocol) and options to be included in a post‐2012 carbon market framework, such as sectoral agreements, soft targets for developing countries and a larger consideration of sinks. The article reviews the different options focusing on their potential to spur mitigation of greenhouse gases in key areas such as energy production. The size and depth of the carbon market, as well as the stringency of the cap and the stabilization path chosen, are variables affecting the effectiveness of different options. The article thus makes a clear case for all large emitters to agree on a long‐term stabilization goal to guide further negotiations on medium‐term carbon market frameworks, and notes that options related to the consideration of sinks, for example, should maintain proportionality with the size of the carbon market to ensure that a sufficient ‘pull’ for technological developments in energy‐related activities is maintained.

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)0.012
metaresearch head score (Gemma)0.017
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 score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0080.015
Open science0.0020.006
Research integrity0.0130.010
Insufficient payload (model declined to judge)0.0090.002

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 head0.089
GPT teacher head0.287
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

Citations4
Published2007
Admission routes1
Has abstractyes

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