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Record W2063265388 · doi:10.1177/0305829810372480

A Tale of Two Copenhagens: Carbon Markets and Climate Governance

2010· article· en· W2063265388 on OpenAlexaff
Steven Bernstein, Michele M. Betsill, Matthew J. Hoffmann, Matthew Paterson

Bibliographic record

VenueMillennium Journal of International Studies · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsUniversity of OttawaUniversity of Toronto
Fundersnot available
KeywordsNegotiationCorporate governanceNormativeClimate governanceClimate changePolitical scienceGlobal governanceEconomicsPolitical economyBusinessLawFinance

Abstract

fetched live from OpenAlex

Assessments of the UN Climate Change Conference in Copenhagen in December 2009 have tended to see it as a ‘return to realism’ — as the triumph of hard interstate bargaining over institutional or normative development about climate change. This article contests that interpretation by showing how it focuses too closely on the interstate negotiations and neglects the ongoing development of carbon markets as governance practices and systems to deal with climate change. It shows that there remains a strong normative consensus about such markets, and a deepening set of transnational governance practices. These governance practices only partly depend on the interstate negotiations. Thinking about the future of global climate governance needs to start with the complexity of interactions between these transnational governance systems and the interstate negotiations.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.022
Scholarly communication0.0120.022
Open science0.0010.006
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0110.001

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 head0.051
GPT teacher head0.289
Teacher spread0.238 · 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 designQualitative
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

Citations164
Published2010
Admission routes1
Has abstractyes

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