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Record W3121871993 · doi:10.1093/cesifo/ifp008

Bringing the Copenhagen Global Climate Change Negotiations to Conclusion

2009· article· en· W3121871993 on OpenAlexaff
John Whalley, Sean Walsh

Bibliographic record

VenueCESifo Economic Studies · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsCentre for International Governance Innovation
Fundersnot available
KeywordsNegotiationMandateEnforcementKyoto ProtocolInternational tradeClimate changePolitical scienceBusinessEconomicsDevelopment economicsLaw

Abstract

fetched live from OpenAlex

In this article we discuss the global negotiations now underway and aimed at achieving new climate change mitigation and other arrangements after 2012 (the end of the Kyoto commitment period). These were initiated in Bali in December 2007 and are scheduled to conclude by the end of 2009 in Copenhagen. As such, this negotiation is effectively the second round in ongoing global negotiations on climate change and further rounds will almost certainly follow. We highlight both the vast scope and vagueness of the negotiating mandate, the many outstanding major issues to be accommodated between negotiating parties, the lack of a mechanism to force collective decision making in the negotiation, and their short time frame. The likely lack of compliance with prior Kyoto commitments by several OECD countries (some to a major degree), the effective absence in Kyoto of compliance/enforcement mechanisms, and growing linkage to non-climate change areas (principally trade) all further complicate the task of bringing the negotiation to conclusion. The major clearage we see that needs to be bridged in the negotiations is between OECD countries on the one hand, and lower wage, large population, rapidly growing countries (China, India, Russia, Brazil) on the other. (JEL codes: F33, F51, F53, Q54, Q56, P28)

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)0.011
metaresearch head score (Gemma)0.024
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 score0.028
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.006
Scholarly communication0.0150.011
Open science0.0020.006
Research integrity0.0070.010
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 head0.206
GPT teacher head0.341
Teacher spread0.135 · 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

Citations23
Published2009
Admission routes1
Has abstractyes

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Same venueCESifo Economic StudiesSame topicClimate Change Policy and EconomicsFrench-language works237,207