MétaCan
Menu
Back to cohort
Record W2003032478 · doi:10.1163/187601005x00147

It Takes Two to Tango - Climate Policy at COP 10 in Buenos Aires and Beyond

2005· article· en· W2003032478 on OpenAlexaboutno aff
Wolfgang Sterk, Hermann E. Ott, Bettina Wittneben, Bernd Brouns

Bibliographic record

VenueJournal for European Environmental & Planning Law · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsInternational lawPolitical scienceClimate policyClimate changeLawGeologyOceanography

Abstract

fetched live from OpenAlex

The first Meeting of the Parties to the Kyoto Protocol (MOP 1) took place from 28 November to 10 December 2005 in Montreal, in conjunction with the eleventh meeting of the Conference of the Parties to the Framework Convention on Climate Change (COP 11). This meeting signifies a successful start into a new era of international climate policy: The Kyoto Protocol, which in the past had been sometimes declared as being dead, has become operational. The challenges of the meeting were framed along the "Three Is", Implementation, Improvement and Innovation. The first challenge (Implementation) entailed in particular the adoption of the Marrakesh Accords, the agreements reached at COP 7 in Marrakesh that set out the detailed rules for making the Kyoto Protocol operational. The second challenge (Improvement) referred to improving the work of the Framework Convention and the Kyoto Protocol in the near future. The third and most important challenge (Innovation) referred to the further evolution of the regime. This article by Bettina Wittneben, Wolfgang Sterk, Hermann E. Ott und Bernd Brouns provides an account of the main developments in Montreal along the lines of the "Three Is". The paper concludes with an assessment and outlook on international climate policy.

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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score1.000

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)0.0000.001

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 head0.052
GPT teacher head0.281
Teacher spread0.229 · 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 teacher head, not a consensus.

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

Citations21
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueJournal for European Environmental & Planning LawSame topicClimate Change Policy and EconomicsFrench-language works237,207