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Record W2169036131

Russia and the Kyoto Protocol: Ratification and Post-Ratification Politics

2015· article· en· W2169036131 on OpenAlexaff
Lisa McIntosh Sundstrom, Laura A. Henry

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRatificationKyoto ProtocolTreatyNegotiationInternational tradePoliticsPolitical scienceGovernment (linguistics)Political economyLawEconomicsPublic administrationGreenhouse gas
DOInot available

Abstract

fetched live from OpenAlex

following the United States ’ decision not to ratify it. Why did the Russian government – with little popular pressure and little enthusiasm for environmental protection – decide to ratify Kyoto, and what measures will it take to implement the treaty? Proponents of ratification were numerous, consisting mainly of scientists, environmentalists, and business interests, but they were countered by a small number of powerful anti-Kyoto voices in the scientific and political communities who appeared to dominate the debate. In the end these battling interests had little influence on the decision due to the centralized institutional environment in Russia which allows the President to make foreign policy decisions largely single-handedly. President Putin ratified the treaty because Russia would likely experience economic gains rather than losses from Kyoto provisions, gain leverage in other international negotiations, and contribute to an image of itself as a good member of the club of advanced industrialized states. The president delayed ratification in order to clarify evidence about gains versus losses and secure concessions from other Kyoto ratifiers in other international negotiations. Implementation of the treaty is proceeding slowly, in part due to uncertainty during the ratification process, and existing efforts indicate that Russia's implementation strategy will likely be directed more at maximizing profits through treaty mechanisms to modernize industrial sectors than at maximizing emissions reductions. This paper is part of a multi-country comparative project aimed at explaining different governments ’ decisions to ratify or not ratify the Kyoto Protocol on Climate Change and

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0050.011
Scholarly communication0.0120.006
Open science0.0010.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.275
Teacher spread0.223 · 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 designTheoretical or conceptual
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

Citations0
Published2015
Admission routes1
Has abstractyes

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