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Record W59896804

The Truth about the Reduction of Greenhouse Gas Emissions Stated in the Kyoto Protocol -Environmental Problems Used as Political and Economic Strategies by European Countries-

2014· article· en· W59896804 on OpenAlexaboutno aff
Yohei Kawabe, Qiyan Wang, Masakazu Yamashita

Bibliographic record

VenueWorld environment · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsKyoto ProtocolGreenhouse gasGovernment (linguistics)Protocol (science)Developing countryPoliticsDignityMontreal ProtocolGlobal warmingConventionPolitical scienceDisadvantagedClimate changeEconomicsEconomic growthGeographyLaw
DOInot available

Abstract

fetched live from OpenAlex

This paper discusses the process of the adoption of the Kyoto Protocol, including the U.N. Framework Convention on Climate Change and government policies of different countries reflected in the process, and examines whether or not the protocol has significance for the prevention of global warming. The results suggest that the process of setting an emission reduction target undergone by the Japanese government did not include thorough discussions and accurate estimates. On the other hand, E.U. member countries and the U.S.A. had discussed various measures with everything taken into account before they attended the Conference of Parties III (COP3). It should have been easy to predict that Japan would be disadvantaged by the enactment of the Kyoto Protocol even before the conference was held. While emission reduction targets for Japan and other developed countries were being set in the Kyoto Conference, all participating countries must have been solely determined to ensure that the protocol would work to their advantage, rather than actively trying to prevent global warming. Furthermore, when the protocol was adopted and emission reduction targets for Britain and Germany were set, these countries had surprisingly already accomplished their goals. This was presumably because industrialized E.U. countries held particularly dominant positions in the conference. On the other hand, Japan was solely determined to build a consensus among the participating countries and maintain its dignity as the host country of the Kyoto Conference. As a result, Japan had to agree to an emission reduction target that could not be easily accomplished.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.533

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)0.0000.000

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 head0.033
GPT teacher head0.240
Teacher spread0.207 · 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.

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

Citations2
Published2014
Admission routes1
Has abstractyes

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