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Record W3004598523 · doi:10.1017/ajil.2019.82

United States Gives Notice of Withdrawal from Paris Agreement on Climate Change

2020· article· en· W3004598523 on OpenAlexaboutno aff

Bibliographic record

VenueAmerican Journal of International Law · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNoticeAdministration (probate law)RegretAgreementPolitical scienceState (computer science)LawMember statesEuropean unionEconomicsInternational trade

Abstract

fetched live from OpenAlex

On November 4, 2019, the Trump administration notified the United Nations that the United States was withdrawing from the Paris Agreement, prompting expressions of regret from a number of countries. Although President Trump had announced in June 2017 that the United States intended to withdraw from the Paris Agreement, its terms had prevented the United States from giving formal notice of withdrawal until November 4, 2019. The withdrawal will take effect on November 4, 2020. Domestically, the governors of many U.S. states responded to the withdrawal by reaffirming their commitment to the goals of the Paris Agreement, consistent with recurring tensions between the Trump administration and progressive states with respect to climate. In another major manifestation of these tensions, on October 23, 2019, the United States sued California over the state's cap-and-trade agreement with Quebec, Canada, alleging that this agreement is an unconstitutional exercise of foreign affairs powers.

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)0.005
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.081
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0140.009
Insufficient payload (model declined to judge)0.0550.022

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 head0.029
GPT teacher head0.317
Teacher spread0.288 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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