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Record W66496003 · doi:10.1017/s0069005800011097

Renewable Energy and Trade: Interpreting against Fragmentation

2014· article· en· W66496003 on OpenAlexaffvenueabout
Maureen Irish

Bibliographic record

VenueCanadian Yearbook of international Law/Annuaire canadien de droit international · 2014
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRenewable energyFragmentation (computing)Natural resource economicsEconomicsBusinessComputer scienceEngineering

Abstract

fetched live from OpenAlex

Summary Several disputes relating to renewable energy are underway at the World Trade Organization (WTO). The Appellate Body has released its first decision on this subject on the feed-in tariff for electricity in the province of Ontario. The disputes raise once again the issue of the relationship between international trade law and environmental protection. Evolving WTO jurisprudence should be able to resolve many of the difficulties, although the crucial problem of the treatment of production and processing methods remains obscure after the Canada – Renewable Energy decision. Questions of fundamental theory lie close to the surface of these debates. The recent expansion in the number of international regimes and tribunals highlights the importance of approaches to interpretation in public international law. As countries negotiate new treaties to address the needs of global society, potential conflicts and overlapping provisions are likely to appear. Differences of opinion about reliance on non-WTO treaties in the WTO dispute settlement system illustrate problems that can be anticipated in several fora. To achieve workable solutions for renewable energy disputes and many others, interpretation should promote the harmonious integration of obligations, in accordance with the intent of the negotiators.

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)0.009
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: Other · Consensus signal: Other
Teacher disagreement score0.598
Threshold uncertainty score0.809

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.008
Science and technology studies0.0070.015
Scholarly communication0.0150.006
Open science0.0020.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0100.001

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 head0.004
GPT teacher head0.203
Teacher spread0.199 · 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
GenreOther

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
Published2014
Admission routes3
Has abstractyes

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