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Record W1698156898

Feed-In Tariffs for Renewable Energy and WTO Subsidy Rules: An Initial Legal Review

2011· article· en· W1698156898 on OpenAlexaboutno aff
Marie Wilke

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsnot available
Fundersnot available
KeywordsSubsidyTariffContext (archaeology)Feed-in tariffRenewable energyInternational tradeRules of originBusinessInternational trade lawInternational economicsEconomicsPublic economicsPolitical scienceEnergy policyLawEngineeringGeography
DOInot available

Abstract

fetched live from OpenAlex

This paper analyzes renewable energy feed-in tariff (FIT) programmes in the context of World Trade Organization (WTO) subsidy rules. By examining the functioning of the FIT programmes implemented by the Canadian province of Ontario, Germany and the United Kingdom (UK) the paper explores how current subsidy rules may treat FIT programmes. The issue formally entered the halls of the WTO when a dispute was lodged with the WTO’s Dispute Settlement Body (DSB) in September 2010 over Ontario’s feed-in tariff scheme (Canada-Renewable Energy (Japan)). A second case on the same measure followed in August 2011 (Canada-Feed-in Tariff (EU)). The FIT programme in question contains a controversial local-content provision which requires up to 60% of input of the project to be resourced in Ontario. Japan and the EU argue that this disadvantages producers outside Ontario and amounts to an illegal subsidy. In particular this decision to file the dispute under the WTO’s subsidy accord has attracted great attention. In an effort to inform the debate on the matter, the main question that this paper addresses is whether WTO rules, specifically the WTO Agreement on Subsidies and Countervailing Measures (SCM Agreement), prohibit FIT programmes as illegal subsidies and if so, on which grounds. The paper also assesses whether there are any exceptions available, in particular whether Article XX of the General Agreement on Tariffs and Trade (GATT) could apply.

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)0.002
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: none
Teacher disagreement score0.790
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.022
GPT teacher head0.285
Teacher spread0.263 · 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

Citations12
Published2011
Admission routes1
Has abstractyes

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