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Record W7135477843

World Trade Organisation environment related case-law

2012· dissertation· cs· W7135477843 on OpenAlexaboutno aff
Karel Ulík

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2012
Typedissertation
Languagecs
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsnot available
Fundersnot available
KeywordsJurisprudenceComplaintWorld tradeDispute resolutionInternational lawSubject (documents)Settlement (finance)
DOInot available

Abstract

fetched live from OpenAlex

WTO Jurisprudence in Environment-related Disputes Abstract There are a growing number of environment-related disputes before panels and the Appellate Body of the World Trade Organization (WTO). The usual pattern is that one member of the WTO adopts a measure aiming at environment protection, while another WTO member considers the measure to be a restriction on international trade. The following complaint usually alleges violations of most-favoured nation treatment, national treatment, or prohibition of elimination of quantitative restrictions. The defending party then has to prove that its measure falls under one of the exceptions allowing them to restrict trade. These environment-related are a subject of this thesis. In introductory chapters, we explore the evolution of GATT/WTO approach towards the environment, the dispute settlement system, and the substantive law of this international organization. Then we analyze relevant jurisprudence from the very first dispute in 1980, when the US failed to defend their import ban on imports of tuna from Canada, to the recent Brazil ban on import of retreated tyres for their negative impacts on the environment and human as well as animal health. Then we turn to the current, yet undecided dispute on the conformity of a seal products ban with the rules of the WTO. In...

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
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 score0.779
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.004
Open science0.0010.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.235
Teacher spread0.227 · 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.

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
Published2012
Admission routes1
Has abstractyes

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