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Record W2080874090 · doi:10.1108/14770020910981489

Building on the Canadian approach to resolve the stalemate on the trade and environment agenda in the World Trade Organization

2009· article· en· W2080874090 on OpenAlexaffabout
Tesh W. Dagne

Bibliographic record

VenueJournal of International Trade Law and Policy · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsThompson Rivers UniversityDalhousie University
Fundersnot available
KeywordsStalematePrinciple of legalityScope (computer science)International tradeTrade barrierWorld tradeEconomic integrationState (computer science)Free tradePolitical scienceLaw and economicsEconomicsBusinessInternational economicsLawComputer science

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to analyze the competing views on the link between trade and environment in the World Trade Organization (WTO), and come up with a proposal that better clarifies the scope of legality of environmentally motivated unilateral trade measures in the multilateral trading system. Design/methodology/approach The paper adopts a doctrinal approach to legal research in providing an exegesis on the various efforts towards the integration of trade and environment in the WTO framework. Findings Employing the theory of transnational social justice as its analytical tool, the paper suggests that a state contemplating the use of environmentally motivated unilateral trade measures first extend positive measures to the communities in other states that are affected by the purported measure. Accordingly, it argues that unilateral trade measures are allowed in the system only as a last resort and only if their application runs congruent to the values and objectives recognized by the system. Originality/value It is hoped that the discussion and proposition in this paper will contribute to the discourse on the clarification of the status of environmentally motivated unilateral trade measures in the WTO.

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: Commentary · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.288
Teacher spread0.262 · 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
GenreCommentary

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
Published2009
Admission routes2
Has abstractyes

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