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Record W2594795538 · doi:10.1515/bjals-2016-0019

The Two Noble Kinsmen: Internal and Legal Transparency in the WTO and Their Connection to Preferential and Regional Trade Agreements

2016· article· en· W2594795538 on OpenAlexaff
Maria Panezi

Bibliographic record

VenueBritish Journal of American Legal Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsCentre for International Governance Innovation
Fundersnot available
KeywordsTransparency (behavior)International tradeNegotiationInternational trade lawInternational economicsDeclarationBusinessPolitical scienceLaw and economicsEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract The proliferation of Preferential Trade Agreements (PTAs) and Regional Trade Agreements (RTAs) has given rise to significant debate on the need to measure, understand and possibly regulate the impact these agreements have on the multilateral trading system under the umbrella of the World Trade Organization (WTO). This article will discuss the two Doha Transparency Mechanisms (legal transparency) regarding regional trade agreements, as they appear in two General Council decisions from 2006 and 2010. I will argue based on a closer look and a consistent interpretation of Paragraph 10 of the Doha Ministerial Declaration that there is another type of transparency that is relevant to the discussion on PTAs/RTAs, namely “internal transparency.” “Internal transparency stricto sensu” highlights the significance of trust in the WTO institutional processes, such as negotiations, decision-making, dispute settlement and trade monitoring that the representatives of developing member states should have in order for the WTO system to function productively. “Internal transparency lato sensu” is introduced in this article as an extension to include any decision-making deficits, exclusionary and asymmetrical outcomes specifically in the area of unchecked Preferential Trade Agreement proliferation. Instead of a conclusion, the article offers some proposals for more a meaningful progress in the WTO with respect to PTAs/RTAs The proposals aim at raising the profile of both legal and internal of transparency and posit that raising the profile of one will inevitably lead in improvements in the other.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.023
GPT teacher head0.299
Teacher spread0.276 · 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 designOther design
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

Citations1
Published2016
Admission routes1
Has abstractyes

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