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Record W3096948612 · doi:10.46850/elni.2016.009

Sustainability and precautionary aspects of CETA dissected

2016· article· en· W3096948612 on OpenAlexaboutno aff
Wybe Th. Douma

Bibliographic record

Venueelni Review · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityInclusion (mineral)International tradePrecautionary principleMember stateEconomicsInternational economicsMember statesBusinessPolitical scienceLaw and economicsEuropean unionSociology

Abstract

fetched live from OpenAlex

The Comprehensive Economic and Trade Agreement (CETA) between the EU, its Member States and Canada has been presented as “the best trade agreement the EU has ever negotiated”. While there are certainly many advantages compared to older trade treaties, two remaining points of concern are investigated in this contribution. The first one relates to the manner in which the EU utilises its own system for ensuring that sustainability concerns are integrated into trade agreements. In the first part of this contribution, it is investigated whether the manner in which the integration instrument is employed in the case of CETA, notably where the inclusion of an investor state dispute settlement (ISDS) mechanism is concerned, is in line with consistent, evidence-based policy choices and with the self-imposed guidelines as laid down in the so-called Trade Sustainability Impact Assessment (TSIA) Handbook. The second part of this contribution investigates whether the continued implementation of the precautionary principle on the side of the EU is properly secured in the view of the various rules, procedures and institutional arrangements contained in the CETA text. In that respect, the findings of a detailed study on this topic are summarised first, after which some of the critique from the side of the Dutch Minister of Foreign Trade and Development Cooperation and from the EU Commissioner for Trade is examined and commented upon.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.944
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.307
Teacher spread0.296 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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