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Record W2618241904 · doi:10.54648/ijcl2017013

The Comprehensive Economic and Trade Agreement (CETA): Are Existing Arrangements Sufficient to Prevent Adverse Effects on Labour Standards?

2017· article· en· W2618241904 on OpenAlexaboutno aff
Franz Christian Ebert

Bibliographic record

VenueInternational Journal of Comparative Labour Law and Industrial Relations · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Labor and Employment Law
Canadian institutionsnot available
Fundersnot available
KeywordsInternational tradeBusinessEconomicsInternational economicsLabour economics

Abstract

fetched live from OpenAlex

The Comprehensive Economic and Trade Agreement (CETA) negotiated between the EU and Canada has given rise to concerns in terms of its effects on labour standards. This article analyses the arrangements available under CETA to address risks for labour standards entailed by the Agreement and what effects can be expected of these arrangements in practice. For this purpose, labour provisions as well as exception clauses, impact assessments and the Joint Interpretative Instrument pertaining to the Agreement are considered. In the final section it is argued that none of the arrangements examined is sufficient to guarantee that CETA will not result in undercutting domestic labour standards, while several avenues are explored for improving the design of the Agreement and better safeguarding labour standards.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.066
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.053
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0080.020
Scholarly communication0.0120.008
Open science0.0030.007
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0040.001

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 head0.083
GPT teacher head0.389
Teacher spread0.306 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations11
Published2017
Admission routes1
Has abstractyes

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