Tackling labour rights and environmental protection through trade and Sustainable Development Chapters: the European approach
Bibliographic record
Abstract
The present chapter seeks to clarify the EU policy direction as regards trade and sustainable development within its trade agenda by providing a comparative analysis of selected TSD standards, taking particular account of the EU-Korea, as the first "new generation" FTA, and the ensuing trade agreements with Colombia, Peru and Ecuador, Central America, Singapore, Vietnam, Canada, Japan and Mexico, as well as recent strategic EU Commission documents on TSD reform. It also touches upon the current trends as regards the TSD enforcement, including the EU's consultations with the Republic of Korea on its failure to implement core labour commitments and the implications of the European Court of Justice's Opinion 2/15 implying the possibility to withdraw trade concessions in case of breach of TSD clauses. It finds some marginal improvements as regards the scope of TSD chapters, especially in the most recent EU trade agreements, however, it still concludes that the current approach with a limited substantive scope combined with the weak enforcement mechanism might undermine the effectiveness of implementation of the TSD chapters. Also, not much has been offered under the strategic EU Commission's documents on the TSD reform. At the same time, the paper finds a substantial potential in keeping up a sustained dialogue between the trading partners with the involvement of civil society groups, which, however, could be also stepped up in future negotiations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".