Mind the compliance gap: managing trustworthy partnerships for sustainable development in the European Union's free trade agreements
Bibliographic record
Abstract
Recent years have seen intensified interest in the labour and environment provisions in the EU's FTAs. The question has arisen whether the incorporation of 'trade and sustainable development' (TSD) chapters in the EU's FTAs deliver on their promise of using the EU's trade power to effectively promote the protection of the environment and improved working conditions in third countries. In particular, the compliance gap between the TSD provisions and their implementation has come to the forefront of the debate. Concerns have been raised that the EU's'promotional approach' based on dialogue and cooperation is less effective that the 'sanctions-based' approach followed by the US and Canada. This article examines the mechanisms for compliance in the TSD chapters in recent EU FTAs and argues that they hold greater promise for real improvements in labour and environmental standards than a sanctions-based enforcement system. However, it posits that, to be effective, and thereby gain the trust of civil society, the EU's 'promotional' approach must be supported by effective mechanisms for transparency, institutionalised dialogue and accountability.
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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 | 0.059 | 0.094 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.023 | 0.033 |
| Open science | 0.003 | 0.027 |
| Research integrity | 0.015 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".