Trade Agreements and Sustainability: Exploring the Potential of Global Value Chain (GVC) Obligations
Bibliographic record
Abstract
ABSTRACT This article investigates the potential of global value chain (GVC)-orientated sustainability provisions in regional and bilateral trade agreements (FTAs). Such provisions impose social and environmental obligations directly onto GVCs, as opposed to creating obligations for governments. The theoretical potential of GVC provisions is examined, and the concepts of effectiveness and legitimacy are introduced as values by which to assess them. Four recent sets of provisions are then scrutinized. These are (i) palm oil sustainability standards from the Indonesia–European Free Trade Association (EFTA) Comprehensive Economic Partnerhsip Agreement (CEPA) FTA, (ii) hen welfare standards in the European Union–Mercosur Association Agreement, (iii) a stipulation of a minimum average wage for the automobile industry in the US–Mexico–Canada Agreement (USMCA), and (iv) enforcement of collective bargaining and freedom of association directly against factories, also in the USMCA. All of these provisions are found to have significant deficiencies. At the same time, it is argued that three different governance models underpin them, namely (i) third-party certification schemes, (ii) domestic regulations of one of the parties, and (iii) bespoke arrangements created for the FTA in question. The article therefore considers the potential and drawbacks of each governance model in terms of their effectiveness and legitimacy, as well as alternative and complementary commitments including unilateral measures and subject-specific trade agreements.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.019 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
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".