Tribute to Gabrielle Marceau upon her Retirement from WTO: How to Reconcile Trade Law with Human Rights, Gender, Labour and Social Concerns in WTO Law, Jurisprudence and How to Reform it?
Bibliographic record
Abstract
This article pays tribute to Gabrielle Marceau’s lifelong commitment to linking international trade law with broader societal objectives such as human rights, gender, labor, and social standards. It examines the persistent tensions between trade liberalization rules and measures taken to guarantee and enforce human rights, particularly when they affect cross-border trade and are based on traditional concepts of “likeness” of goods or services, and differentiation between product-related and non-product-related productions and processing methods. It shows how World Trade Organisation (WTO) law exceptions—most notably Article XX of the General Agreement on Tariffs and Trade and Article XIV of the General Agreement on Trade in Services —have evolved into nuanced proportionality tests that grant states more policy space for pursuing legitimate societal objectives. The analysis is structured around several themes: the ways in which human-rights-related measures can be justified under WTO law; the shift in case law from rigid necessity tests to a more balanced weighing of relevant factors; and the question of which rights are most effectively pursued through trade measures, with economic and social rights emerging as the more promising than civil and political human rights. The analysis proceeds to address at which level, domestically, regionally or multilaterally, human rights are most effectively guaranteed or enforced. The article highlights that many WTO rules, for example in the Agreement on Technical Barrier to Trade , or the Agreements on Sanitary and Phytosanitary Measures and Trade-Related Intellectual Property Rights , already integrate legitimate societal concerns, and that incentive-based tools often work better than sanctions. Finally, it argues for reform of the Agreement on Subsidies and Countervailing Measures to allow more space for subsidies that pursue social or environmental objectives, and for approaches that reduce fragmentation and protectionist abuse, thereby aligning trade disciplines more closely with the promotion of human rights. The article concludes by highlighting the growing role of producers, traders and consumers in respecting human rights along international supply chains, when climate change mitigation and geostrategic rivalries pose challenges that overwhelm governments and multilateralism.
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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 | 0.016 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.023 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.025 | 0.036 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".