Who Are “the Parties” for Purposes of <i>VCLT</i> Article 31(3)(c)? A Case Study in WTO Pragmatism
Bibliographic record
Abstract
Article 31(3)(c) of the Vienna Convention on the Law of Treaties (VCLT) provides that a treaty interpreter must take into account “any relevant rules of international law applicable in the relations between the parties.” The meaning of “the parties,” and more specifically whether there is a precondition that all parties to the treaty being interpreted must also be parties to the other treaty for the latter to qualify under Article 31(3)(c), has been the subject of much academic debate. The question does not necessarily have an obvious answer, and has been seen as being a consequential issue in the WTO context because of a perception among some commentators that: (a) taking non-WTO treaties into account could be a decisive consideration in the interpretation of certain WTO provisions; and (ii) under a strict reading of “the parties”, very few non-WTO treaties would meet the requisite threshold. This article explains how WTO adjudicators have pragmatically bypassed and largely defused this contentious issue by referring to non-WTO treaties effectively as “supplementary means” of interpretation, or, more commonly, as evidence of facts—purposes that arguably could fall outside the purview of Article 31(3)(c).
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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 | 0.026 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.034 | 0.034 |
| Scholarly communication | 0.021 | 0.014 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.021 | 0.018 |
| 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".