A Closer Look At WTO’s Third Pillar: How WTO Committees Influence Regional Trade Agreements
Bibliographic record
Abstract
This paper illustrates how the work of World Trade Organization’s (WTO) standing bodies—its ‘Third Pillar’, as we will call it—is inspiring parties in regional trade agreements (RTA) negotiations and contributing to deeper integration. We focus on the work of the WTO technical barriers to trade (TBT) Committee and explore, as a case study, the extent to which the Committee's decision on principles for development of international standards (the Six Principles) has shaped provisions in RTAs. This Decision, arguably the most important decision taken by the TBT Committee, is meant to clarify which international standards may be a relevant basis for TBT measures; an issue that has been left undefined under the WTO TBT Agreement. Our analysis covers 260 RTAs, and shows that one quarter of RTAs has sharpened and hardened the Committee’s decision by making it directly applicable to Parties (in RTAs) whereas under the WTO they are ‘merely’ recommendations. A small number of RTAs follow a different approach and explicitly name the sources of relevant international standards.
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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 | 0.042 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.026 | 0.015 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.010 |
| 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".