Bibliographic record
Abstract
Abstract Private standards are increasing in number, and they affect trade, but their status in the WTO remains problematic. Standards-takers are typically countries with little bargaining power, who cannot affect their terms of trade, and, thus, even if they possess domestic antitrust laws, will find it hard to persuade standard-setters to take account of their interests. Our concern is to bring more of these standards within the normative framework of the trade regime – that is, we worry that these private forms of social order can conflict with the fundamental norms of transparency and non-discrimination. The WTO membership has consumed itself in endless discussions regarding mundane, legalistic issues, and has not moved at all towards addressing the real concerns of developing countries. We discuss one aspect of the problem: How reclusive should the WTO allow product standards to be? We argue that the WTO should adopt a ‘Reference Paper’ that would encourage its members to apply WTO rules for adopting those standards that already come under the aegis of the WTO to private standards. In the absence of centralized enforcement, utopia in the WTO legal paradigm, transparency disciplines imposed on standard-setters is the best the WTO could offer to those who are negatively affected by private standards.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.043 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.025 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.016 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 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".