Bibliographic record
Abstract
When officials from different countries disagree about trade policy, some say ‘see you in Geneva!’ meaning ‘see you in court!’ In offering a pluralist alternative to this centralism of analysts and practitioners, I represent the World Trade Organization (WTO) not as a coercive court used for enforcement but as a site for the elaboration of a system of ‘law’ that arises from and provides a framework for self-directed human interaction. Trade law is shaped in the shadow of bargaining. I contrast this legal representation with ‘legalization’ to show the contribution it makes to constructivist international theory. An empirical probe in the contentious domain of the WTO Agreement on Sanitary and Phytosanitary Measures (SPS) asks about the relative importance of the few formal SPS ‘disputes’ compared with other ways that WTO law affects global food safety. A discussion of how the trading system responded to ‘mad cow disease’ (BSE) provides empirical confirmation of pluralist insights. Far from being only in Geneva, trade law is everywhere.
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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.038 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".