Bibliographic record
Abstract
The issue of whether and how the trading system should deal with social and economic policies not strictly within the ambit of the WTO has been with us at least since the inception of the GATT in 1947-1948. It is not a new question. The problem, however, has become even more vexing since the 1970s, as tariffs became less important in trading relationships and governments struggled to respond to a proliferation of nontariff barriers to trade. I will argue, in this Afterword, that the question is not whether the WTO should or should not deal with the “trade and … ” subjects—trade and environment, trade and public health, trade and labor rights, trade and human rights, trade and competition, trade and investment, and trade and intellectual property, to name a few. It already does and has done so, in many respects, since 1948. The question I would pose is this: how should these so-called nontrade subjects be dealt with within the WTO system? And who should define the scope of WTO recognition/cognizance of these subjects: WTO member governments (the “Members”) or the quasi-judicial bodies of the dispute settlement system (the panels and the Appellate Body)?
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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.072 | 0.062 |
| Insufficient payload (model declined to judge) | 0.011 | 0.010 |
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".