Bibliographic record
Abstract
I once attended a talk by a Canadian trade negotiator who made the following potent statement: “When multilateralism falters, regionalism picks up the pace.” His use of the term multilateralism referred to the GATT/WTO system described in Chapter 7 and its multilateral trade negotiations. His use of the term regionalism referred informally to the possibility of pursuing what are formally known as preferential trade agreements (PTAs). Recall that one of the founding principles of the GATT/WTO system is nondiscrimination , and that nondiscrimination, in turn, involves the most favored nation (MFN) and national treatment (NT) sub-principles. Under MFN, each WTO member must grant to each other member treatment as favorable as they extend to any other member country. PTAs are a violation of the nondiscrimination principle in which one member of a PTA discriminates in its trade policies in favor of another member of the PTA and against nonmembers. This discrimination has been allowed by the GATT/WTO under certain circumstances. These circumstances include the well-known cases of free trade areas (FTAs), customs unions (CUs), and interim agreements leading to a FTA or CU “within a reasonable length of time.” Before we begin, we need to clarify an issue of terminology. Originally, FTAs and CUs were collectively known as regional trade agreements (RTAs), and this is the term commonly employed by the WTO. However, since the 1990s, an increasing number of FTAs have been between or among countries that are not geographically contiguous , such as the Canada-Chile and Japan-Mexico FTAs. Consequently, a number of leading economists and trade lawyers have recommended that the RTA nomenclature be replaced with that of PTAs. In the spirit of greater accuracy, we use this term here, but it is likely that you will encounter both terms and their acronyms.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.047 | 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".