Bibliographic record
Abstract
Regional blocs have spread to the whole world with usual speed. Some believe the box was opened by the Western Europe when they consolidated their European Economy Community by the Single Market Imitative that took effect in 1992 and by the Maastricht Treaty. Others blame the United States for the final shift when it signed a free trade agreement with Canada in 1988 and abandoned its forty years of opposition in principle to regional initiative. The new wave of calls a controversy. Nobody is excited about the new wave and opportunities it has brought about, but fear it may corrupt the efforts of the General Agreement on Tariffs and Trade (GATT) or the World Trade Organization (WTO) to make progress toward global free trade. In the early 1950s, Viner called economists' attention to the distinction between trade-creation and trade-diversion effects of regional FTAs. In order to minimize the possibility of welfare-reducing trade blocs, the notion of regionalization is proposed. Trade blocs are required to satisfy the McMillan criterion of not lowering their trade volume with outside countries; they have to engage in a reduction of trade barriers against nonmember countries. Obviously, this is a particular form of open regionalism. We should note that, while an regionalism with a modest external liberation can be welfare improving, multilateral trade liberalization can be even more so.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".