The world trade regime, the WTO and large scale crises: Perspectives after the Pittsburg G20 Summit
Bibliographic record
Abstract
One year after the collapse of Lehman Brothers and three years after the start of the food and commodities crisis, time seems ripe to make a provisional assessment of the resilience of the open trade policies to this severe downturn, and to draw the main lessons. In attempting to answer this question, we need to make a distinction between the "world trade regime" and the World Trade Organization (WTO). The former consists in all the multilateral, plurilateral and unilateral trade policies. Sometimes such policies amplify WTO weaknesses. But, sometimes they amplify WTO disciplines, as during the past year (see section 1). The WTO, with its key disciplines and its dispute settlement mechanism, is the undisputed legal skeleton of the world trade architecture. But, it is in a great need to adjust to a faster-moving, often chaotic, world trade regime. The distinction between the WTO and the world trade regime is even more crucial since the designation of the G20 as the "premier forum" for the international economic cooperation between the largest world economies [Pittsburgh Summit communiqué]. Korea which holds the G20 Chair for 2010 (and Canada the host the G20 in Spring) will have the major task to develop this new architecture--weaving together the G20, the WTO and the other traderelated international institutions.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| 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".