The Creation of the Multilateral Trade Court: Design and Experiential Learning
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The creation of the World Trade Organization (WTO)'s dispute settlement system (DSS) in 1995 remains one of the most puzzling outcomes in international politics and international law in the 1990s. We provide a new explanation for this move to law. We argue that important contextual variables of the negotiations have been largely overlooked by existing explanations, namely ‘experiential learning’. While negotiations to create institutions are characterized by uncertainty about distributional effects, negotiators will look for clues that moderate uncertainty. In the context of the Uruguay Round negotiations, a significant amount of information was drawn from actual practice and experience with the existing General Agreement on Tariffs and Trade (GATT) dispute settlement system. In short, experience gained with judicial institutions and outcomes is important to understand the key results of the negotiations: a legalization leap, more specifically a judicialization of the existing dispute settlement system. We focus on the two dominant actors in the negotiations (the United States and the (then) European Community) and provide evidence for our argument based on an analysis of GATT cases in the 1980s, GATT documents, and in-depth interviews with negotiators who participated in the negotiations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it