forthcoming, Canadian Journal of Economics Trade Policy under the GATT/WTO: Empirical Evidence of the Equal Treatment Rule
Bibliographic record
Abstract
A fundamental difference between multilateral trade agreements like the GATT and WTO and preferential trade agreements is the multilateral agreements ’ inclusion of a most-favoured-nation (MFN) principle. Though this principle requires that members implement policies that provide equal treatment to all GATT/WTO countries, an open question is the extent to which members actually follow the MFN principle when the rules so require. This paper is a first attempt to address this question empirically, and to do so, we use a sample of GATT/WTO trade disputes to investigate the effect of successful dispute settlement negotiations on the trade of third country exporters to the defendant country. We document evidence on the pattern of liberalization resulting from trade disputes that is consistent with defendant countries successfully applying the GATT/WTO’s equal treatment rule to the trade of third countries. JEL No. F13
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".