The Politics of Judicial Economy at the World Trade Organization
Bibliographic record
Abstract
Abstract International institutions often moderate the legal decisions they render. World Trade Organization (WTO) panels do this by exercising judicial economy. This practice, which is evident in 41 percent of all rulings, involves the decision not to rule on some of the litigants' arguments. The constraint is that it can be appealed. We argue that panels exercise judicial economy when the wider membership is ambivalent about the future consequences of a broader ruling. This is proxied by the “mixed” (that is, nonpartisan) third-party submissions, which are informative because they are costly, jeopardizing a more decisive legal victory that would benefit these governments too. We empirically test this hypothesis, and find that mixed third-party submissions increase the odds of judicial economy by upwards of 68 percent. This suggests that panels invoke judicial economy to politically appease the wider WTO membership, and not just to gain the litigants' compliance in the case at hand.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".