Bibliographic record
Abstract
This paper develops a framework for analyzing how international courts promote compliance with international law. It first formulates a matrix of four approaches through which international courts promote compliance. Integrating theories of international relations and international law, the matrix has two fault lines based on the logic (rationalist logic of consequences or constructivist logic of appropriateness) and means (direct or indirect) of international courts’ impact. The paper then accounts for the variation in courts’ approaches based on their independence, access, and convergence. A structured, focused comparison of four cases (the World Trade Organization’s Dispute Settlement Understanding, the European Court of Justice, the International Criminal Court, and the African Court on Human and Peoples’ Rights) reveals that courts’ approaches can be consistent or evolve considerably over time. The comparative analysis indicates that, when courts develop approaches over time, high access levels provide them the opportunity to adopt indirect approaches, and low convergence levels can draw courts towards the constructivist approaches. Thus, the paper serves to explain the significant variation in how international courts promote compliance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.005 | 0.005 |
| 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".