Mending Dispute Resolution under the International Health Regulations
Bibliographic record
Abstract
Abstract International dispute resolution not only aims to redress wrongdoings, but also to deter states from violating obligations. Approaching the International Health Regulations (ihr) from this viewpoint and using recent global health crises as examples, this paper argues that dispute resolution must be strengthened in the ihr in order to protect global health security. While a diverse range of dispute resolution mechanisms exist in other legal regimes, this paper proposes that a three-pronged architecture consisting of a guidance mechanism, formal adjudicative mechanism, and recourse to the icj and binding arbitration would provide for the most efficient and timely response to a dispute between states parties. Importantly, this architecture can be used both prior to and during a global health crisis, and could incentivize states parties towards solidarity in the global public health response.
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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 | 0.095 | 0.096 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.015 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 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".