Exploring Models for an International Legal Agreement on the Global Antimicrobial Commons: Lessons from Climate Agreements
Bibliographic record
Abstract
An international legal agreement governing the global antimicrobial commons would represent the strongest commitment mechanism for achieving collective action on antimicrobial resistance (AMR). Since AMR has important similarities to climate change-both are common pool resource challenges that require massive, long-term political commitments-the first article in this special issue draws lessons from various climate agreements that could be applicable for developing a grand bargain on AMR. We consider the similarities and differences between the Paris Climate Agreement and current governance structures for AMR, and identify the merits and challenges associated with different international forums for developing a long-term international agreement on AMR. To be effective, fair, and feasible, an enduring legal agreement on AMR will require a combination of universal, differentiated, and individualized requirements, nationally determined contributions that are regularly reviewed and ratcheted up in level of ambition, a regular independent scientific stocktake to support evidence informed policymaking, and a concrete global goal to rally support.
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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) | 0.000 | 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 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".