‘Someone call a global health lawyer!’: global health law as an emerging community of practice
Bibliographic record
Abstract
Despite the recent expansion of efforts to delineate the normative and institutional contours of global health law, relatively little has been said of the human agents shaping this young field. This article offers a first descriptive account of global health law as an emerging community of practice, composed of, among others, scholars and teachers, advisers, practitioners and advocates who engage international legal norms in an effort to influence global health. Given the potential sway this community holds over the making, interpretation and application of norms that have bearing on global public health, the article calls for a practice of reflexivity and an ethic of care by self-professed ‘global health lawyers’.
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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 | 0.034 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.145 |
| Scholarly communication | 0.022 | 0.028 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.016 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 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".