Human Rights in Global Health: Rights- Based Governance for a Globalizing World edited by Benjamin M. Meier and Lawrence O. Gostin1
Bibliographic record
Abstract
THIS GROUNDBREAKING COMPILATION, edited by two scholars who helped to establish the “health and human rights” field, systematically explores the structures and processes of human rights implementation in global health institutions while arguing that a rights-based approach to health governance advances global health. The 640-page volume brings together forty-six experienced scholars and practitioners who have contributed to twenty-five chapters organized into six thematic sections. This “unprecedented collection of experts” provides unique, hands-on insights into how the “institutional determinants of the rights-based approach to health” facilitate—or hinder—the “mainstreaming” of human rights into global health interventions. The institutional determinants, which—in the contributors’ view—promote the effective integration of human rights implementation into global health governance are: governance (formal commitments, human rights leadership, and member State support), bureaucracy (institutional structure and human rights culture), collaborations (inter-organizational partnerships and civil society participation), and accountability (internal monitoring and independent evaluation).
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 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 | 0.001 | 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 | 0.003 | 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".