The World Health Organization, International Health Regulations and Human Rights Law
Bibliographic record
Abstract
Abstract This article examines the influence of human rights law on infectious disease control through the World Health Organization (who) International Health Regulations (‘IHR’). The who’s evolving work to mainstream human rights in global health governance strongly influenced the 2005 revision of the ihr, framing a new balance between health and human rights in public health emergencies. The 2005 ihr make respect for human rights a central principle and integrate human rights standards in explicit and implicit ways. Yet these reforms also fail to reflect economic, social and cultural rights, inadequately connect to the UN human rights system, and leave unresolved significant legal issues with major impacts on human rights. These weaknesses have been exposed by the covid-19 pandemic, as national pandemic responses have tested who’s authority under the ihr and disproportionately and unjustifiably restricted a range of human rights. Resolving these gaps will require both normative and institutional reforms that bring together human rights and global health governance, including through broader rights-based partnerships amongst international organizations.
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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 | 0.028 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.017 | 0.013 |
| 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".