Solidarity in the Wake of COVID-19: Reimagining the International Health Regulations
Bibliographic record
Abstract
Amid frenzied national responses to COVID-19, the world could soon reach a critical juncture to revisit and strengthen the International Health Regulations (IHR), the multilateral instrument that governs how 196 states and WHO collectively address the global spread of disease.1,2 In many countries, IHR obligations that are vital to an effective pandemic response remain unfulfilled, and the instrument has been largely sidelined in the COVID-19 pandemic, the largest global health crisis in a century. It is time to reimagine the IHR as an instrument that will compel global solidarity and national action against the threat of emerging and re-emerging pathogens. We call on state parties to reform the IHR to improve supervision, international assistance, dispute resolution, and overall textual clarity.
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 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 | 0.052 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.054 |
| Scholarly communication | 0.026 | 0.020 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.014 | 0.030 |
| Insufficient payload (model declined to judge) | 0.006 | 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".