Travel restrictions and variants of concern: global health laws need to reflect evidence
Bibliographic record
Abstract
As the coronavirus disease 2019 (COVID-19) spread in the early days of the pandemic, governments neglected World Health Organization (WHO) guidance and imposed travel restrictions. These public health measures employed varied levels of restrictiveness at national borders, in some cases banning all travel between countries. Where these border control measures were undertaken for domestic political reasons, enacted without consideration of public health evidence, they divided the world when solidarity was needed most.1 Such measures undermined global health law that countries have established as a foundation for preventing and responding to public health emergencies of international concern. \n \nWith the emergence of the Omicron variant, national governments once again returned to international travel restrictions, posing challenges for the rule of law in global health governance. Future reforms of global health law must account for this continuing impulse to enact travel restrictions, ensuring that international legal obligations reflect evolving public health evidence.
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 | 0.054 | 0.247 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.025 |
| Scholarly communication | 0.016 | 0.037 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.010 | 0.020 |
| Insufficient payload (model declined to judge) | 0.012 | 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".