CHAPTER F-4 Border Closures: A Pandemic of Symbolic Acts in the Time of COVID-19
Bibliographic record
Abstract
COVID-19 provoked unprecedented national border closures.Some countries stopped travel from particular regions, despite evidence that such closures are ineffective and illegal under the International Health Regulations (IHRs).Even more countries banned all incoming travel by non-citizens.It has been suggested that these more restrictive total border closures are theoretically effective and arguably permissible under international law.Yet a closer analysis reveals that total border closures are probably still illegal given the IHRs require countries to adopt less restrictive alternatives when possible, such as a 14-day quarantine order for incoming travellers.If border closures are largely ineffective and illegal, then why have at least 142 countries implemented them?The answer lies in the realities of politics.Even if governments know the science and law of border closures, they still feel compelled to enact them because of intense domestic pressure * Dahdaleh Distinguished Chair in Global Governance and Legal Epidemiology, and Professor of Global Health, Law, and Political Science at
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 0.006 |
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".