Vaccination passports: Challenges for a future of air transportation
Bibliographic record
Abstract
COVID-19 has been a major setback for air transportation; many airlines had to request for bailouts and the international flights connectivity is only restarting slowly. Accordingly, many aviation stakeholders put hopes into the ongoing process of vaccination, with the expectation that a high degree of vaccination will push the envelope for a return to normalcy. One prerequisite for reviving international air connectivity is the introduction of verification documents, also called "vaccination passports". These passports, however, come with several challenges which need to be overcome in order to enable recovery. In this study, we propose a framework covering five important aspects and policy challenges concerning the introduction of vaccination passports for a return of aviation, covering the topics: Competition, Epidemiology, Technology, Ethics, and Politics. Neglecting to appropriately address these challenges will likely not only delay the recovery, but possibly miss an important opportunity before new disastrous events appear on the horizon.
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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 | 0.019 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.015 | 0.022 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.018 | 0.016 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".