The Right to Safe Transport + Air Passenger Rights After COVID-19
Bibliographic record
Abstract
The coronavirus crisis has been extremely disruptive for the international passenger transportation market. It has also triggered a major legal disruption in the field of passenger rights. In recent decades, the focus of air passenger policy has largely shifted from safety to rights in case of delay and cancellation, a change predominantly induced by the EU. COVID-19 has led to a major paradigm shift, with safety again becoming the number one policy target. Passengers have a wide range of tools to enforce their rights to timely travel and these remedies have made an effective contribution to a reduction in delays and cancellations in air transport. Passengers’ remedies in case of unsafe transport seem largely limited to the possibility of bringing an action in case of bodily injury, lésion corporelle, based on the Montreal Convention (MC). This contribution aims firstly to evaluate the effectiveness of this remedy as a preventive tool for increasing passenger safety. Secondly, it aims to assess the impact of COVID-19 on existing passenger rights in respect of cancellation and delay, as well as the impact of existing passenger rights policy on airlines’ operational margin for enhanced safety management. Based on this analysis, we aim to make recommendations for a more effective model for the protection of passengers’ safety, while at the same time embedding safety in the existing passenger rights policy instead of overriding it. Sommaire: La crise du coronavirus a extrêmement perturbé le marché du tra
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.009 | 0.006 |
| 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".