MétaCan
Menu
Back to cohort
Record W4389583895 · doi:10.25172/jalc.88.4.5

Navigating Through Cloudy Skies: The Montreal Convention & Article 17 “Accidents” Post-Moore

2023· article· en· W4389583895 on OpenAlexaboutno aff
Elan Wilson

Bibliographic record

VenueJournal of Air Law and Commerce · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Aviation
Canadian institutionsnot available
Fundersnot available
KeywordsConventionTreatyConfusionLawAccident (philosophy)Event (particle physics)Supreme courtPerspective (graphical)Air transportPetitionerAviationRubricOperations researchLaw and economicsPolitical scienceSociologyEngineeringComputer scienceAeronauticsPsychology

Abstract

fetched live from OpenAlex

The Montreal Convention is a multilateral treaty that comprehensively regulates international air carriers. Specifically, Article 17 of the treaty allows passengers to recover against air carriers for injuries or deaths on international flights, so long as certain requirements are met. In Air France v. Saks, the Supreme Court held that “accident”—a controlling term in Article 17—describes an event that is external to the passenger and “unexpected or unusual.” Last year, in Moore v. British Airways PLC, the First Circuit purported to identify a split over what this language means. According to Moore, there are courts who (correctly) gauge whether an event is unexpected or unusual from the perspective of an airline passenger with ordinary experience in commercial air travel (an objective standard that I will call the Reasonable Passenger Approach). On the other hand, there are courts who (incorrectly) determine whether an event is unexpected or unusual from the perspective of the airline industry, using industry norms and customs as guides (a standard I will call the Industry Approach). In this Comment, I will explain why the standard endorsed by the First Circuit in Moore muddies the waters and how a more holistic, totality-of-the-circumstances approach (the Holistic Approach) offers a better rubric for Article 17 “accident” analyses. Given the recency of the Moore case, my goal in this Comment is to provide timely insight on its blind spots while offering an approach that might rescue Moore from a legacy of confusion.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.768
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.344
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Air Law and CommerceSame topicInternational Law and AviationFrench-language works237,207