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Record W4414190445 · doi:10.54648/aila2025046

Mental Injury Damages under the Montreal Convention 1999 as Developed by the United States

2025· article· en· W4414190445 on OpenAlexaboutno aff
Andrew J. Harakas

Bibliographic record

VenueAir and Space Law · 2025
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsnot available
Fundersnot available
KeywordsDamagesScope (computer science)ConventionNegotiationMeaning (existential)Mental illnessPoison control

Abstract

fetched live from OpenAlex

The issue of the availability of mental injury damages under the Montreal Convention continues to be debated despite the efforts made in the negotiations and drafting to retain existing language to preserve judicial precedent relating to the Warsaw Convention, thereby avoiding unnecessary litigation over issues already decided by the courts. In the United States (US), courts had achieved a consensus that pure mental injuries were not recoverable under the Warsaw Convention because such injuries cannot be considered a ‘bodily injury’ within the meaning of Article 17, but recovery was allowed for mental injuries to the extent they were caused by or flowed from a bodily injury. Recent decisions in the US (and the European Union) have upset this consensus and uncertainty exists as to the availability and scope of such damages under the Montreal Convention. The courts in the US are once again divided as to the whether the mental injury must flow from a ‘bodily injury’ and the EU has taken this even further by eliminating the need for any ‘bodily injury’ for the recovery of mental injury damages. This article provides an overview of the law in the US related to the recovery of mental injury damages under the Warsaw Convention, the development of the law under the Montreal Convention and how some courts have reverted to the view rejected over thirty years ago that mental injury damages are allowed under the Article 17 even if unrelated to the bodily injury.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.018
GPT teacher head0.358
Teacher spread0.340 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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