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Record W2561912308 · doi:10.54648/aila2016020

Pioneering for Rights of the Differently Abled: Scope under the Montreal Convention

2016· article· en· W2561912308 on OpenAlexaboutno aff
Nivedita Raju, Ramya Sankaran

Bibliographic record

VenueAir and Space Law · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Aviation
Canadian institutionsnot available
Fundersnot available
KeywordsConventionDamagesHarmLawPolitical scienceScope (computer science)Interpretation (philosophy)DutyPhilosophyComputer science

Abstract

fetched live from OpenAlex

The ruling of Stott v. Thomas Cook heralded the ‘exclusivity principle’ of the Montreal Convention for future claims for damages. However, the case simultaneously raised concerns regarding the rights of differently abled air passengers. Mr Stott, partially paralysed, was denied all his requests for assistance. This resulted in a series of traumatic events following which, Mr Stott suffered severe emotional harm. When Mr Stott claimed damages under the concerned EC Regulations, it was held that the Convention would be applicable exclusive to all other laws. This article examines a new line of reasoning in arguments for differently abled passengers, in light of the circumstances of Stott. The article identifies relevant international and national legislations on rights of differently abled passengers to substantiate a claim under the Convention, from a fresh perspective, without overturning the exclusivity principle. The authors argue that failure of an airline to abide by prevailing national and international laws on disability rights amounts to an ‘unexpected event’ and breach of duty of care, thereby falling within the purview of an ‘accident’ under the Convention. Applying abundant case law on the interpretation of Article 17, the authors aim to craft a successful claim for damages for differently abled air passengers, under selected circumstances unexplored by courts, within the confines of the Convention.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.989

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 head0.011
GPT teacher head0.257
Teacher spread0.246 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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