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Record W4401912780 · doi:10.54648/aila2024034

The Carrier’s Defence to Liability for Delay under the Montreal Convention and EU Regulation 261/2004

2024· article· en· W4401912780 on OpenAlexaboutno aff
Ricardo Pazos

Bibliographic record

VenueAir and Space Law · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicLaw, logistics, and international trade
Canadian institutionsnot available
Fundersnot available
KeywordsLiabilityConventionPolitical scienceLawBusiness

Abstract

fetched live from OpenAlex

This paper analyses the specific defence to liability for delay available to carriers, comparing its features under the Montreal Convention (MC99) and EU Regulation 261/2004 (Regulation 261). The relationship between these legal instruments has never been an easy one, whereas recent case law of the Court of Justice of the European Union on the socalled ‘extraordinary circumstances defence’ invites to explore similarities and differences between the international and the European approaches. The scope of application of the defence is clearer in Regulation 261 than in MC99. The former will only affect cancellations and delays – not cases of denied boarding, and its impact remains limited to the lump-sum compensation set out in Article 7 of Regulation 261. In turn, MC99 covers delays, but it is uncertain whether it also encompasses cancellations and situations of denied boarding – particularly when the passengers concerned are provided alternate transportation. Moreover, the defence laid down in MC99 applies to damage occasioned by delay, but the definition of ‘damage’ is left to domestic law. This situation gives rise to diverging decisions by national courts. Regarding the conceptualization of the defence, the wording of the relevant provisions might lead to think that both instruments share a regime of liability for presumed culpability. However, the extraordinary circumstances defence is much more complex. As a consequence, there is no alignment between MC99 and Regulation 261, although points of convergence are highlighted.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score0.319

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 head0.247
Teacher spread0.229 · 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
Published2024
Admission routes1
Has abstractyes

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