An Analysis of the Grounds of Jurisdiction and Jurisdictional Issues of e-Ticketing in Light of the Warsaw/Montreal System
Bibliographic record
Abstract
In June 2008, the commercial aviation industry moved to 100% electronic ticketing. The advantages of this process are numerous and cannot be underestimated. On the other hand, the extent of this phenomenon has induced the airlines to become web portals. Given the World Wide Web and its global application, the most compelling legal question in this respect would seem to pertain to the transboundary applicability of a contract of air carriage concluded via the Internet. The characteristics of a cyber contract, namely the physical distance between the parties and the fact that the conclusion of the contract is achieved through action other than traditional signature, raises issues both on a theoretical and practical level. Consequently, two questions need to be answers: (i) when is the contract to be deemed as concluded; and (ii) where did the “meeting of the minds” effectively occur? This paper is designed to provide a comprehensive analysis of the international framework regarding jurisdictional issues within the context of private air law. In doing so, the main legal instruments, such as the Warsaw and the Montreal Conventions, will be taken into consideration, both from an academic and a practical perspective. Recent trends in the airline business, such as e-ticketing, suggest addressing attention to a number of emerging legal categories, which are expected to play a topical role in the future.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
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".