Adjustment and Integration of International and Domestic Rules on Compensation for Damage to Checked Luggage of Air Passengers—Focusing on the Montreal Convention and China's Civil Aviation Law
Bibliographic record
Abstract
In 2024, the Montreal Convention raised the compensation limit for checked luggage to 1,519 Special Drawing Rights (SDRs). This revision further highlights the lag and shortcomings of China's Civil Aviation Law and its supporting regulations in aligning with international conventions. To address the challenges of integrating international and domestic rules on compensation for damage to checked luggage, this study conducts a comparative analysis of the core provisions of the Montreal Convention and China's Civil Aviation Law, supplemented by an empirical analysis of the case Lou Mengjie v. Aeroflot Russian Airlines. The research identifies key differences between the two frameworks in terms of compensation limits and scope of application, while also revealing practical integration difficulties, such as the chaotic application of mixed transportation rules, the disconnect between the domestic compensation limit of 100 yuan per kilogram and actual losses, and deviations in the judicial application of the convention. Grounded in the theory of transformative domestication, the study proposes a three-dimensional optimization approach: unifying core convention systems through legislation, standardizing the application of laws in judicial practice, and establishing a dynamic regulatory mechanism through administrative measures. This provides actionable solutions for aligning China's aviation laws with international rules, ultimately achieving the dual goals of protecting passenger rights and promoting the sustainable development of the aviation industry.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".