MétaCan
Menu
Back to cohort
Record W4412676427 · doi:10.37859/jeq.v10i1.8209

LEGAL PROTECTION OF PASSENGERS FOR LOSS AND DAMAGE OF LUGGAGE ON AIR AIRLINES BASED ON THE 1999 MONTREAL CONVENTION AND NATIONAL LAW CASE STUDY RULING NUMBER 44/PDT-Sus-BPSK/2023/PN.PDG

2025· article· en· W4412676427 on OpenAlexaboutno aff
Reyna Pramesti, Sutiarnoto Sutiarnoto, Fajar Khaify Rizky

Bibliographic record

VenueJOURNAL EQUITABLE · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Policies and Emissions
Canadian institutionsnot available
Fundersnot available
KeywordsConventionLawPolitical scienceAeronauticsEngineering

Abstract

fetched live from OpenAlex

Air transportation plays a strategic role in the mobility of people and goods, but the risk of loss and damage to baggage is an important issue that requires legal regulation. The Montreal Convention 1999 and national laws, including Law Number 1 of 2009 concerning Aviation, provide the legal basis for airlines' liability to passengers. These regulations set limits on airline liability and compensation claim procedures that aim to provide protection and legal certainty for passengers. This study uses a descriptive method with a normative legal approach, utilizing primary, secondary, and tertiary data that are analyzed qualitatively. The results of the study indicate that the legal regulations related to airline liability for loss and damage to baggage are quite comprehensive. However, its implementation still faces obstacles, such as complicated and less transparent claim procedures. Incidents of loss or damage to goods have material and psychological impacts on passengers and can damage the airline's reputation. Therefore, steps are needed to improve the effectiveness of the implementation of the rules, including simplifying claim procedures, increasing transparency, and monitoring airline compliance in order to protect consumer rights.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.576

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.284
Teacher spread0.266 · 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 designSimulation or modeling
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

Explore more

Same venueJOURNAL EQUITABLESame topicEnvironmental Policies and EmissionsFrench-language works237,207