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Record W4403162189 · doi:10.70082/esiculture.vi.1494

The Legal Approach to Investor Liability Conditions for Damage to Third Parties on the Ground within National Scope in the UAE Civil Aviation Law No. 20 of 1991 and the Saudi Civil Aviation Law No. 44 of 1426 AH: A Comparative Study

2024· article· en· W4403162189 on OpenAlexaboutno aff
Aser Mohamed Abou Deif

Bibliographic record

VenueEvolutionary Studies in Imaginative Culture · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicLaw, logistics, and international trade
Canadian institutionsnot available
Fundersnot available
KeywordsCivil aviationScope (computer science)Legal liabilityAviation lawLiabilityLawPolitical scienceCivil law (Civil law)AviationEngineeringPublic lawComputer science

Abstract

fetched live from OpenAlex

The damage caused by non-military aircraft to persons or property on the ground has long been a subject of international concern. Two key conventions were established to regulate liability arising from such damage: the 1952 Rome Convention, commonly known as the Rome Convention on “Damage Caused by Foreign Aircraft to Third Parties on the Surface,” and, later, the Montreal Convention of 2009, formally known as the “Convention on Compensation for Damage Caused by Aircraft to Third Parties.” The Montreal Convention was a result of the signatory states to the Rome Convention recognizing the need to review and update certain provisions. Both the United Arab Emirates and the Kingdom of Saudi Arabia are signatories to this convention. While international regulations play a significant role, domestic legislation is equally critical. It is therefore incumbent upon nations to enact clear legal provisions to regulate the liability of aviation investors for damage caused by aircraft to third parties on the ground, from a national legal perspective. This study addresses an issue of critical importance, namely the need for precise regulations that clarify the conditions of an aviation investor’s liability for damage to third parties on the ground within the national legal frameworks of the UAE and Saudi Arabia. Through comparative analysis, this research seeks to address the legislative gaps found in the UAE’s Civil Aviation Law No. 20 of 1991 on this matter.

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)0.002
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.725
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
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 head0.072
GPT teacher head0.333
Teacher spread0.261 · 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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