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Record W2906946066 · doi:10.4337/9781786435200.00011

International and EU legal frameworks of aviation security

2018· book-chapter· en· W2906946066 on OpenAlexaboutno aff
F. Rossi Dal Pozzo

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInternational Law and Aviation
Canadian institutionsnot available
Fundersnot available
KeywordsAviationConventionTerrorismAviation lawAirport securityPolitical scienceCivil aviationInternational tradeAir transportBusinessLawEngineeringComputer securityAeronauticsComputer science

Abstract

fetched live from OpenAlex

Chapter 4 stresses the intrinsic international nature of air transport and travel and the consequent need to implement a common legal framework. The legal initiatives related to aviation security started to emerge in the 1960s as an answer to the first wave of hijackings and were substantiated in the Tokyo Convention in 1963. Subsequent terrorist related hijackings led to the Hague and Montreal Conventions. The consequent regulations were changed in the decade following the tragic events of September 11, 2001 by enhancing the security protocols within the aircrafts and at the airports. Such measures should be commensurate with the risks and should take into account cost-benefit ratio analyses. The chapter then considers the EU regulations for aviation security since the September 11 events. A further section of the chapter discusses the passenger name records that started as a commercial initiative and were converted to a security protocol since 2004.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0030.008
Scholarly communication0.0090.006
Open science0.0010.003
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0120.003

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 head0.014
GPT teacher head0.267
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations4
Published2018
Admission routes1
Has abstractyes

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