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Record W7026824931

Aviation Security: Terrorist Acts Demonstrate Urgent Need to Improve Security at the Nation's Airports

2001· article· en· W7026824931 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2001
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy and History of Science
Canadian institutionsnot available
Fundersnot available
KeywordsAirport securityAviationLimitingTerrorismCivil aviationLaw enforcementStrengths and weaknessesEnforcementControl (management)
DOInot available

Abstract

fetched live from OpenAlex

Testimony issued by the General Accounting Office with an abstract that begins "A safe and secure civil aviation system is a critical component of the nation's overall security, physical infrastructure, and economic foundation. Billions of dollars and myriad programs and policies have been devoted to achieving such a system. Although it is not fully known at this time what actually occurred or what all the weaknesses in the nation's aviation security apparatus are that contributed to the horrendous events on September 11, 2001, it is clear that serious weaknesses exist in our aviation security system and that their impact can be far more devastating than previously imagined. As reported last year, GAO's review of the Federal Aviation Administration's (FAA) oversight of air traffic control (ATC) computer systems showed that FAA had not followed some critical aspects of its own security requirements. Specifically, FAA had not ensured that ATC buildings and facilities were secure, that the systems themselves were protected, and that the contractors who access these systems had undergone background checks. Controls for limiting access to secure areas, including aircraft, have not always worked as intended. GAO's special agents used fictitious law enforcement badges and credentials to gain access to secure areas, bypass security checkpoints at two airports, and walk unescorted to aircraft departure gates. Tests of screeners revealed significant weaknesses as measured in their ability to detect threat objects located on passengers or contained in their carry-on luggage. Screening operations in Belgium, Canada, France, the Netherlands, and the United Kingdom--countries whose systems GAO has examined--differ from this country's in some significant ways. Their screening operations require more extensive qualifications and training for screeners, include higher pay and better benefits, and often include different screening techniques, such as "pat-downs" of some passengers."

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)0.001
metaresearch head score (Gemma)0.005
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0060.007
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 head0.015
GPT teacher head0.162
Teacher spread0.147 · 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

Citations0
Published2001
Admission routes1
Has abstractyes

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