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Record W3154673046 · doi:10.19255/jmpm02510

The fear of flying and the competitiveness of a return to service of the Boeing 737 MAX

2021· article· en· W3154673046 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Modern Project Management · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsTicketPurchasingAeronauticsPreferenceService (business)Air travelAirplaneAdvertisingEvent (particle physics)BusinessMarketingOperations researchEconomicsComputer scienceEngineeringAviationComputer securityMicroeconomics

Abstract

fetched live from OpenAlex

Fear of flying has no direct relationship with actual airline or aircraft safety. For those afraid of flying, the choice of an airline ticket and the related airplane is expected to be an important issue. This article uses a methodology to simulate the experience of purchasing unlabeled airline tickets to investigate whether individuals who are afraid of flying unconsciously change their choice depending on the ticket parameters. The Boeing 737 MAX, which became notorious for being grounded due to two recent accidents, was randomly assigned to airline tickets. This aircraft was compared with eight competing alternatives. The results demonstrate that in the event of a return to service, the passenger preference for this aircraft would be low comparable to that for competing modern airplanes that are less known to the North American public. Nonetheless, Boeing products continue to instill a sense of safety and trust in those afraid of flying.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.156

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 head0.032
GPT teacher head0.241
Teacher spread0.209 · 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