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Record W4221072030 · doi:10.1111/1911-3838.12295

Risks and Controls in a Changing Business Environment: Global Transportation Facility and Concerns About Missing Revenues*

2022· article· en· W4221072030 on OpenAlexaffvenue
Ron Messer

Bibliographic record

VenueAccounting Perspectives · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsKwantlen Polytechnic University
Fundersnot available
KeywordsRevenueAviationBusinessAuditFinanceDebtGovernment (linguistics)Business travelAccountingEngineering

Abstract

fetched live from OpenAlex

Abstract This case examines the effects of privatization in the aviation industry, specifically as it concerns an airport referred to as the Global Transportation Facility (GTF). In a deregulated environment, it is important for airports to ensure that all revenues earned from aircraft landings and passenger use of its terminal buildings are identified, billed, and collected. This will be a concern to users of financial information, including those holding corporate debt and government authorities, as well as the airport's senior management, board of directors and other stakeholders. Your role as the head of internal audit at GTF is to determine whether aviation‐related billings are complete and accurate. You are also concerned about the consequences of errors in reported revenues, including how to identify these and assess their impact.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.039
GPT teacher head0.253
Teacher spread0.214 · 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 designObservational
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

Citations1
Published2022
Admission routes2
Has abstractyes

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