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Record W2677457372

Measuring Success: The search for assessment criteria in determining the impact of deregulation in regional aviation

2011· article· en· W2677457372 on OpenAlexaboutno aff
Tarryn Kille, Paul Raymond Bates, Patrick Stuart Murray

Bibliographic record

VenueGriffith Research Online (Griffith University, Queensland, Australia) · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsDeregulationAviationCompetition (biology)Government (linguistics)BusinessService (business)Economic growthEconomicsEngineeringMarket economyMarketing
DOInot available

Abstract

fetched live from OpenAlex

Regional aviation is considered critical to the development of regional and remote communities. It has been recognised by the Australian, Brazilian and Canadian governments that regional aviation is also crucial to the continued economic development of these countries. Whilst all three countries have similar economic structures, they have also completed a cycle of regional aviation deregulation over the last twenty years. A comparative analysis of the economic regulatory reforms conducted in Australia, Brazil and Canada has been provided. The paper uses this analysis to suggest the development of four criteria (improved service quality, increased competition, increased efficiency and increased innovation), to determine the impact of government economic policy on regional aviation.

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)0.031
metaresearch head score (Gemma)0.120
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.031
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.120
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0150.016
Science and technology studies0.0010.005
Scholarly communication0.0070.013
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.580
GPT teacher head0.430
Teacher spread0.150 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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