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Record W2752021738 · doi:10.14430/arctic4663

The Relationship between Airport Infrastructure and Flight Arrivals in Remote Northern Canadian Communities

2017· article· en· W2752021738 on OpenAlexvenueaboutno aff
Michael J. Widener, Shoshanna Saxe, Tracey Galloway

Bibliographic record

VenueARCTIC · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCircumpolar starRunwayGeographyAir traffic controlPopulationAviationReliability (semiconductor)ArcticAir travelEnvironmental resource managementEnvironmental scienceEngineeringEcologyDemography

Abstract

fetched live from OpenAlex

Much of Canada’s northern population resides in communities that are inaccessible by road for a substantial portion of the year. Residents of these “fly-in” communities rely on aircraft to provide a wide range of social, economic, and transportation services. However, for numerous reasons, including the often extreme environmental conditions in the circumpolar regions of Canada, a substantial number of flights to these communities are cancelled or diverted. Using a dataset from two airlines that serve the western portion of this region with information about schedules, delays, and cancellations of more than 18 500 flights, we examined the links between airport infrastructure, flight arrival reliability, and a variety of socioeconomic variables in 23 northern communities. Results show that runway length has a significant impact on the reliability of flight arrival, but also that the reliability of flights may not affect the cost of food in the communities included in our analysis. These findings provide evidence that lengthening runways could improve air service in the Canadian North.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.001
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 head0.057
GPT teacher head0.334
Teacher spread0.277 · 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.

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

Citations12
Published2017
Admission routes2
Has abstractyes

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