MétaCan
Menu
Back to cohort
Record W3184358290 · doi:10.5539/jsd.v14n4p108

Subsidized Regional Airlines as a Sustainable Development Mechanism for Remote Locations Heavily Dependent on Air Transportation

2021· article· en· W3184358290 on OpenAlexvenueno aff
Celso José Leão e Silva, Maurício Oliveira de Andrade, Viviane Adriano Falcão, Carlos Fabrício Assunção da Silva

Bibliographic record

VenueJournal of Sustainable Development · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsSubsidyOperationalizationAir transportBusinessSustainabilityEnvironmental planningMechanism (biology)PopulationRegional scienceNatural resource economicsEconomic geographyGeographyTransport engineeringEconomicsEcology

Abstract

fetched live from OpenAlex

The understanding that air transport induces the economic development of a region has motivated studies on regional air transport and the necessary subsidies for its implementation. Several countries have implemented specific subsidy plans with a focus on integrating their territories through a network of air routes, depending on the funding methods and the results of the investments that were made. However, few studies summarize the geographical conditions of the locations served that justify their dependence on air transport as the only viable means of accessibility. This article seeks to identify the geographical characteristics of these locations to illustrate the conditions that justify the need for subsidies for the operationalization of air transport as a mechanism to promote the minimum sustainability conditions for such locations. We collected socioeconomic data of a set of 1365 subsidized routes of 28 countries from the Americas, Asia, Europe, and Oceania and tracing a profile of localities, classified in nine different clusters. The results indicated that isolated locations in islands, in the polar regions and areas of impenetrable forests have an almost exclusive dependence on air transport as a means of access and that justify the maintenance of subsidies to air routes as a fundamental requirement for the accessibility of the population to services of a social and humanitarian nature.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.796
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.030
GPT teacher head0.245
Teacher spread0.215 · 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 designTheoretical or conceptual
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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Sustainable DevelopmentSame topicAviation Industry Analysis and TrendsFrench-language works237,207