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Record W2023153826 · doi:10.1080/0042098042000268429

Network Accessibility and the Spatial Distribution of Economic Activity in Eastern Asia

2004· article· en· W2023153826 on OpenAlexaff
Antonio Páez

Bibliographic record

VenueUrban Studies · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsMcMaster University
Fundersnot available
KeywordsEconomic geographyDistribution (mathematics)Process (computing)Regional scienceEconomic integrationSpatial distributionMultivariate statisticsGeographyEconomicsComputer scienceInternational trade

Abstract

fetched live from OpenAlex

The continued integration of international economies is an unfolding process that has accelerated in recent years and that is believed to have the potential to impact on the structure of the spatial economy. The process is of interest from the viewpoint of the transport scholar, because a relevant question is whether, and if so to what extent, the economic changes implied by integration can be guided and influenced by transport infrastructure and services. A number of studies have been conducted, in particular in a European setting, that examine the potential links between accessibility and economic activity. The objective of this paper is to analyse the relationship between intermodal network accessibility and the spatial distribution of economic activities in an east Asian setting. To this end, a multivariate framework based on the use of spatial statistical models is proposed that furthers the methodological possibilities of accessibility analysis. The empirical findings suggest that, once contextual factors are considered, the influence of accessibility as an explanatory factor of the spatial distribution of economic activity in the region becomes very much diminished.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.996

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 studies0.0000.001
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 head0.035
GPT teacher head0.319
Teacher spread0.284 · 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

Citations41
Published2004
Admission routes1
Has abstractyes

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