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Case Study: Relationship of Walk Access Distance to Transit with Service, Travel, and Personal Characteristics

2007· article· en· W2120132979 on OpenAlexaffabout
Baha Alshalalfah, Amer Shalaby

Bibliographic record

VenueJournal of Urban Planning and Development · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransit (satellite)DowntownTransport engineeringTRIPS architectureService (business)BusinessPublic transportGeographyAdvertisingMarketingEngineering

Abstract

fetched live from OpenAlex

This paper explores the relationship between walk access distance to transit and various characteristics of the transit service and transit users in the city of Toronto, Canada. The data used in this study included individual records of transit trips made in the morning peak period (6–9 a.m.) on a regular week day. The results show that the dense transit route network in the downtown area results in lower walk access distances than in other parts of the city. Also, dwelling type of the household, number of vehicles available in the household, and transit service frequency show a noteworthy relationship with access distance in Toronto. In general, it was found that around 60% of transit users in Toronto live within the transit service area of 300m airline distance assumed by the transit service provider. These results indicate that people in Toronto are willing to walk further to access transit than assumed existing standards for transit service areas.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.452
Threshold uncertainty score0.900

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.059
GPT teacher head0.328
Teacher spread0.269 · 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

Citations150
Published2007
Admission routes2
Has abstractyes

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