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Record W4390228003 · doi:10.1016/j.tranpol.2023.12.012

Transit-oriented development and bikeability: Classifying public transport station areas in Montreal, Canada

2023· article· en· W4390228003 on OpenAlexafffundabout
Arianne Robillard, Geneviève Boisjoly, Dea van Lierop

Bibliographic record

VenueTransport Policy · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTransit-oriented developmentPublic transportTypologyWalkabilityTransport engineeringLand useTRIPS architectureSustainable transportCyclingSustainable developmentUrban planningLand-use planningRelevance (law)Urban sprawlEnvironmental planningBusinessSustainabilityBuilt environmentGeographyEngineeringCivil engineeringPolitical scienceForestry

Abstract

fetched live from OpenAlex

Transit-oriented development (TOD), characterized by a high and mix development around public transport stations, is gaining traction as a sustainable way to support the use of public transport for regional trips and active transport for local trips. To support integrated land use and transport planning, several TOD typologies have been developed, with a focus on land use and transport characteristics, and more recently walkability. While TOD aims to motivate the use of active modes, including cycling, assessments of bikeability have been left out of TOD typologies. To fill this gap, this study seeks to develop a bicycle-oriented TOD typology that combines indicators related to the cycling environment with traditional land use and transport indicators. Using Montreal, Canada as a case study , 14 indicators are generated to develop a TOD typology oriented on bikeability and the 114 public station areas are grouped into seven distinct clusters. The results demonstrate that the addition of bikeability criteria to the TOD typology helps discriminate the different types of stations based on their current bikeability and bikeability potential. The proposed framework enables identifying and prioritizing targeted interventions to station development. This study is of relevance to planners and researchers aiming to integrate cycling in the development of TOD.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.038
GPT teacher head0.294
Teacher spread0.257 · 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

Citations13
Published2023
Admission routes3
Has abstractyes

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