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A ride for whom: Has cycling network expansion reduced inequities in accessibility in Montreal, Canada?

2018· article· en· W2788719482 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Transport Geography · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsInstitut National de la Recherche Scientifique
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCyclingJourney to workRecreationGentrificationGeographyQuarter (Canadian coin)Poison controlCensusEquity (law)ImmigrationSuicide preventionInjury preventionDemographic economicsTransport engineeringEconomic growthDemographySociologyPublic transportPopulationEngineeringEnvironmental healthPolitical scienceMedicineEconomics

Abstract

fetched live from OpenAlex

It is widely agreed today that the existence of a network of bicycle paths fosters a feeling of safety as well as the use of the bicycle for both recreational and utilitarian purposes. Recent studies have found a link between the presence of cycling infrastructures and gentrification. Few studies have however examined the growth of the cycling networks from the perspective of environmental equity.
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\nThe main objective of this study is to determine whether the extension of the cycling network in the urban areas of Montreal and Longueuil and the city of Laval over a quarter of a century (1991 to 2016) has reduced or reinforced inequities in accessibility for low-income populations, recent immigrants, children, and older people.
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\nArchival maps were employed to reconstruct the cycling networks in the Montreal area in a GIS for six years (1991, 1996, 2001, 2006, 2011, 2016). Census data and spatial analysis methods were then used to measure whether or not inequities in the accessibility of the cycling network increased over the period in question.
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\nThe results show that, in 25 years, the cycling network has more than doubled in size. It can however be seen that some areas are still very poorly served, and that the network lacks connectivity. Low-income individuals have generally enjoyed good accessibility over the entire period. A strong decrease in inaccessibility for recent immigrants and seniors is also observed. The most important result is clearly that there has been little or no improvement for children, who are found to be in a situation of inequity.

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.

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)0.003
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 score0.355
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.029
GPT teacher head0.296
Teacher spread0.267 · 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