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Record W4405315223 · doi:10.1016/j.cstp.2024.101349

Are all streets created equal? Measuring the differences in the built environment among streets with various socioeconomic characteristics in Montréal, Canada

2024· article· en· W4405315223 on OpenAlex
Elitza Kraycheva, Hisham Negm, Madhav G. Badami, Ahmed El-Geneidy

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

VenueCase Studies on Transport Policy · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaFonds de Recherche du Québec-Société et Culture
KeywordsSocioeconomic statusGeographyTransport engineeringBuilt environmentCivil engineeringEngineeringDemographySociologyPopulation

Abstract

fetched live from OpenAlex

• Streets play an important role in shaping urban landscapes and sustaining city life. • The Maps-Mini tool was used to assess microscale built environment features in Montréal, QC, Canada. • Results show significant disparities in the quality of the built environment across various socioeconomic neighborhoods. • Lower-income areas generally exhibit poorer built environment quality. • Results were inconsistent between assessments conducted via Google Street View imagery and in-person site visits. Streets play an important role in shaping urban landscapes and sustaining city life. Through streetscape design, cities can foster vibrant and inclusive neighborhoods that cater to the diverse needs of their residents. Our research aims to determine whether variations at the microscale level of the built environment exist among streets of similar typologies across diverse socioeconomic neighborhoods in Montréal, QC, Canada. The short version of the Microscale Audit of Pedestrian Streetscapes (MAPS-Mini) tool was used to assess microscale features essential for creating high-quality built environments. Assessments were conducted using Google Street View and in-person site visits to ensure a comprehensive analysis of the tool’s effectiveness across different methodologies and urban contexts. Results show significant disparities in the quality of the built environment across various socioeconomic neighborhoods. Despite having identical typologies and characteristics, streets in lower-income areas generally exhibit poorer built environment quality, highlighting that streets are not always created equal in Montréal. This trend is particularly evident in medium and high-density neighborhoods. Less than a third of the audited streets were deemed to have high-quality built environments. This paper can be of value to practitioners working towards addressing disparities in the built environment to create equitable, healthy, and livable communities.

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)0.001
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 score0.134
Threshold uncertainty score0.692

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 head0.044
GPT teacher head0.281
Teacher spread0.238 · 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