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Record W4414498626 · doi:10.1016/j.cities.2025.106511

Satisfaction in pedestrianized areas: What shapes positive and negative experiences?

2025· article· en· W4414498626 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

VenueCities · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsInstitut National de la Recherche ScientifiquePolytechnique Montréal
FundersCampbell Family Mental Health Research InstituteNatural Sciences and Engineering Research Council of CanadaMitacsInstitut national de la recherche scientifique
KeywordsCohabitationPerceptionCluster (spacecraft)Position (finance)Variable (mathematics)VariablesPublic opinion

Abstract

fetched live from OpenAlex

One of the approaches to improve the livability, safety, and accessibility of cities and to make neighborhoods livable places for all their residents is implementing car-free projects. Although pedestrianization provides many benefits, public resistance is sometimes directed against these projects. Based on a database of 95 variables collected through an online survey with over 1300 respondents in Montreal, Canada, this study aims to explore differences in how people experience pedestrianization and to investigate the factors shaping these perceptions. Cluster analysis is used to identify groups with varying levels of satisfaction with pedestrianization. The key differences between these groups center on attitudes toward the cohabitation of pedestrians and two-wheeler users and the opinion on the impact of pedestrianization on individuals' mobility and travel patterns. The less satisfied group with pedestrianization includes a lower percentage of females, a higher percentage of people with limitations using public and active transportation, and a higher proportion of older people. Since cyclist-pedestrian cohabitation is the variable with the highest difference between clusters, this variable is analyzed using an interpretable ensemble learning approach to better understand people's position on pedestrianization. The results suggest that having experience in cycling, a higher frequency of cycling, an agreement that pedestrians should share the car-free streets with cyclists, and a better perception of safety on car-free streets increase the satisfaction related to the cyclists-pedestrians cohabitation. • The levels of satisfaction with pedestrianization experiences are examined. • Cohabitation of pedestrians/2-wheelers impacts the level of satisfaction. • The profiles of the less satisfied group with pedestrianization are identified. • Having experience in cycling increased the cohabitation of pedestrians/2-wheelers.

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)0.000
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 score0.146
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.299
Teacher spread0.283 · 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