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Record W4390541765 · doi:10.1080/21650020.2023.2296891

Influence of the built environment on community mobility of people living with visual disabilities: a scoping review

2024· review· en· W4390541765 on OpenAlexafffund
Kishore Seetharaman, Atiya Mahmood, Farinaz Rikhtehgaran, Ghazaleh Akbarnejad, Farrukh Chishtie, Mike Prescott, Alison F. Chung, W. Ben Mortenson

Bibliographic record

VenueUrban Planning and Transport Research · 2024
Typereview
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of British ColumbiaUniversity of VictoriaSimon Fraser University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPedestrianBuilt environmentAffect (linguistics)PerceptionWalkabilityNeighbourhood (mathematics)Orientation and MobilityPsychologyApplied psychologyHuman–computer interactionComputer scienceTransport engineeringEngineeringVisually impairedCommunicationCivil engineering

Abstract

fetched live from OpenAlex

Understanding how the outdoor environment shapes the community mobility of people with visual disabilities is key to designing an accessible public realm and facilitating their rights to use outdoor spaces. A scoping review was conducted to explore 1) What aspects of the built environment affect the community mobility of persons with visual disabilities? and 2) How does the built environment affect the community mobility of persons with visual disabilities? Forty-three peer-reviewed publications from 2000 to 2022 were included after conducting database searches, screening of articles, and data charting. Studies focused on micro-environmental features related to sidewalks and crosswalks (e.g. landmarks, curbs, curb ramps, tactile warning/guiding surfaces, and accessible pedestrian signals), and broad environmental factors (e.g. neighbourhood amenities and street layout) and their influence on orientation, wayfinding, and safety. The paper discusses the role of the built environment in 1) posing barriers to outdoor mobility (e.g. potholes, poorly designed curb cuts, obstacles at waist-height or eye-level, poor lighting, inadequate pedestrian signal, complicated street layout), and 2) offering cues (e.g. visual, tactile, auditory, olfactory, kinaesthetic) for spatial perception and navigation. Focusing on how the built environment shapes community mobility is necessary to enhance accessibility through urban planning and design and assistive technology.

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)0.007
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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.385
Threshold uncertainty score0.851

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.130
GPT teacher head0.454
Teacher spread0.324 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations19
Published2024
Admission routes2
Has abstractyes

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