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Record W4412999564 · doi:10.1016/j.tranpol.2025.103762

Advancing the design and implementation of accessible taxi services: A study of driver and disabled rider experiences

2025· article· en· W4412999564 on OpenAlexafffundabout
Élyse Comeau, Siobhán Kelly, Timothy Ross

Bibliographic record

VenueTransport Policy · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalToronto Rehabilitation InstituteUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsTransport engineeringBusinessMarketingEngineeringDisabled peoplePsychologyApplied psychology

Abstract

fetched live from OpenAlex

Accessible taxi services play an important role in supporting disabled people's mobility and their access to employment, education, healthcare, and social activities. This paper examines the accessible taxi service experiences of drivers and disabled riders in Toronto, Canada. Findings are based on a thematic analysis of 590 customer-reported complaints and 494 driver-reported incident reports provided by an accessible taxi brokerage contracted by the city's paratransit service. The findings reveal issues concerning safe service delivery, communication and disability awareness, and conflict management. To address these issues, we propose a three-part training program for drivers and riders, focused on disability awareness, physical safety, and conflict resolution. We then discuss policy implications and the roles of accessible taxi brokerages, paratransit agencies, and local governments in ensuring safe and effective accessible taxi services. We recommend incorporating a critical disabilities studies perspective into future policies and protocols to help with identifying and addressing ableist elements of accessible taxi and paratransit services. • Accessible taxi drivers and disabled riders both face various issues during trips. • Issues with disability awareness, physical safety, and conflicts must be addressed. • Taxi protocols for conflict management and inclement weather trips must be clearer. • Accessible taxi drivers require better disability training. • A three-module disability training framework is proposed for consideration.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.369
Teacher spread0.352 · 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 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

Citations2
Published2025
Admission routes3
Has abstractyes

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