Barrier-Free Transport Choices in Multimodal Cities: Understanding Perceived Accessibility of People with Mobility Disabilities
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.
Bibliographic record
Abstract
This study examines the factors and mechanisms influencing perceived accessibility and transport choices among people with mobility disabilities (PMDs) in Quebec City, Canada. It explores physical, social, and personal factors shaping mobility in a multimodal context, including fixed-route buses, paratransit, cars, and micromobility (small vehicles designed for short, lightweight travel and usually powered by human or low-power electric motors). Participants, all members of an advocacy organization, use various mobility aids. A mixed-method approach combines survey data (35 participants) with narrative interviews (eight participants) and participant observation. Findings reveal that perceiving a transport mode as accessible does not guarantee its use. Social and personal factors, such as other passengers’ behavior, crowding, self-perceptions of autonomy, and social networks, significantly influence choices, alongside physical factors like sidewalk conditions, weather, and infrastructure. Combining usability from the interactionist Disability Creation Model (HDM-DCP) with perceived accessibility theory, we examine the overlooked framework of PMDs’ mobility decision-making in multimodal contexts, providing insights to develop more inclusive transport systems and foster barrier-free, equitable societies.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it