Mobility Justice for Persons With Disability: Body–Environment Interactions and Velomobility
Bibliographic record
Abstract
This article addresses a major source of inequality and exclusion in contemporary transport, namely the mobility injustices faced by persons with diverse forms of disability. Our focus is on one aspect, the potential for velomobility – using a range of adaptive cycles – to increase mobility and, therefore, access to education, work, recreation, social encounters, and to enjoy freedom. We pursue this topic by, first, advancing the notion of epistemic justice as the form of justice most appropriate for addressing this issue. Second, we outline some recent technical developments of adaptive cycles, suggesting that considerable progress has been made in managing a range of impairments such that technical blockages do not currently appear to be the main obstacles to the wider adoption of velomobility. We then examine socio-economic, political, environmental, and cultural constraints, suggesting these socially constructed blockages present the biggest obstacles to advancing velomobility for persons with disability who might otherwise gain the diverse therapeutic benefits.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".