The landscape of contemporary paratransit research: A critical systematic review of the literature in the US and Canada
Bibliographic record
Abstract
• Using a systematic review, three approaches to paratransit research are identified. • The first approach includes studies that model paratransit systems using large datasets. • The second focuses on how paratransit could be delivered differently. • The third explores existing systems. • The perspectives of paratransit users are over-shadowed by a focus on cost-cutting. In the United States (US) and Canada, paratransit refers to transportation services that supplement scheduled, fixed route, mass transit to eligible passengers, namely people with disabilities and a growing number of older adults. This paper presents a critical systematic review of the literature on paratransit in the US and Canada since 2010 (n = 57), investigating what is known about paratransit, as well as the methodological and conceptual approaches privileged in this literature. Three separate approaches to the study of paratransit were identified. The first approach is paratransit modeling (n = 22). Under this approach, papers focus on demand modeling and route optimization (n = 12), cost optimization (n = 6), or quality of service and system information management (n = 4). Papers under the second approach, alternatives (n = 15), all propose different ways to provide paratransit services, including public–private partnerships (n = 6), autonomous vehicle technologies (n = 5), and the diversion of current paratransit user toward other modes (n = 4). Thirdly, many papers examine current services (n = 20), relating to system performance (n = 9), operational considerations (n = 7), or user perspectives (n = 4). When combined with a strong bias toward quantitative studies (77%) the perspectives of paratransit users are under-represented in the literature, over-shadowed by a focus on cost-cutting and improving operational efficiency. These trends are discussed in relation to neoliberalism and Critical Ableist Studies. Future research should directly involve paratransit users, engage in theory, and embrace qualitative methods.
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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 | 0.064 | 0.242 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.047 | 0.051 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".