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Record W4409387533 · doi:10.1016/j.cstp.2025.101452

Discrepancies between initial applicants and actual users of a new microtransit service: The case of FlexRide Milwaukee

2025· article· en· W4409387533 on OpenAlex
Robert J. Schneider, Lingqian Hu, Yency Martinez

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCase Studies on Transport Policy · 2025
Typearticle
Languageen
FieldEngineering
TopicTransportation and Mobility Innovations
Canadian institutionsUniversity of Toronto
FundersNational Science Foundation
KeywordsService (business)Transport engineeringBusinessOperations researchComputer scienceEngineeringMarketing

Abstract

fetched live from OpenAlex

• On-demand, microtransit service helped low-income workers reach suburban jobs. • High use by people who were Black, without cars, under age 35. • Actual use by low-income workers and women was lower than initial applications. • Actual use by unemployed, cash users, and third-shift workers was lower than initial applications. Amid the long-term trend of declining transit ridership in the US, there is growing interest in leveraging on-demand microtransit to complement existing transit service, particularly to improve the accessibility of autoless riders to jobs, health care, or other activities in lower-density areas that are inefficient to serve with fixed-route transit. However, relatively little is known about whether these new microtransit services effectively serve their intended user groups. We studied FlexRide Milwaukee, an on-demand, microtransit service created to connect low-income workers and job seekers from predominantly Black neighborhoods on the northwest side of the City of Milwaukee, Wisconsin with predominately white, employment-rich suburbs. This employment-focused service helped FlexRide users reach jobs located in suburbs with limited transit service. Analyzing trip data from the FlexRide pilot study period (April 18 to September 30, 2022), we profiled 713 applicants who showed initial interest in trying the service. Ultimately, 428 of these applicants signed up as participants to use the service and 128 of them actually used FlexRide Milwaukee (80 frequent and 48 occasional riders). Descriptive analyses and logistic regression models showed that participants used FlexRide more often if they were already employed, Black, or did not have access to a household vehicle. However, compared with their high levels of initial interest, people with low incomes and women underused FlexRide Milwaukee. People who were unemployed, used cash, or worked third shift also underused the service. More research is needed to understand the latent demand for this type of microtransit service among these groups.

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 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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.035
GPT teacher head0.338
Teacher spread0.303 · 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