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Disability and pedestrian road traffic injury: A scoping review

2022· review· en· W4293680744 on OpenAlexaff
Naomi Schwartz, Ron Buliung, Arslan Daniel, Linda Rothman

Bibliographic record

VenueHealth & Place · 2022
Typereview
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsInstitute for Clinical Evaluative SciencesUniversity of TorontoToronto Metropolitan University
Fundersnot available
KeywordsPedestrianInjury preventionHuman factors and ergonomicsPoison controlSuicide preventionRoad trafficOccupational safety and healthPhysical medicine and rehabilitationPsychologyMedicineEnvironmental healthTransport engineeringEngineering

Abstract

fetched live from OpenAlex

Disability and ableism remain a nascent area of inquiry in road traffic injury research. A scoping review of academic literature was conducted to understand the state of knowledge on disability and pedestrian-motor vehicle collisions. Sixty-two eligible articles were identified and included. A significantly higher risk of pedestrian collisions, injuries, and fatalities was consistently found among disabled people. Risk factors included individualized factors such as walking speed and crossing decisions of disabled people. The roles of social/political environments in injury risk were less commonly explored. More research is needed to assess how inaccessible or disabling environments may produce elevated risk of pedestrian injury among disabled populations.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0100.012
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.060
GPT teacher head0.368
Teacher spread0.308 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations36
Published2022
Admission routes1
Has abstractyes

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