MétaCan
Menu
Back to cohort
Record W3131936754 · doi:10.32866/001c.19046

Public Transit Riders’ Perceptions and Experience of Safety: COVID-19 Lessons from Edmonton

2021· article· en· W3131936754 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFindings · 2021
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPublic transportCoronavirus disease 2019 (COVID-19)Transit (satellite)PandemicBusinessPublic healthPublic relationsPerceptionMarketingTransport engineeringAdvertisingPsychologyMedicinePolitical scienceEngineeringNursing

Abstract

fetched live from OpenAlex

This study aims to understand who and under what circumstances is more likely to travel and feel safe using public transit in Edmonton, Canada, amidst the COVID-19 pandemic, by analyzing data from an online survey conducted during the summer of 2020. We provide empirical evidence that an individual better informed about the measures Edmonton Transit Service is taking to ensure physical distancing and meet the health and safety concerns of riders is more likely to feel safe using public transit. It is recommended that transit agencies continuously communicate with riders regarding ongoing efforts to promote the health and safety of all users.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.263
Teacher spread0.221 · 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