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Record W3160523774 · doi:10.32866/001c.24072

Changes in Transit Accessibility to Food Banks in Toronto during COVID-19

2021· article· en· W3160523774 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
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Food insecurityPublic transport2019-20 coronavirus outbreakPandemicFood supplyBusinessTransit (satellite)Low incomeSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Food securityGeographyAgricultural economicsSocioeconomicsMedicineEconomicsTransport engineeringEngineeringAgricultureVirology

Abstract

fetched live from OpenAlex

Food banks provide an essential lifeline for those experiencing food insecurity. In Toronto, Canada, 21 new food bank locations opened between February, 2020 and May, 2021 in response to the COVID-19 pandemic. In this article, we measure and map how this has improved public transit accessibility to food banks, with a focus on improvements among low-income residents. We find that the percent of low-income residents that can reach a food bank within a 20 minute one-way transit trip improved from 50% to 60% during this time period.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.045
GPT teacher head0.342
Teacher spread0.297 · 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