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Record W3165690667 · doi:10.32866/001c.24082

The Accessibility Implications of a Pilot COVID-19 Vaccination Program in Hamilton, Ontario

2021· article· en· W3165690667 on OpenAlexaffabout
Antonio Páez, Christopher D. Higgins

Bibliographic record

VenueFindings · 2021
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsThe Scarborough HospitalUniversity of TorontoMcMaster University
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Government (linguistics)Pilot programVaccinationGeographyDistribution (mathematics)PharmacyPopulation2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)SocioeconomicsBusinessEnvironmental healthMedicineVirologySociologyFamily medicineOutbreakMedical education

Abstract

fetched live from OpenAlex

The Government of Ontario in Canada announced the pilot for a new vaccination program, with designated pharmacies across the province now able to offer COVID-19 vaccines. The accessibility of this program raises questions about travel times to vaccination sites and the distribution of these times among the population. In our examination of the City of Hamilton we find that selected sites do not serve rural and urban residents well; particularly, the associated cost of travel (in terms of travel time) is expected to be disproportionally borne by lower income urban populations and rural residents. Modest additions to the list of pilot sites in the city can substantially alleviate this inequity.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.324
GPT teacher head0.481
Teacher spread0.158 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations9
Published2021
Admission routes2
Has abstractyes

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