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Record W3111921709 · doi:10.1080/14739879.2020.1851147

Reimagining medical education for primary care in the time of COVID-19: a world view

2020· article· en· W3111921709 on OpenAlex
Robin Ramsay, Nagwa Hegazy, Chandramani Thuraisingham, Marie Andrades, Victor Ng, Carmen Cabezas, Joy Mugambi, Val Wass

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

VenueEducation for Primary Care · 2020
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsCollege of Family Physicians of Canada
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Primary careDiversity (politics)Public relations2019-20 coronavirus outbreakPrimary health careSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)SociologyMedical educationHealth carePolitical sciencePedagogyNursingMedicineFamily medicineVirology

Abstract

fetched live from OpenAlex

This article sets out to highlight the challenges and opportunities for medical education in primary care realised during the COVID-19 pandemic and now being enacted globally. The themes were originally presented during a webinar involving educationalists from around the world and are subsequently discussed by members of the WONCA working party for education. The article recognises the importance of utilising diversity, addressing inequity and responding to the priority health needs of the community through socially accountable practice. The well-being of educators and learners is identified as priority in response to the ongoing global pandemic. Finally, we imagine a new era for medical education drawing on global connection and shared resources to create a strong community of practice.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.593
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
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 head0.021
GPT teacher head0.359
Teacher spread0.338 · 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