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Record W4403208676 · doi:10.3138/cjhh.678-112023

COVID-19 in Perspective: A Witness Seminar

2024· article· en· W4403208676 on OpenAlexaffabout
Catherine Carstairs, Amy L. Greer, Rachael Magilsen

Bibliographic record

VenueCanadian Journal of Health History · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsWitnessPandemicPerspective (graphical)Oral historyCoronavirus disease 2019 (COVID-19)HistoryPublic relationsPolitical scienceMedicineLawSociologyArtPathologyVisual artsArchaeologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

In June 2023, we brought together leaders who responded to the emergency phase COVID-19 pandemic in Ontario as part of a "Witness Seminar." This approach to studying history was developed by the Institute of Contemporary British History. It has been extensively used in the history of science and medicine by the Wellcome Trust History of Twentieth Century Medicine. A witness seminar provides a collective oral history, in which participants can express diverse perspectives, build on each other's thoughts, and create a documentary record for policy makers and future historians. The published transcript provides an intimate look at how the pandemic played out in the eyes of some of key responders and raises many questions about the history of public health funding and administration in the province of Ontario, the failures in long-term care, and the need to improve pandemic communication. This article documents the success of the pandemic response.

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)0.005
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.240
Threshold uncertainty score0.478

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0290.009
Scholarly communication0.0060.005
Open science0.0020.009
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0430.003

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 head0.095
GPT teacher head0.448
Teacher spread0.353 · 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 designQualitative
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

Citations1
Published2024
Admission routes2
Has abstractyes

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