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Record W4405001094 · doi:10.1515/9780776636429-003

Overview of COVID-19: Old and New Vulnerabilities

2020· book-chapter· en· W4405001094 on OpenAlexaboutno aff
Colleen M. Flood, Vanessa MacDonnell, Jane Philpott, Sophie Thériault, Sridhar Venkatapuram

Bibliographic record

VenueUniversity of Ottawa Press eBooks · 2020
Typebook-chapter
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakVirologyComputer scienceBiologyMedicineOutbreakInfectious disease (medical specialty)Pathology

Abstract

fetched live from OpenAlex

The book, comprising 43 short chapters, is divided into 6 subthemes: federalism and governance, accountability, civil liberties, equity, labour, and global health.Our approach is one primarily grounded in law, because of the critical nature of law in defining responsibilities, accountability, rights, distribution of wealth, and, indeed, health.We have included other important disciplines, including ethics, public policy, public health, and medicine.We begin this overview chapter by providing context for the pandemic with facts and figures (including what we do not know), before turning to discuss in more detail how we employ a lens of vulnerability throughout our analysis.Subsequently, for each of our subthemes, we highlight insights emerging from the chapters.We conclude by claiming that the COVID-19 pandemic forces us to reflect deeply on how we are governed and on our policy priorities in order to ensure pandemic preparedness, response, and recovery policies include all of us, not just some or the most privileged of us. Context for a Modern-Day PlagueThe Emergence of COVID-19 At the time of writing, the novel coronavirus SARS-CoV-2 1 has infected people in 213 countries and territories and on every continent except Antarctica. 2 As of June 27, 2020, over 495,781 people worldwide 3 have died, including the 8,504 people who have died in Canada. 4The true death toll is certainly higher and will continue to rise.The respiratory illness caused by SARS-CoV-2 was initially identified by regional health authorities in China after dozens of people with similar symptoms were treated in Wuhan, Hubei Province, in December 2019.This made headlines when the World Health

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 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.655
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.344
GPT teacher head0.359
Teacher spread0.014 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations2
Published2020
Admission routes1
Has abstractyes

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