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Record W3132667882 · doi:10.1007/s10912-021-09677-3

COVID-19, Contagion, and Vaccine Optimism

2021· article· en· W3132667882 on OpenAlexafffund
Kelly McGuire

Bibliographic record

VenueJournal of Medical Humanities · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsTrent University
FundersSocial Sciences and Humanities Research Council of CanadaTrent University
KeywordsVaccinationNarrativeRealmPandemicOptimismPolitical sciencePublic relationsCoronavirus disease 2019 (COVID-19)SociologySocial psychologyPsychologyMedicineVirologyDiseaseLawInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Steven Soderbergh's Contagion (2011) positions the vaccine as the end point of the arc of ​pandemic, marking both the containment of an elusive virus and ​the resumption of a life not fundamentally different from ​before the disease outbreak. ​The film reinforces the ​assumption that a pandemic will awaken ​all of us to the urgency of vaccination​, persuading us to put aside our reservations and anxieties ​and the idea that compliance is the inevitable outcome of quarantine. This article explores how pro-vaccination cultural products ​such as Contagion might in fact undermine public health efforts by promoting a false narrative, which simplifies the kind of vaccination campaign necessary for herd immunity to develop. An ethic of sacrifice and selflessness drives the public health messaging of the film but leaves intact certain individualistic tropes and plague narrative scapegoating tendencies, while the framing of the vaccine as "gift" takes it out of the realm of medical science altogether.

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)0.004
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.016
Scholarly communication0.0080.005
Open science0.0000.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.039
GPT teacher head0.349
Teacher spread0.310 · 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 designNot applicable
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

Citations12
Published2021
Admission routes2
Has abstractyes

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