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Record W4251960992 · doi:10.22215/etd/2014-10268

Printing the Pandemic: An Analysis of H1N1 Vaccine News Coverage

2014· dissertation· en· W4251960992 on OpenAlexaff
Heather McBride

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsCarleton University
Fundersnot available
KeywordsFraming (construction)Dissenting opinionPandemicViewpointsPolitical sciencePublic healthMedia coveragePublic relationsPublic discourseDutyNews mediaMedia studiesCoronavirus disease 2019 (COVID-19)MedicineHistorySociologyLawInfectious disease (medical specialty)DiseaseArt

Abstract

fetched live from OpenAlex

This thesis examines print media coverage of the vaccination debate during the H1N1 pandemic in 2009.It explores how the agenda-setting press in North America framed the benefits and risks of vaccination: the key themes it emphasized, the sources whose voices it privileged and those it overlooked, and the cultural and historical references it invoked.Although news headlines initially depicted an ominous message of doom, over time the framing of the disease shifted as the severity of the illness failed to live up to its worst-case projections.The research shows that the coverage significantly privileged the claims of public health officials, provided very little space for dissenting viewpoints and perspectives, and emphasized themes of risk, uncertainty, moral duty and responsibility.

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)0.003
metaresearch head score (Gemma)0.034
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0120.015
Science and technology studies0.0020.002
Scholarly communication0.0060.004
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.033
GPT teacher head0.362
Teacher spread0.330 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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