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Record W1489532896 · doi:10.22230/cjc.2007v32n3a1853

Fit to Print: A Natural History of Obesity Research in the Canadian News Media

2007· article· en· W1489532896 on OpenAlexaffvenueabout
Stephannie C. Roy, Guy Faulkner, Sara-Jane Finlay

Bibliographic record

VenueCanadian Journal of Communication · 2007
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsUniversity of Toronto
FundersCenters for Disease Control and Prevention
KeywordsNewspaperMediationMeaning (existential)JournalismNatural (archaeology)Mass mediaEvent (particle physics)Health communicationPublic healthInterdependenceNews mediaMedia studiesPolitical sciencePublic relationsAdvertisingPsychologySociologyHistoryMedicineSocial scienceBusiness

Abstract

fetched live from OpenAlex

This natural-history approach to investigating media reports concerning health can reveal the complex process whereby health research becomes news. Using television and newspaper reports of a press event taken from a larger project, this article examines the inception and mediation of obesity research in the Canadian news media. By exploring questionnaire data, a media release, telephone interviews with journalists, and news reports, we can better understand the meaning making that occurs at all levels in the communications process. We conclude that there is an interdependent and possibly problematic relationship between health sources and journalists that shapes the inception and mediation of obesity research and the translation of health research to the public.

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)0.017
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.331
GPT teacher head0.516
Teacher spread0.185 · 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 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

Citations16
Published2007
Admission routes3
Has abstractyes

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