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Record W2099838112 · doi:10.1123/jpah.4.2.180

Get the News on Physical Activity Research: A Content Analysis of Physical Activity Research in the Canadian Print Media

2007· article· en· W2099838112 on OpenAlexaffabout
Guy Faulkner, Sara-Jane Finlay, Stephannie C. Roy

Bibliographic record

VenueJournal of Physical Activity and Health · 2007
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNewspaperCredibilityContent analysisPhysical activityAdvertisingPsychologyDisseminationPublic relationsNews mediaPolitical scienceMedicineSociologyBusinessSocial sciencePhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: News media may play a critical role in disseminating research about physical activity and health. This study examined how much physical activity research gets reported in the media and its prominence and credibility. METHODS: A content analysis was conducted of the reporting of physical activity research in Canadian national and local newspapers from November 2004 to April 2005. RESULTS: Physical activity research was given some prominence and treated as news through the use of several devices to infer credibility. However, newspapers appeared to invest little in the production of physical activity research as news and information about research methodology was infrequent. CONCLUSIONS: While stories reporting physical activity research were given some prominence and credibility, the lack of significant investment and the limited reporting on research methodology suggests that important aspects of research related to physical activity may not be well represented in newspaper coverage.

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)0.009
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.991
Threshold uncertainty score0.684

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.064
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0280.031
Science and technology studies0.0040.003
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.560
GPT teacher head0.539
Teacher spread0.021 · 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.

Study designObservational
DomainEvaluation
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

Citations10
Published2007
Admission routes2
Has abstractyes

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