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Record W2076015037 · doi:10.1080/10810730305733

The Influence of Famous Athletes on Health Beliefs and Practices: Mark McGwire, Child Abuse Prevention, and Androstenedione

2003· article· en· W2076015037 on OpenAlexaff
William J. Brown, Michael D. Basil, Mihai C. Bocârnea

Bibliographic record

VenueJournal of Health Communication · 2003
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsAndrostenedionePublic healthAthletesHEROPsychologyIdentification (biology)Suicide preventionPoison controlMedicineDevelopmental psychologyEnvironmental healthNursing

Abstract

fetched live from OpenAlex

When Mark McGwire broke Roger Maris's home run record in September of 1998, he was instantly declared an American hero and held up as a positive role model for teenagers and young adults. The extensive media attention focused on McGwire made the general public aware of his use of a muscle-building dietary supplement, Androstenedione. It also increased the public's awareness of McGwire's public service to prevent child abuse. The present research assesses audience involvement with McGwire through parasocial interaction and identification, and the effects of that involvement on audience knowledge of and attitudes toward Androstenedione and child abuse prevention. Results indicate parasocial interaction with an athlete regarded as a public role model likely leads to audience identification with that person, which in turn promotes certain attitudes and beliefs. In this case, parasocial interaction and identification with Mark McGwire was strongly associated with knowledge of Androstenedione, intended use of the supplement, and concern for child abuse. Implications of this research for featuring celebrities in health communication campaigns are discussed.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.049
GPT teacher head0.336
Teacher spread0.286 · 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 designObservational
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

Citations171
Published2003
Admission routes1
Has abstractyes

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