Effects of Reading Health and Appearance Exercise Magazine Articles on Perceptions of Attractiveness and Reasons for Exercise
Bibliographic record
Abstract
OBJECTIVE: To examine the effects of reading exercise-related magazine articles (health, appearance, or control) and the moderating effects of exercise self-identity on reasons for exercise and perceptions of attractiveness, among women in first year university. An additional purpose was to use a thought listing technique, the results of which were examined for evidence of internalization of the exercise-related messages. PARTICIPANTS: Female students in their first year of studies between September 2010 and April 2011 (N = 173; mean age = 19.31 years, mean body mass index = 22.01). METHODS: Participants read a health, appearance, or control article, listed thoughts, and completed questionnaires measuring reasons for exercising, physical self-perception, and exercise self-identity. RESULTS: Participants in the health condition rated exercise for health significantly higher than control condition participants. Participants with high exercise self-identity rated attractiveness as a reason for exercising significantly higher than low exercise self-identity participants in both the health and appearance conditions. Participants with higher internalization scores (i.e., accepted societal norms of appearance) reported exercising for attractiveness reasons more so than participants with lower internalization scores. CONCLUSIONS: The good news is that health messages may be influential and result in wanting to exercise for health purposes. However, exercising for attractiveness was rated highly by participants with high exercise identity who read either the health or appearance articles. Health and appearance are not necessarily distinct concepts for female undergraduate students and the media may influence cited reasons for exercise.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".