Effects of Biggest Loser exercise depictions on attitudes
Bibliographic record
Abstract
The purpose of this study was to examine the influence of television priming on exercise related attitudes. Participants (N = 121) were randomly assigned to watch clips from American Idol or the Biggest Loser . Participants self-reported leisure time physical activity, exercise attitudes and thoughts about the video before receiving a debriefing statement. A 2 (video condition) by 2 (active or non-active classification) ANCOVA with affective attitudes as the dependent variable was conducted. Vigor from the mood subscale was included as a covariate. Participants in the Biggest Loser group displayed worse explicit affective attitudes towards exercise: F (1, 116) = 3.85, p = .05, ? 2 = .03. Vigor was a significant covariate in this relationship: F (1, 116) = 10.28, p the Biggest Loser could influence thoughts and attitudes towards exercise. Therefore, the show may be antagonistic toward health promotion messages that advocate exercise as enjoyable.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".