Mission accomplished? Physical activity, affect, and self-esteem
Bibliographic record
Abstract
The homeless experience a variety of physical, psychological and social vulnerabilities; physical activity and sport may be one vehicle to help alleviate some of these challenges. Self-esteem can predict intention and moderate the level of control the individual perceives they have over a specific health behaviour such as physical activity. There is evidence that even a single bout of physical activity can positively change affective states. Patrons from a homeless shelter (N = 34) participated in one of four physical activity experiences. Four physical activity experiences were selected based on results from our previous research: bowling, yoga, war canoe and Atlatl, and ball hockey. Self-report exercise behaviour and intentions were assessed prior to activity participation. Self-esteem and physical activity affect were measured before and after each activity. There were no significant changes in self-esteem or affect following physical activity participation. No between group differences were evident for self-esteem or affect. Self-esteem was not a significant predictor of self-reported exercise behaviour. Exercise behaviour was a significant predictor of physical activity affect; F(1, 27) = 5.74, p = .02; with an R2 = .18. Participants who participated more regularly in physical activity had higher ratings of physical activity affect. Acknowledgments: University of Winnipeg Major Research Grant
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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 | 0.003 |
| 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) | 0.003 | 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".