An examination of gender, age, and income level on most used physical activity contexts
Bibliographic record
Abstract
Physical activity (PA) contexts have been associated with PA participation and adherence. Studies have shown that in general middle aged and older adults preferred to exercise alone whereas university aged adults preferred exercising with others outside of a structured class setting. This study sought to determine whether an exerciser's personal characteristics would influence the PA contexts engaged in the most. The present study examined the following personal characteristics: gender, age, and income. Participants (N = 313) completed an online survey indicating which PA contexts they used the most: (a) with others in a structured setting; (b) with others in an unstructured setting; (c) alone with others around; and (d) completely alone. The results suggested that all three personal characteristics may influence an individual's use of PA context. For example, for outdoor activities, females engaged in PA with others in an unstructured setting substantially more (38.5%) than with others in a structured setting (4.7%). In addition, the findings showed a wide distribution of responses indicating use of the four PA contexts by individuals of all genders, age groups, and income levels. Although preliminary, these findings could serve to direct PA initiatives for adults.Acknowledgments: Partners of Southwestern Ontario in motion
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".