Getting in the game: An investigation of voluteering in sport among older adults
Bibliographic record
Abstract
Volunteering is a positive leisure activity for older adults, yet this group has one of the lowest rates of volunteering across many nations, particularly in sport. The purpose of this qualitative study was to explore factors associated with volunteering in sport among older adults. Using Peters‐Davis, Burant, and Braunschweig's (2001) multidimensional framework, semi‐structured interviews with older adult sport volunteers (n=20,65 years and older) uncovered themes within structural, cultural, cognitive, and situational dimensions of volunteering behaviour. The findings revealed that the older adult volunteers had large social networks, past involvement in sport, and a history of volunteering. They reported becoming involved in sport volunteering as an opportunity to use their skills, for social connections, and to stay active. They also identified quality of health, awareness of volunteer opportunities, and spousal employment status as factors that influenced their volunteering. Preliminary implications for recruiting older adults to volunteering in sport, and directions for future research, are drawn from the findings.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".