Doing ‘More for Adult Sport’: Promotional and Programmatic Efforts to Offset Adults’ Psycho-social Obstacles
Bibliographic record
Abstract
This chapter addresses psycho-social and pedagogical research pertaining to adult sportspersons, or Masters athletes. Young and Callary specifically review three areas that may inform strategies on how to attract more interested adults to sport: promotional messaging, accommodating participatory motives in programming and tailoring curriculum to the needs of adult athletes. Working from the premise that more effective informational strategies are needed to promote adult sport, the authors present emerging research to illustrate how messaging around involvement opportunities may persuade middle-aged adults who participated in sport in youth to re-engage as adults. The authors then discuss a line of inquiry examining whether adult sportspersons see participatory motives accommodated in their programming differently than adult exercisers, and whether incorporating motives into sport programming may be a strategy to grow adult sport. The authors appraise emerging findings and what they mean for the recruitment or retention of adult sport participants. They further identify areas demanding greater scrutiny, including conceptual limitations and the risk of overgeneralizing results beyond privileged and exclusive adult cohorts who may already have an interest in sport. Finally, the authors describe research portraying how learning principles are different in adult sport than in the youth context, specifically underscoring the pertinence of andragogical principles. Based on perspectives from athletes and coaches, this work suggests that to do ‘more for adult sport’, current coaching curriculum and programming may need to be reconsidered to facilitate enriched sport experiences for an older cohort of adults.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".