Looking beyond the “intended beneficiary”: parent experiences and perspectives of child participation in sport-for-development programs at an inner-city Toronto sport facility
Bibliographic record
Abstract
Rationale/purpose: Although there have been studies on the impact of families and sport for development (SFD) in regard to youth participants, less is known about parent experiences of SFD. The purpose of this study is to explore parent experiences of SFD and how SFD affects family life outside of the program setting.Research methods: In this study, an interpretive qualitative approach was adopted to explore parent experiences of SFD. Semi-structured interviews and focus groups were utilized for the purposes of generating grounded knowledge in a practical research setting.Findings: Data analysis revealed three themes of SFD and parents: (1) social benefits directly related to parent’s day-to-day lives; (2) the (usually) safe and family-oriented space of SFD; and (3) parent expectations of SFD as well as opportunities for family bonding outside the SFD space.Practical implications: The implications of this study call attention to the ways sport managers, SFD scholars and practitioners may seek to further involve parents and families in SFD initiatives.Research contributions: This research builds and extends on SFD research that examines parent perspectives by highlighting the ways SFD affects parents in ways that may not be immediately noticeable when examining programs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".