The health and educational impact of removing financial constraints for school sport
Bibliographic record
Abstract
Financial barriers often restrict sport participation among children from low-income families. Schools are thought to offer equitable access to programming, including school sport participation. However, pay-to-play school sport models can inhibit participation among students from low-income households. Recognizing the potential benefits of school sport and realizing the financial barriers to participation, the purpose of this study was to understand the extent to which school sport promotes educational experiences and holistic well-being of Canadian youth from low-income families. A case study was conducted with stakeholders who were supported by funding from a non-profit organization to help cover the costs of school sport registration fees. Data were collected from in-depth interviews with low-income students and their parents, teacher-coaches and school administrators. Three overarching themes were representative of the experiences of school sport participation among low-income students: (1) healthy student-athletes, (2) developing student-athletes in school, for life, and (3) supporting student-athletes as a community. The participants perceived that school sport participation offered holistic health benefits, and developed skills and behaviours that support positive educational experiences and foster life skills. Further, our results highlighted the importance of the school community in supporting low-income students to participate in school sport teams and the need to reframe school sport to better support low-income families.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".