Using the RE-AIM framework to evaluate the impact of a sport for development program serving marginalized youth
Bibliographic record
Abstract
Sport for development (SFD) interventions can act as a catalyst for positive youth development. This case study used the RE-AIM framework to evaluate the individual and community level impact of Ahead of the Game (AOTG), a 12-week school-based program that empowers marginalized youth through sport and mentorship in the Peel District School Board (PDSB) (Ontario, Canada). Each of the five RE-AIM dimensions were assessed using surveys and school administrative records. Overall, 1,551 Peel district students (85% male; age 14-19) have participated in AOTG (Reach). Participants attended an average of 87% of sessions. Main reasons for participation included: the supportive environment (30%), the opportunity to build positive relationships (25%), mentorship (23%), and learning life skills (22%). Participants reported increased conflict resolution (89%) and anger management skills (90%) (Efficacy). 19/42 schools within PDSB have run AOTG, 8 of which are the highest priority schools in the Board. Two AOTG facilitators have collaborated with at least one school staff at each site. (Adoption). The majority (79%) of sites have implemented the AOTG program curriculum in its entirety, with 16% also administering AOTG's evaluation component (Implementation). School records show a decrease in participants' negative incidents with teachers and school administration at one-month follow-up. 14/19 schools have repeated the program the following school year (Maintenance). AOTG is an effective mentorship-based SFD program that demonstrates the potential for building positive relationships, increasing life skills, and decreasing juvenile delinquency. Application of the RE-AIM framework to this program provides a blueprint for its translation to other SFD 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 | 0.023 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".