Co-designing physical activity programs with immigrant children and families: a Strengthening Community Roots: Anchoring Newcomers in Wellness and Sustainability (SCORE!) Research Study
Bibliographic record
Abstract
Physical activity (PA) is a key health promotion strategy for preventing non-communicable diseases such as obesity. However, certain populations, such as immigrants, may participate less and have lower levels of PA. The objective of this study was to co-design a PA program aimed at increasing PA participation among immigrant children in Canada. This program was developed in partnership with community members (caregivers and children), service providers, and community leaders. Using an experience-based co-design (EBCD) approach, participants identified key issues and challenges related to PA in their community and then co-designed programs and activities that addressed these concerns. Three co-design workshops were held to explore barriers and facilitators to PA and a healthy lifestyle. In small groups, 49 participants led the design of seasonal community programs, including swimming, soccer, gardening, and tennis. Through the workshops, a tailored program was developed in collaboration with the community to address barriers and facilitators to PA for immigrant families. By actively involving relevant community members in the design and development process, the co-design workshops aimed to create a PA program that is more likely to be effective, accepted, and sustainable in promoting PA and a healthy lifestyle for immigrant children and 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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".