Impact of the ParticipACTION Report Card on physical activity for children and youth in Canada: 2015–2024
Bibliographic record
Abstract
Background: Canada has produced 16 national Report Cards on the Physical Activity of Children and Youth over the past 20 years. This manuscript details the impact of the most recent Report Cards released between 2015 and 2024, updating evidence since the publication of the impact paper focused on the first 10 years (2005-2014). Methods: Various quantitative and qualitative approaches were employed to catalogue the developmental history and background of the Report Card, its leadership and sources of funding; consolidate and discuss the various evaluations and assessments that have been performed on the Report Card from 2015 to 2024; describe the distribution and reach of the Report Card from 2015 to 2024; and, examine the multi-dimensional impact of the Report Card on propelling the movement to get children and youth moving over the past 10 years in Canada and internationally. Results: Leadership by ParticipACTION has led to replicating the Children and Youth Report Card in over 70 jurisdictions, with many examples of beneficial cross-fertilization of ideas across jurisdictions and sectors. The multisectoral impact of the Report Card in Canada continues to be substantial, though sustained funding remains a challenge. There is modest evidence that grades for some indicators are drifting upwards. Deliberate efforts have been made to better integrate evidence and gaps related to the physical activity of equity-denied groups. Conclusions: Over the past 10 years, the ParticipACTION Children and Youth Report Card has continued to have a measurable, positive impact on the pediatric physical activity field in Canada (and beyond).
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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 | 0.017 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".