A Model of Knowledge Translation in Health
Bibliographic record
Abstract
The health of Canadian children and youth has deteriorated in the past few decades and physical inactivity is a powerful contributor. Active Healthy Kids Canada (AHKC; www.activehealthykids.ca) is a national not-for-profit organization with a mission to inspire the nation to engage all children and youth in physical activity by providing expertise and direction to policy makers and the public on how to increase and effectively allocate resources and attention toward physical activity for Canadian children and youth. Annually, for the past 7 years, the AHKC Report Card has consolidated and translated research knowledge to drive social action for policy change relating to physical activity among children and youth. Original published articles and key surveillance data from national and regional surveys are reviewed. A group of content experts from across Canada meet semiannually to review the evidence and assign letter grades. The AHKC Report Card has played a key role in informing discussions that have led to action on physical inactivity in Canada. Further evidence of the Report Card's influence is in the replication of the model in several other jurisdictions, including Saskatchewan and Ontario, Canada; Louisiana, United States; South Africa; Mexico; and Kenya.
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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 | 0.092 | 0.091 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.009 | 0.041 |
| Scholarly communication | 0.020 | 0.022 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.011 | 0.006 |
| Insufficient payload (model declined to judge) | 0.026 | 0.006 |
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".