Takin' it to the Streets: A Community-University Partnership Approach to Physical Activity Research and Knowledge Translation
Bibliographic record
Abstract
Over the past decade, researchers have faced increasing pressure to bridge the gap between the generation of new knowledge and the translation of that knowledge into applications and products that can benefit society. SCI Action Canada is an example of a community-university partnership approach to bridging the research generation-knowledge translation gap. It is an alliance of 30 community-based organizations and university-based researchers working together to increase physical activity participation among people living with a spinal cord injury (SCI). This paper provides an overview of activities undertaken by SCI Action Canada, presented within the framework of key principles of effective knowledge translation. Recommendations are made for the cultivation of successful community-university partnerships to develop, evaluate, and implement physical activity innovations.
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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 | 0.081 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.017 | 0.015 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".