Sports day in Canada: a longitudinal evaluation
Bibliographic record
Abstract
Sports Day in Canada (SDIC) is an annual event celebrating the role of sport within communities and promoting sport participation across Canada. SDIC ends a week of thousands of local sporting events and activities with a day-long national television broadcast. The objectives of this study were to evaluate whether awareness of SDIC has increased over time among Canadians (2010–2013), identify correlates of awareness, and assess changes in individuals' intentions to engage in sport. Online surveys were administered (2010: N = 863; 2011: N = 674; 2012: N = 861; 2013: N = 1447) to assess demographics, levels of physical activity and sport participation, awareness of SDIC, and intentions to participate in sport and physical activity as a result of SDIC. Analyses were conducted using independent t-tests, one-way ANOVAs, and a series of binary logistic regressions. Awareness of SDIC increased significantly from 26.9% in 2010 to 41.2% in 2013. Current sport participation (OR 1.21; 95% CI [1.11, 1.32]; OR 1.32; 95% CI [1.19, 1.47]; OR 1.26; 95% CI [1.16, 1.37]; OR 1.30; 95% CI [1.22, 1.38]) was the only significant correlate of awareness in years 2010–2013, respectively. Among people aware of SDIC, intentions to participate in sport as a result of SDIC have significantly increased over time, F(3, 1662) = 8.88, p < .001. Special events such as SDIC appear to have a role to play as part of a broader strategy to encourage sport participation among Canadians. A challenge for such events remains in reaching inactive people.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".