Physical literacy levels of Canadian children aged 8–12 years: descriptive and normative results from the RBC Learn to Play–CAPL project
Bibliographic record
Abstract
The current physical literacy level of Canadian children is unknown. The Royal Bank of Canada (RBC) Learn to Play – Canadian Assessment of Physical Literacy (CAPL) project, which is anchored in the Canadian consensus statement definition of physical literacy, aimed to help establish the current physical literacy level of Canadian children. The CAPL was used to assess the physical literacy (and component domains: Daily Behaviour, Physical Competence, Knowledge and Understanding, and Motivation and Confidence) of Canadian children aged 8–12 years. Data were collected from 11 sites across Canada, yielding a sample of 10,034 participants (5030 girls). Descriptive statistics by age and gender were calculated and percentile distributions of physical literacy scores, including each domain and individual measure, were derived. The mean age of participants was 10.1 ± 1.2 years. Total physical literacy scores (out of 100) were on average 63.1 ± 13.0 for boys and 62.2 ± 11.3 for girls. For boys and girls respectively, domain scores were 19.9 ± 4.7 and 19.3 ± 4.1 (out of 32) for Physical Competence; 18.6 ± 7.9 and 18.5 ± 7.4 (out of 32) for Daily Behaviour; 12.7 ± 2.8 and 12.2 ± 2.6 (out of 18) for Motivation and Confidence; and 11.8 ± 2.8 and 12.2 ± 2.6 (out of 18) for Knowledge and Understanding. Physical Competence measures were on average 28.1 ± 8.4 cm (sit-and-reach flexibility), 33.5 ± 9.4 kg (grip strength, right + left), 23.4 ± 14.1 laps (Progressive Aerobic Cardiovascular Endurance Run [PACER] shuttle run), 61.8 ± 43.8 s (isometric plank), 19.0 ± 3.8 kg/m2 (body mass index), 67.3 ± 10.8 cm (waist circumference), and 20.6 ± 3.9 out of 28 points for the Canadian Agility and Movement Skill Assessment (CAMSA), with scores for boys higher than girls and older children higher than younger children for grip strength, PACER, plank, and CAMSA score. Girls and younger children had better scores on the sit-and-reach flexibility than boys and older children. Daily pedometer step counts were higher in boys than girls (12,355 ± 4252 vs. 10,779 ± 3624), and decreased with age. These results provide the largest and most comprehensive assessment of physical literacy of Canadian children to date, providing a “state of the nation” baseline, and can be used to monitor changes and inform intervention strategies going forward.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".