Comparing physical literacy scores by sex and movement behaviour distributions across physical literacy profiles among elementary school students: an exploratory study
Bibliographic record
Abstract
Current literature supports the idea that physical literacy may serve as a key concept for promoting, in children, physically active lifestyles over the long term. However, in France, few studies have focused on physical literacy levels among children, particularly when it comes to comparing scores between boys and girls. Building on a North American approach, the Canadian Assessment of Physical Literacy Second Edition (CAPL-2) framework provides classification of physical literacy profiles based on the overall physical literacy score across four main dimensions: physical, behavioural, affective, and cognitive. The association between these profiles and relevant indicators of movement behaviour distribution remains unclear in the literature. Therefore, the present exploratory study had two main aims: (i) to compare physical literacy scores by sex; and (ii) to compare, across physical literacy profiles, indicators of movement behaviour distribution (intensity gradient, tendency to spend time at higher intensities, and power-law exponent alpha, sedentary accumulation patterns). Ninety-nine final-year primary school students (Avrillé, Maine-et-Loire, France) were assessed using the CAPL-2. CAPL-2 total scores, multivariate combinations of CAPL-2 domain and item scores by sex, and multivariate combinations of movement behaviour distribution metrics across physical literacy profiles were compared using nonparametric analyses. The results encourage conducting confirmatory studies focusing primarily on sex differences in overall physical literacy and the affective dimension. It also supports conducting studies confirming the ability of physical literacy profiles to reflect the intensity gradient, that is, children's tendency to spend their activity time at higher intensities.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".