2022 French Report Card on Physical Activity and Sedentary Behaviors in Children and Youth: From Continuous Alarming Conclusions to Encouraging Initiatives
Bibliographic record
Abstract
BACKGROUND: Scientific evidence and public health reports keep highlighting the continuous and alarming worldwide progression of physical inactivity and sedentary behaviors in children and adolescents. The present paper summarizes findings from the 2022 French Report Card (RC) on physical activity for children and youth and compares them to the 2016, 2018, and 2020 RCs. METHODS: The 2022 edition of the French RC follows the standardized methodology established by the Active Healthy Kids Global Matrix. Ten physical activity indicators have been evaluated and graded based on the best available evidence coming from national surveys, peer-reviewed literature, government and nongovernment reports, and online information. The evaluation was also performed in children and adolescents with disabilities. Indicators were graded from A (high level of evidence) to F (very low level of evidence) or INC for incomplete. RESULTS: The evaluated indicators received the following grades: overall physical activity: D-; organized sport participation and physical activity: C; active play: F; active transportation: C; sedentary behaviors: D-; family and peers: D; physical fitness: C; school: C-; community and the built environment: F; government: B. CONCLUSIONS: While this 2022 French RC shows progression for 7 out of the 10 indicators considered, it also underlines the continuous need for actions at the local, regional, and national levels to develop better surveillance systems and favor a long-term improvement of youth movement behaviors.
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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 | 0.018 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".