France’s 2018 Report Card on Physical Activity for Children and Youth: Results and International Comparisons
Bibliographic record
Abstract
BACKGROUND: Insufficient levels of physical activity and increasing sedentary time among children and youth are being observed internationally. The purpose of this paper is to summarize findings from France's 2018 Report Card on physical activity for children and youth, and to make comparisons with its 2016 predecessor and with the Report Cards of other countries engaged in the Global Matrix 3.0. METHODS: The France's 2018 Report Card was developed following the standardized methodology established for the Global Matrix 3.0 by grading 10 common physical activity indicators using best available data. Grades were informed by national surveys, peer-reviewed literature, government and nongovernment reports, and online information. RESULTS: The expert panel awarded the following grades: overall physical activity, D; organized sport participation and physical activity, C-; active play, INC; active transportation, C-; sedentary behaviors, D-; physical fitness, B-; family and peers, INC; school, B; community and the built environment, INC; and government, C. CONCLUSIONS: Very concerning levels of physical activity and sedentary behaviors among French children and youth were observed, highlighting the urgent need for well-designed national actions addressing the presented physical inactivity crisis. The top 3 strategies that should be implemented in priority to improve the lifestyle of French children and youth are provided.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".