Global Matrix 4.0 physical activity report cards grades for children and adolescents: A comparison among 15 Asian countries and regions
Bibliographic record
Abstract
Background: : This paper aimed to compare the report card grades among 15 Asian jurisdictions participating in the Global Matrix 4.0, and to explore differences in regional cultural and policy factors related to physical activity behaviors. Methods: All participating jurisdictions followed a harmonized process to develop a country report card. Ten required common indicators were assessed, including five behavioral indicators (Overall Physical Activity, Organized Sport and Physical Activity, Active Play, Active Transportation, Sedentary Behavior), four sources of influence indicators (Family and Peers, School, Community and Environment, and Government), and an outcome indicator (Physical Fitness). Letter grades, ranging from A+ to F or incomplete (INC), were assigned to the indicators based on the predefined benchmarks and grading rubric, and were converted to numerical scale for analyses. Results: The country average scores ranged from F (Indonesia) to B- (Japan), with C+/C/C- the most prevalent grades. The mean behavioral score (D+) was lower than sources of influence score (C+). Poor grades (D or F) were observed for Overall Physical Activity among 73.3% (11/15) of the jurisdictions. Government was the indicator with the highest proportion of A or B grades (66.7%), followed by School (53.3%). Physical Fitness (n = 10) and Active Play (n = 8) were two indicators with the largest number of INC grades. Conclusions: Poor grades for physical activity and sedentary behavior were generally found in Asian jurisdictions. The better, though modest, grades on the sources of influence have not been translated into favorable behaviors among children and adolescents. The findings also suggested surveillance gaps for physical fitness, active play, and organized sport participation. National-level investments and action plans are needed to ensure physical activity interventions are developed, effectively implemented, and regularly evaluated in multiple settings.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".