Results From Shanghai’s (China) 2016 Report Card on Physical Activity for Children and Youth
Bibliographic record
Abstract
BACKGROUND: Internationally comparable evidence is important to advocate for young people's physical activity. The aim of this article is to present the inaugural Shanghai (China) Report Card on Physical Activity for Children and Youth. METHODS: Since no national data are available, the working group developed the survey questionnaire and carried out the school surveys for students (n = 71,404), parents (n = 70,346), and school administrators and teachers (n = 1398). The grades of 9 report card indicators were assigned in accordance with the survey results against a defined benchmark: A is 81% to 100%; B is 61% to 80%; C is 41% to 60%, D is 21% to 40%; F is 0% to 20%. RESULTS: The 9 indicators were graded as follows: Overall Physical Activity Levels (F), Organized Sport Participation (F), Active Play (D-), Active Transportation (C-), Sedentary Behavior (F), Family and Peers (B), School (B+), Community and the Built Environment (D+), and Government (D). CONCLUSIONS: Levels of physical activity and sedentary behavior were low and below the respective recommended guidelines. Interventions and policies at the community level should be encouraged to promote physical activity and reduce sedentary behavior. Future national surveys should be encouraged to strengthen Shanghai's Report Card on Physical Activity for Children and Youth.
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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 | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".