Results from Nepal’s 2018 Report Card on Physical Activity for Children and Youth
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: Nepal's Report Card on Physical Activity for Children and Youth summarises the available evidence on ten physical activity-related indicators among Nepalese children and youth. METHODS: Published scientific papers on physical activity of Nepalese children and youth (5-17 years) were searched systematically in four databases (Medline, Embase, PsycINFO, and PubMed Central) while some survey reports were manually searched. Letter grades were assigned to ten indicators (Overall Physical Activity, Organized Sport Participation, Active Play, Active Transportation, Sedentary Behaviours, Physical Fitness, Family and Peers, School, Community and Environment, and Government) by the country's report card team based on available data. RESULTS: Among the ten indicators, five indicators were successfully graded based on available data. Overall Physical Activity was graded as D+. Active Transportation and Family and Peers were assigned as A- and A, respectively. Community and Environment was graded as C-. The other five indicators could not be graded due to insufficient data. CONCLUSIONS: Though a majority of Nepalese children and youth use active modes of transport and have adequate support for physical activity from family and peers, overall participation in physical activity appears to be low. Lack of data identified with five incomplete indicators reflects the need for further research. Studies with larger sample, more rigorous study design and objective assessment of physical activity is recommended for future physical activity surveillance in Nepal.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.000 |
| 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".