Results from Hong Kong’s 2019 report card on physical activity for children and youth with special educational needs
Bibliographic record
Abstract
BACKGROUND: /Objective: The Active Healthy Kids 2019 Hong Kong Report Card on Physical Activity for Children and Youth with Special Educational Needs (SEN) provides evidence-based assessments for nine indicators of physical activity behaviors and related sources of influence for 6- to 17-year-olds with SEN in Hong Kong. This is the first Report Card for this population group in Hong Kong. METHODS: The best available data between 2008 and 2019 were reviewed by a panel of experts. Following the Active Healthy Kids Global Alliance (AHKGA) development process, letter grades were assigned to nine indicators (Overall Physical Activity, Organized Sport Participation, Active Play, Active Transportation, Sedentary Behaviors, Family & Peers, School, Community & Environment, and Government Strategies & Investments). RESULTS: ) were assigned a letter grade. The remaining indicators including Organized Sport Participation, Active Play, Active Transportation, Family & Peers, and Community & Environment were not graded due to insufficient data. CONCLUSIONS: A majority of children and youth with SEN in Hong Kong are physically inactive and have a high level of sedentary behaviors. Schools are ideal settings to promote physical activity for this population. There is a need to develop a comprehensive surveillance system to monitor this population, assess efforts to improve the grades, and promote physical activity opportunities for children and youth with SEN.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".