Results from the 2022 Mexican report card on physical activity for children and adolescents
Bibliographic record
Abstract
Introduction: The Mexican Report Card on Physical Activity for Children and Adolescents aims to assess the prevalence of movement behaviors and opportunities to perform them. Methods: Data on 11 indicators were obtained from national health surveys, census data, government documents, websites, and published studies. Data were compared against established benchmarks, and a grade between 0 and 10 was assigned to each indicator. Results: For Daily Behaviors, we found 34.5% of Mexican children and adolescents meet Physical Activity recommendations (Grade 3), 48.4% participate in Organized Sports (Grade 5), 35-75.8% engage in Active Play outdoors (Grade 4), 54.1% use Active Transportation (Grade 5), 43.6% spend <2 h in Sedentary Behavior per day (Grade 4), and 65-91% meet Sleep recommendations (Grade 7). Girls have lower physical activity levels and sports participation than boys of the same age. For Physical Fitness, we found 56.2-61.8% of children and adolescents have an adequate body mass index for their age (Grade 6). For Sources of Influence, we found 65-67% of parents engage in physical activity or sports in a week (Grade 7), 32.2-53.3% of basic education schools have a physical education teacher (Grade 6), and 37% of neighborhoods in Mexico have sidewalks with trees (Grade 4). Regarding Government, several policies and programs aimed at improving children physical activity were launched but their impact and allocated implementation budget are unknown (Grade 6). Discussion: Mexican children and adolescents engage in low levels of movement behaviors and have limited opportunities to perform such behaviors. The grades and recommendations provided here should be considered to improve such opportunities.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".