Results from Mexico’s 2014 Report Card on Physical Activity for Children and Youth
Bibliographic record
Abstract
BACKGROUND: The Mexican Report Card on Physical Activity in children and youth was first developed in 2012 as a tool aimed at informing policy and practice. The objective of this paper is to update the Report Card to reflect the current situation in Mexico. METHODS: A literature search was conducted in Spanish and English using major databases, and complemented with government documents and national health surveys. Information on the 9 indicators outlined in the Global Matrix of Report Card Grades was extracted. Experts from Mexico and Canada met to discuss and assign a grade on each indicator. RESULTS: The physical activity indicator was assigned a C+, which was higher than in the previous report card. Sedentary behavior was assigned a D, which was lower than the previous report card. Organized Sports and Active Transportation, which were not graded in the previous report card, were assigned grades of D and B-, respectively. Government and Built Environment were assigned grades of C and F, respectively. Family and Peers and Active Play were not graded (INC). CONCLUSIONS: Levels of PA and sedentary behaviors among Mexican children and youth were below the respective recommended references. The implementation and effectiveness of current government strategies need to be determined. The Mexican Report Card is a promising knowledge translation tool that can serve to inform policies and programs related to physical activity.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.014 | 0.015 |
| 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) | 0.009 | 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".