Colaboración trilateral entre Canadá, Estados Unidos y México en torno a la Iniciativa contra la Obesidad Infantil
Bibliographic record
Abstract
ABSTRACT Childhood obesity is an important public health problem that affects countries in the Americas. In 2014, Pan American Health Organization (PAHO) Member States agreed on a Plan of Action for the Prevention of Obesity in Children and Adolescents in an effort to address the impact of this disorder in the Americas region. The interventions laid out in this regional plan are multi-faceted and require multi-sectoral partnerships. Building on a strong history of successful trilateral collaboration, Canada, Mexico, and the United States formed a partnership to address the growing epidemic of childhood obesity in the North American region. This collaborative effort, known as the Trilateral Cooperation on Childhood Obesity Initiative, is the first initiative in the region to address chronic noncommunicable diseases by bringing together technical and policy experts, with strong leadership and support from the secretaries and ministers of health. The Initiative’s goals include increasing levels of physical activity and reducing sedentary behavior through 1) increased social mobilization and citizen engagement, 2) community- based outreach, and 3) changes to the built (man-made) environment. This article describes the background and development process of the Initiative; specific goals, activities, and actions achieved to date; and opportunities and next steps. This information may be useful for those forming other partnerships designed to address childhood obesity or other complex public health challenges in the region.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".