Addressing Hidden Hunger in School-Aged Children and Adolescents within the Context of the Food System
Bibliographic record
Abstract
Over the past decade, public health advocates and policymakers have grappled with the increasing issue of the double burden of malnutrition. Building on the Sustainable Development Goals and the United Nations Decade of Action on Nutrition, strengthening food systems is paramount to addressing hidden hunger, otherwise known as micronutrient deficiencies, and the provision of healthy, sufficient quality and quantity, affordable, safe, and culturally acceptable food. Using the UNICEF Innocenti Framework on Food Systems for Children and Adolescents as guidance, this review identifies four evidence-based food system strategies to drive improvements in micronutrient deficiencies in low- and middle-income countries in the context of school-aged children and adolescents: agriculture, food supply chains, food environments, and social behavioral change communication. With multiple players and drivers in the picture, strong and reliable oversight from national and local governments is required, through accountability, regulation, and sustained commitment to creating policies and proper infrastructure to support healthy food consumption and limit access to unhealthy food items. Moreover, given the complexity of hidden hunger, a holistic systems approach with a "right to food" lens is required to begin addressing and improving the diets and nutrition of children and adolescents. This involves synergistic and collaborative actions from all actors within the food system, as well as interactions with systems that have the ability to deliver nutrition interventions at scale. These systems include health, water and sanitation, education, and social protection. Only through partnerships and collaboration between all drivers, determinants, and key components of the food system, including its interactions with other global systems, will we be able to appropriately address hidden hunger in school-aged children and adolescents.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".