Socialization of Education on the Importance of Balanced Nutrition for the Young Generation in the Millennial Farmers Group of Kabul Village
Bibliographic record
Abstract
The millennial generation, a growing segment of Indonesia's youth, is expected to play a crucial role in the nation's future development. Thus, it is imperative to adequately prepare this resource, particularly by enhancing the quality of their education and health. Knowledge and understanding of health, especially nutrition, are critical for this group as it directly impacts their cognitive abilities. However, many young people still lack awareness of balanced nutrition, leading to various health. To address this, an educational outreach on the importance of balanced nutrition was conducted for the millennial farmer group in Kabul Village. The goal was to equip the youth with knowledge about balanced nutrition, influencing their eating habits and dietary patterns in the target village. The outreach employed educational methods, including material presentations by the team, interactive discussions, and summarizing the discussion outcomes. Monitoring results during the outreach indicated high participant interest, evidenced by numerous questions, particularly regarding parental roles in ensuring balanced nutrition for adolescent family members. Young participants highlighted the challenge of avoiding unhealthy snacks due to the proliferation of culinary trends and social media influences, often leading them to try foods without considering their nutritional value. The balanced nutrition education initiative aims to benefit both millennials and the older generation. Consequently, it is hoped that parents will emphasize balanced nutrition messages to their children within their families.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".