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Record W4240642356 · doi:10.21009/141.09

The Implementation of Eating Healthy Program in Early Childhood

2020· article· en· W4240642356 on OpenAlexaboutno aff
Fitria Budi Utami

Bibliographic record

VenueJPUD - Jurnal Pendidikan Usia Dini · 2020
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyDevelopmental psychologyComputer science

Abstract

fetched live from OpenAlex


 
 
 Eating habits develop during the first years of a child's life, children learn what, when, and how much to eat through direct experience with food and by observing the eating habits of others. The aim of this study is to get a clear picture of the Eating program Healthy, starting from the planning, implementation, supervision, and evaluation as a case study of nutrition education; to get information about the advantages, disadvantages and effects of implementing a healthy eating program for children. This research was conducted through a case study with qualitative data analysed using Miles and Huberman techniques. Sample of children in Ananda Islāmic School Kindergarten. The results showed the Healthy Eating program could be implemented well, the diet was quite varied and could be considered a healthy and nutritious food. The visible impact is the emotion of pleasure experienced by children, children become fond of eating vegetables, and make children disciplined and responsible. Inadequate results were found due to the limitations of an adequate kitchen for cooking healthy food, such as cooking activities still carried out by the cook himself at the Foundation's house which is located not far from the school place; use of melamine and plastic cutlery for food; the spoon and fork used already uses aluminium material but still does not match its size; does not involve nutritionists.
 Keywords: Early Childhood, Eating Healthy Program
 References:
 
 
 
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Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.366
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations2
Published2020
Admission routes1
Has abstractyes

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