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Record W2071643193 · doi:10.2304/eerj.2005.4.2.5

Children's Visual Representations of Food and Meal Time: Towards an Understanding of Nutrition and Educational Practices

2005· article· en· W2071643193 on OpenAlexaff
Lorraine Savoie‐Zajc

Bibliographic record

VenueEuropean Educational Research Journal · 2005
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsPerspective (graphical)PsychologyPsychological interventionOverweightDevelopmental psychologyPedagogySociologySocial psychologyObesityMedicine

Abstract

fetched live from OpenAlex

Within the broad perspective of school and social exclusion, this article pays attention to an important factor of exclusion: overweight and obesity in primary school children. An interdisciplinary research was conducted and aimed at the study of social representations and practices surrounding food which primary school children, their parents and their teachers hold. This article proposes, firstly, an analysis of drawings produced by the children. Most of them represented dinner time as a social event when the family gathers together. It is pictured as a pleasant and joyful moment of the day, in settings of people standing close to one another or sitting around a table. While concrete references to the act of eating are present, it is the spirit of family reunion that predominates. Secondly, the article will clarify the perspectives teachers have regarding their role in educating for healthy food habits. Holding a prevention perspective, the conclusion will stress the importance of partnerships between parents and schools that should be enacted. Joint interventions should be planned for.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.294
GPT teacher head0.582
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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".

Quick stats

Citations5
Published2005
Admission routes1
Has abstractyes

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