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Rejection of Known and Previously Accepted Foods During Early Childhood: An Extension of the Neophobic Response?

2012· article· en· W2133884373 on OpenAlexvenueno aff
Steven Daniel Brown, Gillian Harris

Bibliographic record

VenueInternational Journal of Child Health and Nutrition · 2012
Typearticle
Languageen
FieldMedicine
TopicChild Nutrition and Feeding Issues
Canadian institutionsnot available
FundersUniversity of Birmingham
KeywordsMedicineExtension (predicate logic)Developmental psychologyPsychology

Abstract

fetched live from OpenAlex

Children begin to reject new foods (food neophobia) at around 18 to 30 months. At this time parents also report the rejection of known and previously accepted foods. The studies presented here are the first to examine this rejection of previously accepted foods in isolation and presents a number of significant findings. Using a parental questionnaire, it was found that the rejection of known and previously accepted food begins towards the end of infancy, commonly occurs during nursery age, reduces in frequency after 30 months and most often involves the rejection of vegetables, mixed foods and fruit. It is hypothesised that some known and previously accepted foods are rejected due to an extension of the neophobic response. When neophobia begins, infants become hyper-vigilant to the visual perceptual features of food in order to recognise the food given. Foods not matching learnt expectations, due to perceptual changes between servings, may be categorised as ‘new’ or ‘different’ and rejected in a neophobic response. A second study offers some support for this hypothesis, showing that those children who are reported as having rejected a known and previously accepted food score higher on neophobia and ‘picky’ eating scales. Implications are discussed.

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)0.001
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 score0.359
Threshold uncertainty score0.255

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.016
GPT teacher head0.313
Teacher spread0.297 · 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".

Quick stats

Citations5
Published2012
Admission routes1
Has abstractyes

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