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Record W2520165439 · doi:10.1371/journal.pone.0163018

Japanese and Canadian Children’s Beliefs about Child and Adult Knowledge: A Case for Developmental Equifinality?

2016· article· en· W2520165439 on OpenAlexaffabout
Stanka A. Fitneva, Elizabeth Pile Ho, Misako Hatayama

Bibliographic record

VenuePLoS ONE · 2016
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsQueen's University
Fundersnot available
KeywordsEquifinalityDevelopmental psychologyPsychologyCognitive developmentChild developmentCognitionBiologyEcology

Abstract

fetched live from OpenAlex

Children do not know everything that adults know, nor do adults know everything that children know. The present research examined the universality of beliefs about child and adult knowledge and their development with 4- and 7-year-old Canadian and Japanese children (N = 96). In both countries, all children were able to identify adult-specific knowledge and only older children displayed beliefs about child-specific knowledge. However, Japanese and Canadian children differed in whether they used their own knowledge in deciding whether a person who knew an item was a child or an adult. In addition, parental and child beliefs were related in Japan but not in Canada. These findings indicate that children growing up in different cultures may take different paths in developing beliefs about age-related knowledge. Implications for theories of socio-cognitive development and learning 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 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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.112
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.256
Teacher spread0.226 · 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 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

Citations15
Published2016
Admission routes2
Has abstractyes

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