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Record W2032411637 · doi:10.5723/csdc.2012.2.2.123

Affective Decision-Making among Preschool Children in Diverse Cultural Contexts

2012· article· en· W2032411637 on OpenAlexaboutno aff
Li Qu, Shan Gao, Cindy Yip, Hong Li, Philip David Zelazo

Bibliographic record

VenueChild Studies in Diverse Contexts · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsChosePsychologyGratificationDevelopmental psychologyMainland ChinaMainlandCultural diversityCross-culturalChinese cultureValue (mathematics)Social psychologyChinaGeographySociologyPolitical science

Abstract

fetched live from OpenAlex

The current study examined 3- and 4-year-olds' affective decision-making in a variety of cultural contexts by comparing European Canadian children to Chinese Canadian, Hong Kong Chinese, and mainland Chinese children (N = 245). All children were tested with a delay of gratification task in which children chose between an immediate reward of lower value and a delayed reward of higher value. Results showed that Chinese Canadian and Hong Kong Chinese children chose more delayed rewards than European Canadian children, with mainland Chinese children showing a trend toward more delayed rewards. Across cultures, 4-year-olds chose more delayed rewards than 3-year-olds; and among 4-year-olds, girls made more such choices than boys. The findings are consistent with previous findings that exposure to Chinese culture is associated with better cool executive function, but they also highlight the importance of examining development across diverse cultural contexts.

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)0.001
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 score0.315
Threshold uncertainty score0.627

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.361
Teacher spread0.332 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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