MétaCan
Menu
Back to cohort

Japanese and American Children's Reasoning about Accepting Credit for Prosocial Behavior

2010· article· en· W1896233220 on OpenAlexaff
Gail D. Heyman, Shoji Itakura, Kang Lee

Bibliographic record

VenueSocial Development · 2010
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsProsocial behaviorPsychologyDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

Children's reasoning about the appropriateness of accepting credit for one's own prosocial behavior was examined. Participants aged 7 to 11 years old in Japan and the United States (total N = 206) were presented with a series of stories in which a protagonist performs a good deed and is asked about it by another character. Across stories, the protagonist either truthfully acknowledges the deed or falsely denies it, in a statement that is made either in public or in private, and is addressed to either a teacher or to a peer. As predicted, Japanese children judged protagonists less favorably when they acknowledged the good deed in public rather than in private. Further, Japanese children tended to view modest lies more favorably overall than did children in the U.S. These results point to the importance of modesty in Japan and to the ways in which Japanese children take into account the social context of communication when deciding whether it is appropriate for individuals to convey information about themselves.

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)0.012
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 score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.038
GPT teacher head0.368
Teacher spread0.330 · 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

Citations35
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueSocial DevelopmentSame topicCultural Differences and ValuesFrench-language works237,207