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Record W2994086284 · doi:10.1111/desc.12930

Young children are more likely to cheat after overhearing that a classmate is smart

2019· article· en· W2994086284 on OpenAlexaff
Li Zhao, Lulu Chen, Wenjin Sun, Brian J. Compton, Kang Lee, Gail D. Heyman

Bibliographic record

VenueDevelopmental Science · 2019
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsPsychologyPraiseConversationSocializationSocial psychologyDevelopmental psychologyCheatingDishonestyCommunication

Abstract

fetched live from OpenAlex

Research on moral socialization has largely focused on the role of direct communication and has almost completely ignored a potentially rich source of social influence: evaluative comments that children overhear. We examined for the first time whether overheard comments can shape children's moral behavior. Three- and 5-year-old children (N = 200) participated in a guessing game in which they were instructed not to cheat by peeking. We randomly assigned children to a condition in which they overheard an experimenter tell another adult that a classmate who was no longer present is smart, or to a control condition in which the overheard conversation consisted of non-social information. We found that 5-year-olds, but not 3-year-olds, cheated significantly more often if they overheard the classmate praised for being smart. These findings show that the effects of ability praise can spread far beyond the intended recipient to influence the behavior of children who are mere observers, and they suggest that overheard evaluative comments can be an important force in shaping moral development.

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)0.003
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.050
GPT teacher head0.262
Teacher spread0.211 · 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

Citations27
Published2019
Admission routes1
Has abstractyes

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