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Record W3174504432 · doi:10.1002/icd.2251

An investigation of children's empathic dispositions and behaviours across seven countries

2021· article· en· W3174504432 on OpenAlexaffabout
Violet Kozloff, Jason M. Cowell, Elizabeth Huppert, Natalia Gómez-Sicard, Kang Lee, Randa Mahasneh, Susan Malcolm‐Smith, Bilge Selçuk, Xinyue Zhou, Jean Decety

Bibliographic record

VenueInfant and Child Development · 2021
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Toronto
FundersJohn Templeton Foundation
KeywordsEmpathyPsychologySituational ethicsEmpathic concernProsocial behaviorDispositionDevelopmental psychologyDictator gamePerspective-takingSocial psychology

Abstract

fetched live from OpenAlex

Abstract This study examined individual influences on child empathy, the relationship between child and parent empathy, and the relationship between empathy and prosociality across seven countries. A large sample of children (N = 792, 49% female) from the ages of 6–10 years completed a situational empathy task, as well as a dictator game to assess prosociality. The questionnaire of cognitive and affective empathy was used to assess parents' and children's empathic dispositions. Children participated from Canada, China, Colombia, Jordan, South Africa, Turkey, and the United States. Situational empathy, empathic disposition, and prosociality were all positively associated with age. Boys displayed less situational empathy and lower empathic disposition than girls. Parental empathic disposition predicted the same dispositions in children but were not related to children's situational empathy or prosociality. No association was found between child prosociality and child empathic disposition. Overall, the results suggest similar ontologies of empathic disposition and situational empathy across countries.

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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.011
GPT teacher head0.275
Teacher spread0.264 · 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

Citations9
Published2021
Admission routes2
Has abstractyes

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