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Record W1978485935 · doi:10.1177/0165025413479861

The role of honesty and benevolence in children’s judgments of trustworthiness

2013· article· en· W1978485935 on OpenAlex
Fen Xu, Angela D. Evans, Chunxia Li, Qinggong Li, Gail D. Heyman, Kang Lee

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Behavioral Development · 2013
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsUniversity of TorontoBrock University
Fundersnot available
KeywordsHonestyPsychologyDishonestySocial psychologyCharacter (mathematics)TrustworthinessCharacter traitsRelation (database)DeceptionCheatingDevelopmental psychology

Abstract

fetched live from OpenAlex

The present investigation examined the relation between honesty, benevolence, and trust in children. One hundred and eight 7-, 9-, and 11-year-olds were read four story types in which the character’s honesty (honesty or dishonest) was crossed with their intentions (helping or harming). Children rated the story character’s honesty, benevolence, and whether they trusted the character. Results indicated that 7- to 11-year-olds considered both honesty and benevolence when making trust judgments, and older children were more likely than younger children to trust helpful lie-tellers. Further, the relation between dishonesty and trust judgments was mediated by children’s judgments of benevolence. These findings suggest that at least from 7 years onward, children have a nuanced understanding about the relationship between honesty and trust.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.184
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.280
Teacher spread0.272 · 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