MétaCan
Menu
Back to cohort
Record W4235639545 · doi:10.31234/osf.io/yw4bq

Children show reduced trust in confident advisors who are partially informed

2019· preprint· en· W4235639545 on OpenAlexaff
Michelle Huh, Igor Grossmann, Ori Friedman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsOverconfidence effectPsychologySocial psychologyLow Confidence

Abstract

fetched live from OpenAlex

Young children trust confident informants over cautious ones, and this tendency can lead them to heed the claims of informants whose confidence is unjustified. The ability to recognize overconfidence, and not be swayed by it, is therefore important for children to obtain accurate information and to make better decisions. In two experiments (total N = 232), we show that 4- to 6-year-olds use information about whether speakers are fully or only partially informed to judge whether confident claims should be heeded. In each experiment, children were shown scenarios in which a confident speaker and a cautious one gave conflicting claims. When both speakers were completely informed, children expressed more trust in the confident speaker’s claim. However, when both speakers only had partial information, children did not believe the confident speaker over the more cautious one. These effects did not vary with age. The present findings are the first to suggest that children as young as 4 understand when confidence is unwarranted, and they may indicate that reminders that a speaker is only partially informed could help children recognize when confidence is unjustified.

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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.022
GPT teacher head0.298
Teacher spread0.276 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same topicChild and Animal Learning DevelopmentFrench-language works237,207