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Record W3100405770 · doi:10.1177/0956797620966526

Susceptibility to Being Lured Away by a Stranger: A Real-World Field Test of Selective Trust in Early Childhood

2020· article· en· W3100405770 on OpenAlexafffund
Qinggong Li, Wenyu Zhang, Gail D. Heyman, Brian J. Compton, Kang Lee

Bibliographic record

VenuePsychological Science · 2020
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyCredibilityTest (biology)Context (archaeology)Developmental psychologySocial psychologyNaturalismField (mathematics)Point (geometry)

Abstract

fetched live from OpenAlex

In this preregistered field study, we examined preschool children’s selective trust in a real-life situation. We investigated whether 3- to 6-year-old children (total N = 240) could be lured to a new location within their school grounds by an unfamiliar adult confederate. In a between-subjects manipulation, the confederate established either a high or a low level of personal credibility by providing information that the child knew to be either true or false. In Experiment 1, in which the confederate was female, children showed sensitivity to informational accuracy by being less willing to leave with an uninformed confederate, and this effect increased with age. In Experiment 2, in which the confederate was male, children were reluctant to leave regardless of informational accuracy. These findings point to real-world implications of epistemic-trust research and provide the first evidence regarding the early development of selective trust in a high-stakes naturalistic context.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.073
Threshold uncertainty score0.813

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.330
Teacher spread0.309 · 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 teacher head, 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

Citations17
Published2020
Admission routes2
Has abstractyes

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