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Record W2926857144 · doi:10.1080/10888691.2019.1586544

Transmission of children’s disclosures of a transgression from peers to adults

2019· article· en· W2926857144 on OpenAlexafffund
Heather L. Price, Angela D. Evans, Kaila C. Bruer

Bibliographic record

VenueApplied Developmental Science · 2019
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversity of ReginaBrock UniversityThompson Rivers University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsWitnessPsychologyContext (archaeology)Transmission (telecommunications)Peer groupEvent (particle physics)Marine transgressionDevelopmental psychologySocial psychologySelf-disclosureLaw

Abstract

fetched live from OpenAlex

Peers are common recipients of disclosures about negative events, but the transmission of peer disclosures to adults is not well understood. We explored children’s (N = 352; aged 6–11 years) disclosures of a negative event to peer and adult interviewers. Some children witnessed an adult transgression and were asked to keep the transgression a secret (witnesses). Some of these witnesses (peer-interviewed witnesses) were then interviewed by peer who had not witnessed the event (peer interviewers) and then by an adult. The remainder of the witnesses (control) were only interviewed by an adult. Peer interviewers who received a disclosure were likely to share the disclosure with an adult and were significantly more likely to do so than children in either witness condition. Although the probability of disclosure transmission likely depends on context, this study provides the first evidence of peer recipients’ willingness to disclose to adults at a high rate.

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)0.003
metaresearch head score (Gemma)0.016
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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.007
GPT teacher head0.252
Teacher spread0.244 · 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

Citations5
Published2019
Admission routes2
Has abstractyes

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