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Record W4396900826 · doi:10.1080/10888691.2024.2353151

Does implying peer knowledge during an interview promote truthful disclosures from peer disclosure recipients and witnesses?

2024· article· en· W4396900826 on OpenAlex

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

VenueApplied Developmental Science · 2024
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsThompson Rivers UniversityBrock UniversityUniversity of Regina
Fundersnot available
KeywordsPsychologySelf-disclosurePeer-to-peerSocial psychologyPeer reviewPolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

We tested a novel implied peer knowledge paradigm in which both child witnesses and child recipients (children who previously received a disclosure from a witness) were able to infer, with varying degrees of saliency, the likelihood that an adult interviewer would hear about a negative transgression from a peer and adjust their disclosure strategy accordingly. We tracked children’s disclosures (N = 418; aged 6-12 years; Mage = 8.91 years, SD = 1.37) across two interviews and found that providing a verbal notice of implied knowledge to child disclosure recipients (not child witnesses) that a peer who had previously disclosed to them would also be talking to an adult increased their disclosure rates. This study adds to a small body of work examining patterns of disclosure transmissions from witnesses to peers to adults, which is frequently observed in situations of child sexual abuse.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.029
GPT teacher head0.339
Teacher spread0.310 · 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