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Record W3163118246 · doi:10.1002/acp.3840

Children's <scp>under‐informative</scp> responding is associated with concealment of a transgression

2021· article· en· W3163118246 on OpenAlexafffund
Jennifer Gongola, Shanna Williams, Thomas D. Lyon

Bibliographic record

VenueApplied Cognitive Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsMcGill University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyRecallMarine transgressionFalse memoryDevelopmental psychologySocial psychologyCognitive psychology

Abstract

fetched live from OpenAlex

Summary Concealment (i.e., omitting information without saying anything untrue) has received little empirical attention relative to falsification (i.e., false statements). This study examined free recall reports among a sample of 349 maltreated and nonmaltreated children ages four to nine, and found that concealment of a minor transgression was significantly associated with two types of responding: generic under‐informative responding, wherein responses are relevant but imprecise, general, or vague; and specific under‐informative responding, wherein responses selectively omit incriminating details. Under‐informative responding failed to distinguish between children who would ultimately reveal the transgression when asked recognition questions and children who would answer falsely. The results suggest that children's initial recall reports may provide some insight into the likelihood that they are concealing information.

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)0.002
metaresearch head score (Gemma)0.018
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.331
Teacher spread0.305 · 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

Citations6
Published2021
Admission routes2
Has abstractyes

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