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Record W2171093636 · doi:10.1007/s10979-004-0793-0

"Intuitive" Lie Detection of Children's Deception by Law Enforcement Officials and University Students.

2004· article· en· W2171093636 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

VenueLaw and Human Behavior · 2004
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsQueen's University
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsDeceptionPsychologyLie detectionLegal psychologyLaw enforcementLyingSocial psychologyLawPolitical science

Abstract

fetched live from OpenAlex

Adults' ability to detect children's deception was examined. Police officers, customs officers, and university students attempted to differentiate between children who lied or told the truth about a transgression. When children were simply questioned about the event (Experiment 1), the adult groups could not distinguish between lie-tellers and truth-tellers. However, participants were more accurate when the children had participated in moral reasoning tasks (Experiment 2) or promised to tell the truth (Experiment 3) before being interviewed. Additional exposure to the children did not affect accuracy (Experiment 4). Customs officers were more certain about their judgments than other groups, but no more accurate. Overall, adults have a limited ability to identify children's deception, regardless of their experience with lie detection.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.015
GPT teacher head0.302
Teacher spread0.287 · 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