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Development of Lying and Cognitive Abilities

2018· book-chapter· en· W2966568862 on OpenAlexaff
Victoria Talwar

Bibliographic record

VenueOxford University Press eBooks · 2018
Typebook-chapter
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsMcGill University
Fundersnot available
KeywordsTemptationPsychologyLyingCognitionCognitive developmentAutism spectrum disorderDevelopmental psychologyCognitive psychologyAutismSocial psychologyNeuroscienceMedicine

Abstract

fetched live from OpenAlex

Abstract The emergence and development of children’s lie-telling is closely associated with their developing cognitive abilities. Telling a lie involves complicated cognitive functions including theory-of-mind understanding and executive functioning abilities. Recent research has found that lie-telling emerges in the preschool years and children’s abilities to maintain their lies improves with age. The current chapter reviews existing literature on the development of children’s lie-telling behavior and its relation to various aspects of children’s cognitive development. It covers the work of Lewis, Stanger, and Sullivan (1989), including the well-known guessing-game experiment, where the child is left alone with temptation and the instruction not to peek. Much of Talwar, Lee, et al.’s research into three-to-seven-year-old children’s lie-telling behavior is covered; and the interaction between these studies and Theory of Mind is emphasized; this is illuminated in the account of research using child subjects with Autism Spectrum Disorder.

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)0.000
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.051
GPT teacher head0.269
Teacher spread0.218 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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