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Record W2345417018 · doi:10.3791/53773

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime

2016· article· en· W2345417018 on OpenAlexafffund
Joshua Wyman, Ida Foster, Victoria Talwar

Bibliographic record

VenueJournal of Visualized Experiments · 2016
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsMcGill University
FundersMcGill University
KeywordsPsychologyCriminologyComputer science

Abstract

fetched live from OpenAlex

A considerable amount of research has evaluated children's lie-telling behaviors and skills(1-2); however, limitations with the tasks used for eliciting false testimonies and interviewing children have restricted the generalizability of the findings. The primary aim of the current study is to provide an easy-to-administer and ecologically valid method for measuring the veracity and quality of school-aged children's (ages 6-11) testimonies when they are asked to provide different types of true and false reports. Moreover, the methodology enables researchers to examine the social and developmental factors that could influence the credibility of a child's testimony. In the current study, children will witness a theft, and are then asked to either falsely deny the transgression, falsely accuse a researcher of the theft, or tell the truth. Afterwards, children are to be interviewed by a second researcher using a thorough and ecologically valid interview protocol that requires children to provide closed-ended and free-recall responses about the events with the instigator (E1). Coders then evaluate the length and number of theft-related details the children give throughout the interview, as well as their ability to maintain their true and false reports. The representative results indicate that the truth and lie-telling conditions elicit the intended behaviors from the children. The open-ended interview questions encouraged children to provide free-recall information about their experiences with E1. Moreover, findings from the closed-ended questions suggest that children are significantly better at maintaining their lies with age, and when producing a false denial compared to a false accusation. Results from the current study can be used to develop a greater understanding of the characteristics of children's true and false testimonies about crime, which can potentially benefit law enforcement, legal staff and professionals who interview children.

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)0.010
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.057
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.036
GPT teacher head0.483
Teacher spread0.447 · 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 designBench or experimental
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

Citations2
Published2016
Admission routes2
Has abstractyes

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