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Record W2341321883 · doi:10.1108/jfp-01-2015-0010

Question type and its effect on children's maintenance and accuracy during courtroom testimony

2016· article· en· W2341321883 on OpenAlexaff
Christine Saykaly, Angela M. Crossman, Mary Morris, Victoria Talwar

Bibliographic record

VenueJournal of Forensic Practice · 2016
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsMcGill University
Fundersnot available
KeywordsDenialInterviewPsychologyOriginalityRecallAssertionValue (mathematics)Order (exchange)CognitionSocial psychologyCognitive psychologyComputer scienceLawMathematicsStatisticsPsychotherapist

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to investigate the influence of question type (open-ended, prompted, reverse order and chronological order recall) on children’s ability to maintain a truth or a lie in a two-part mock-courtroom study. Design/methodology/approach – In total, 96 children ( M age =131.00 months) between 9 and 12 years of age were asked to testify about an interaction with a research assistant the week prior. They were assigned to one of four conditions (true/false×assertion/denial). Findings – Results indicate that question type has an influence on children’s ability to maintain their condition. Results also indicate that regardless of question type, children have difficulty recalling information sequentially. Practical implications – Implications of the current research support the use of various question types, including increasing the cognitive load demands, when interviewing children. Originality/value – To date, this is the first study to investigate the use of reverse order questioning in a courtroom study with 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 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)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.876
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.331
Teacher spread0.318 · 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 teacher head, 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

Citations11
Published2016
Admission routes1
Has abstractyes

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