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Record W1535216650 · doi:10.1002/bsl.2144

Exploring Parent–Child Discussions of Crime and their Influence on Children's Memory

2014· article· en· W1535216650 on OpenAlexafffund
Kelly L. Warren, Carole Peterson

Bibliographic record

VenueBehavioral Sciences & the Law · 2014
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsMemorial University of Newfoundland
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsInterviewWitnessRecallPsychologyEyewitness testimonyLeading questionSuggestibilityNarrativeDevelopmental psychologyCognitive interviewCommissionSocial psychologyPsychiatryCognitionCognitive psychologyComputer science

Abstract

fetched live from OpenAlex

When children witness or experience criminal events, the first people they go to are generally parents. Typically, no one else is privy to these conversations, and consequently little is known about their specific content. Research has shown that children can be quite accurate witnesses at times. However, they can also incorporate information from misleading and suggestive questions into their recall, and once their event memory has been changed, children may be unable to provide accurate reports. It is important then to assess parent-child discussions about crime. In the present study, 7- to 10-year-old children watched a video of a theft and talked about it with a parent immediately afterwards, and half had a second immediate interview with a researcher. All were interviewed by a different interviewer 1 week later. Results showed that: parents relied on direct and yes/no questions; children made errors of commission in response to questions; some parents asked leading or misleading questions; children incorporated all correct information from leading questions and nearly 40% of incorrect information from misleading questions; children provided additional information when interviewed by an interviewer 1 week later; and children remained relatively accurate in their descriptions but some were more accurate with parents than with an interviewer 1 week later.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score0.852

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 studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.161
GPT teacher head0.322
Teacher spread0.161 · 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 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

Citations13
Published2014
Admission routes2
Has abstractyes

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