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Record W2084060050 · doi:10.1348/135532508x398549

The effect of repeated questioning on children's accuracy and consistency in eyewitness testimony

2009· article· en· W2084060050 on OpenAlexaboutno aff
Sarah Krähenbühl, Mark Blades, Christine Eiser

Bibliographic record

VenueLegal and Criminological Psychology · 2009
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsnot available
Fundersnot available
KeywordsRepetition (rhetorical device)Consistency (knowledge bases)PsychologyQuarter (Canadian coin)Repeated measures designInterval (graph theory)Eyewitness testimonySocial psychologyDevelopmental psychologyStatisticsMathematicsHistoryLinguistics

Abstract

fetched live from OpenAlex

Purpose. In police interviews children may be asked the same question many times. We investigated how the number of repetitions and the interval between those repetitions affected the accuracy and consistency of children's responses. Methods. 156 children aged 4–9 years watched a staged event and were interviewed individually 1 week later. Children were asked eight open‐ended questions, which were each repeated a further four times (making a total of forty questions). Half these open‐ended questions could be answered from information in the event, and half were unanswerable (so children should have said ‘don't know’ in response to these questions). The questions were repeated in gist form. The interval between an initial question and its repetitions was varied by use of other questions and twenty non‐repeated filler questions. The intervals between repetitions were immediate repetition, repetition after a delay of three intervening questions, after a delay of six intervening questions, and after ten or more intervening questions. Results. Over a quarter of children's responses to repeated questions changed, usually resulting in a decline in accuracy, particularly after the first repetition. Subsequently, the number of repetitions and delay interval had little effect on responses to answerable questions although accuracy to unanswerable questions continued to decline. Conclusions. Question repetition had a negative affect on children's consistency and accuracy. For unanswerable questions in particular, the more often a question was repeated the more likely children were to invent a response.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score0.569

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.356
Teacher spread0.330 · 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

Citations38
Published2009
Admission routes1
Has abstractyes

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