Police officers' perceptions and experiences of promoting honesty in child victims and witnesses
Bibliographic record
Abstract
Abstract Purpose This two‐phase study employed a mixed‐methods design to explore UK police officers' perceptions and experiences of promoting honesty in child witnesses with a special focus on the recommended inclusion of Truth‐Lies Discussions (TLDs) at the start of interviews with children. Method In Phase 1, police officers completed an online survey designed to cover their experiences and perceptions regarding truth‐promotion with child witnesses. In Phase 2, police officers were individually interviewed to elicit an in‐depth understanding of current practice relating to this aspect of investigative interviews with children. Results Around half of the survey respondents believed that TLDs promote honesty in children. The majority reported always using TLDs during interviews to ensure compliance with UK best‐practice guidance. There was evidence of a misconception among some police officers that children's performance on TLDs was related to their subsequent truth‐telling behaviour. Following analysis of the interview transcripts, we found a main theme of police officers' uses of TLDs , which included (i) gauging children's conceptual understanding of truths/lies, (ii) ensuring no deviation from guidance and (iii) communicating children's credibility to the court. A second main theme revealed the challenges and obstacles police officers perceived when embarking on TLDs. These were that (i) one type of TLD is not suitable for all children, (ii) the training is insignificant and the application is inappropriate and (iii) participants sometimes use alternative strategies to promote honesty with children. Conclusion Police officers reported following guidance because a failure to do so would jeopordise children's testimony and provided recommendations for future practice‐informed research designs to test techniques for the promotion of honesty in child witnesses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".