A field study of adult witness interviewing practices in a Canadian police organization
Bibliographic record
Abstract
Purpose. The current study examined witness interviewing practices in a Canadian police organization. The effect of interviewer, interviewee, and interview characteristics on those practices was also examined. Method. Ninety witness interviews from a Canadian police organization were coded for the following interviewing practices: types of questions asked (i.e. open‐ended, probing, closed‐ended, clarification, multiple, leading, opinion/statement, and re‐asked), the number of interruptions, percentage of words spoken by interviewer, type of pre‐interview instructions (consequential vs. generic), and whether or not a free narrative was requested (and when requested during the interview). Characteristics pertaining to the interviewer (e.g. primary interviewer's age), interviewee (e.g. witness gender), and interview (e.g. crime type) were also coded. Results. Results showed that closed‐ended and probing questions were the most widely asked questions, and that open‐ended questions were asked relatively infrequently. It was also found that the 80–20 talking rule was violated in 89% of the interviews, interviewers rarely interrupted the witnesses, and free narratives were requested often. Overall, the effect of interviewer, interview, or interviewee characteristics on interviewing practices was minimal. Conclusions. The finding that scientifically prescribed interviewing practices are employed rarely by Canadian police officers highlights a need for increased professional interviewing training. The finding that practices are largely unaffected by personal and situational factors suggests that such training would be equally beneficial for all types of interviewers, interviewees, and contexts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".