How multiple interviews and interview framing influence the development and maintenance of rapport
Bibliographic record
Abstract
Information obtained from investigative interviews is crucial for police to develop leads, advance investigations and make effective decisions. One well-endorsed approach for eliciting detailed and accurate information is building rapport between the interviewer and interviewee. While familiarity and communicative tone are predicted determinants of rapport, the effects of repeated exposure to an interviewer, as well as interview framing, on rapport has rarely been tested. In two simulated suspect interview experiments, we tested whether established rapport is maintained during a second interview with the same interviewer (Experiment 1) and how accusatory and humanitarian interview framings impact the development of rapport (Experiment 2). We also tested, across both experiments, whether nonverbal mimicry can be a proxy for measuring rapport. We found evidence suggesting that rapport, once established, is carried over to subsequent meetings, and that it is possible to build rapport even when it was poorly established in the initial interview. We also found that an accusatory interview framing was associated with lower rapport than a humanitarian interview framing, and that interview framing affected nonverbal mimicry between interviewer and interviewee. Contrary to our expectations, mimicry did not correlate with an existing measure of rapport.
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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 | 0.001 | 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) | 0.000 | 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".