The Cognitive Interview Buffers the Effects of Subsequent Repeated Questioning in the Absence of Negative Feedback
Bibliographic record
Abstract
The Cognitive Interview (CI) is known to elicit high-quality information from cooperative witnesses. The present study examined whether the CI protects against two suggestive interview techniques: repeated questioning and negative feedback. Young adults (n = 98) watched one of two crime videos and were interviewed with either a CI or free recall. One week later, a second interviewer asked answerable questions (about information in the video) and unanswerable questions (about information not in the video). Half of the participants received negative feedback about their performance. All participants were then asked the questions a second time. The CI resulted in more correct responses to answerable questions and fewer errors to unanswerable questions at the first questioning. The CI produced the highest consistency for answerable questions in the face of repeated questioning in the absence of negative feedback, and resulted in the most changes in responses to answerable questions when negative feedback was applied. No effects were found for unanswerable questions. The CI protected against repeated questioning, but only in the absence of negative feedback.
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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 | 0.010 | 0.132 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".