Facilitating sensitive disclosures by building rapport: the sensitive topic paradigm
Bibliographic record
Abstract
Investigative interviews are critical to both the investigative process and its subsequent outcome. It is not uncommon, however, for interviewees to be reluctant to disclose all that they can remember due to negative feelings (e.g. shame, embarrassment). To overcome such feelings and facilitate detailed disclosures, researchers and practitioners across a variety of professional contexts have advocated for the use of rapport building. There exists little research, however, where rapport building has been experimentally evaluated within an ecologically valid paradigm. Within the current study, participants underwent an interview regarding a topic that we be believed to be inherently uncomfortable to discuss (i.e. details of their self-pleasuring behaviours) and were questioned using either a Rapport or No Rapport approach. Across N = 39 participants, results indicated (1) the outlined paradigm may be an effective method of examining interviewing tactics in an ecologically valid manner and (2) establishing rapport is an effective method of overcoming feelings of discomfort and facilitating disclosures. Practical and theoretical implications, as well as potential next steps are discussed.
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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 | 0.040 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".