‘I like you so . . . ’: how transgressor and interviewer likeability and familiarity influence children’s disclosures
Bibliographic record
Abstract
This study examined how children’s age and their ratings of the likeability of a transgressor (E1) and an interviewer (E2) influenced their testimonies after witnessing a theft. Children (N = 152; ages 7–13 years) witnessed E1 steal $20 from a wallet. E1 then asked the children to lie and say that they did not take the money. Children were interviewed about their experience with E1 and completed two questionnaires about E1 and E2. Children who reported higher likeability scores with E1 were more likely to attempt to conceal the theft and more willing to keep it a secret. Children who reported higher likeability scores with E2 were more likely to indirectly disclose the theft. Age also played a role in children’s ability to maintain their concealment. Results have important implications for professionals who interview children and suggest that more research is needed to examine ways to increase children’s comfort with interviews/interviewers.
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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 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".