Did Your Mom Help You Remember?: An Examination of Attorneys’ Subtle Questioning About Suggestive Influence to Children Testifying About Child Sexual Abuse
Bibliographic record
Abstract
Researchers studying children’s reports of sexual abuse have focused on how questioners overtly assess coaching and truthfulness (e.g., “Did someone tell you what to say?”). Yet attorneys, and defense attorneys, in particular, may be motivated to ask about suggestive influence and truthfulness in subtle ways, such as with implied meaning (e.g., “Did your mom help you remember?”). Such questions may be particularly challenging for children, who may interpret statements literally, misunderstanding the suggested meaning. The purpose of this study was to examine and categorize how attorneys’ ask about suggestive influence and truthfulness. We wanted to learn how attorneys subtly accuse suggestive influence, and how frequently this occurred. We hypothesized that questions indirectly accusing suggestive influence would be common, and that defense attorneys would ask more subtle questions, and fewer overt questions, than prosecutors. We examined 7,103 lines of questioning asked by prosecutors and defense attorneys to 64 children testifying about alleged child sexual abuse. We found that 9% of all attorneys’ lines of questioning asked about suggestive influence or truthfulness. The majority (66%) of these were indirect accusations. Indirect accusations of suggestive influence spanned a range of subtleties and topics, including addressing conversational influences (e.g., coaching), incidental influences (e.g., witnessing abuse), and others. We also found defense attorneys were less likely than prosecutors to ask about suggestive influence and truthfulness overtly. We conclude that attorneys commonly ask about suggestive influence and truthfulness in subtle ways that developing children may struggle to understand, and which may result in affirmations of influence, even when allegations are true.
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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 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".