An Archival Analysis of Actual Cases of Historic Child Sexual Abuse: A Comparison of Jury and Bench Trials.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Logistic regression analyses were used to predict verdicts from 466 Canadian jury and 644 Canadian judge-alone criminal trials involving delayed or historic allegations of child sexual abuse. Variables in regard to the complainant and offence were selected from the legal, clinical, and experimental literatures, including mock juror research. Of six variables that had been related to decisions reached in mock juror research concerning delayed allegations of child sexual abuse (i.e., repressed memory testimony, involvement in therapy, length of delay, age of complainant, presence of experts, and frequency of abuse) two (age of complainant and presence of expert) predicted verdicts. An additional five variables (duration, severity, complainant-accused relationship, threats, and complainant gender) were also examined: of these, threats and the complainant-accused relationship reliably predicted jury verdicts. For judge-alone trials, five variables predicted verdict: length of the delay, offence severity, claims of repression, the relationship between complainant and accused, and presence of an expert. Implications of the jurors' and judges' differential sensitivity to these variables for future simulation and archival research are discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it