CHAPTER 1 Searching for Offenders’ Memories of Violent Crimes
Bibliographic record
Abstract
year-old citizen of Toronto, stabbed her abusive common-law husband to death. Margaret claimed to be amnesic for the crime. She claimed to have no memory whatsoever of the act of killing, but remembered events immediately before and after the killing (Gould & MacDonald, 1987; Porter, Birt, Yuille & Herve, 2001). The case attracted enor-mous media attention, and it was revealed that Margaret had been abandoned and abused as a child, experienced life as a sex-slave, pros-titute, alcoholic and drug addict, and had been exposed to violence throughout her life. Due to her history of longstanding abuse, Margaret herself and the women’s movement in Canada regarded her as a victim rather than a perpetrator. Eventually, she was acquitted of murder and received a probation sentence. Less than a year later, she killed her second husband and was sentenced to life imprisonment.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".