Bibliographic record
Abstract
The authors present a rare case of a family in which both the mother, and four decades later the son, committed second-degree murder while suffering from major mental illnesses. The mother had successfully used a mental disorder defence and it was likely that the son who had raised the defence would have qualified also. The mother has a history of adverse childhood experiences. The son had also experienced various severe childhood adversities, though there were no functional impairments, personality dysfunction, suicidality or violent crimes until the onset of treatment-resistant schizoaffective disorder around age 18. His earlier comorbidities included sport-related traumatic brain injuries, sickle cell trait, severe burns, and tardive dyskinesia. His comorbidities around the material time included occasional cannabis use and dementia pugilistica. While awaiting court ruling on criminal responsibility, additional stressors triggered significant deterioration of his schizoaffective disorder and the court found him unfit to stand trial. During rehabilitation, he was severely injured by another accused, which subsequently led to his demise. This case is the first report of intergenerational mental disorder defence and involved almost every facet of criminal forensic psychiatry, which highlights the need for further research on the association between intergenerational ACEs and intergenerational risk for criminal behaviour from a comprehensive and longitudinal perspective.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".