The battered who commit homicide; an overview of battered person’s syndrome and battered child syndrome in Canadian and American contexts
Bibliographic record
Abstract
Battered Person's Syndrome (BPS) is a set of psychological symptoms experienced by victims who are victims of intimate partner violence. BPS may inform a defense in homicide cases wherein battered individuals killed their abusers. Similarly, Battered Child Syndrome (BCS) can be used as evidence to support a claim of self-defence wherein the child is the aggressor, and a care provider is the victim. Forensic psychiatrists provide expert opinion evidence regarding such claims of self-defence. A psycholegal opinion, often provided by forensic psychiatrists, can serve to identify factors that influence culpability and understanding of one's actions at the material time of the offenses. Both BPS and BCS can be considered in the context of such assessments, however, further description and comparison of these syndromes is lacking in the current literature. The purpose of this article is to provide a succinct examination of the psycholegal parameters related to BPS and BCS in the Canadian and American contexts and to provide a perspective on how both can be compared. We also highlight several landmark cases in both Canada and the United States and provide a brief overview of the imperative role that forensic psychiatrists play in the development of such cases.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".