Decision Making and Aggression in Forensic Psychiatric Inpatients
Bibliographic record
Abstract
This study provides initial empirical support for a novel neurobiological decision-making model proposed by Nussbaum (2005), applied to an aggression typology (Nussbaum, Saint-Cyr, & Bell, 1997). The Iowa Gambling Task (IGT; Bechara, Damasio, Damasio, & Anderson, 1994) was analyzed for forensic inpatients using both the traditional method of scoring reflecting motivational decision making and a novel method developed by Yechiam, Busemeyer, Stout, and Bechara (2005) that provides scores for three cognitive decision-making components: attention, learning, and response-choice consistency. Predatory seclusions were predicted by traditional motivational scoring of the IGT but not by the cognitive scores. Conversely, Irritable seclusions were predicted only by the cognitive scoring system. Based on these findings, the utilization of the aggression typology and the inclusion of these clinical measures could enhance and refine violent risk assessment, suggest specific treatment targets for different aggression types, and monitor responses to interventions prior to release into the community.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".