A Developmental Model of Serial Killers: a retrospective analysis
Bibliographic record
Abstract
Although in 2005 Hickey concluded that serial murder likely results from a combination of 'predisposition' and 'facilitating factors', he did not describe this predisposition nor did he define 'facilitating factors'.This research aimed to advance Hickey's conclusion by setting out the features of this predisposition and creating a model for identifying 'facilitating factors'.A new developmental model of serial killers was constructed by reformatting an existing military model of killing, deleting some of its components and adding others from the DSM IV's diagnostic criteria for PTSD.The model was then tested by analyzing biographical data collected on a sample of 34 known serial killers.The collected data yielded findings which challenged long held assumptions that dysfunctional mother/child relationships and psychopathy are integral to the occurrence of serial murder and suggested that social isolation, bullying, trauma, chronic emotional numbing and committing murder during adolescence are pivotal factors in serial killer development.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".