Crime Scene Behaviors and Characteristics of Offenders with Mental Illness: A Latent Class Analysis
Bibliographic record
Abstract
The current study aimed to identify distinct types of crime scene behaviors based on the criminal planning and motivation of offenders with mental illness in South Korea. Furthermore, our study examined the relationships between the identified types of crime scene behaviors in terms of the offenders' sociodemographic characteristics, modus operandi, and types of mental illness. Utilizing latent class analysis, the associations between crime scene behavior types and offender characteristics such as demographic factors, crime scene actions, and criminal information were empirically investigated. In particular, based on a sample obtained from a national police database of offenses committed between 2006 and 2014, four offense groups were identified: (i) instrumental-planned, (ii) instrumental-unplanned, (iii) expressive-unplanned, and (iv) hybrid. Additionally, significant relationships were found between offense styles and offender characteristics as well as criminal backgrounds. The findings suggest that mental disorders influence the types of actions exhibited by offenders during the commission of their crime. The results are discussed in terms of their theoretical and practical utility to criminal investigation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".