Stranger Danger: Analyzing Offender Behaviors Based on Victim Approach Tactics in Sexual Homicide
Bibliographic record
Abstract
Victims of sexual homicide may be deceived by perpetrators who use a friendly approach to gain access to them, making it difficult for the victim to assess the danger posed by the stranger. When investigating sexual homicides committed by strangers, investigators often lack direct information, including how the perpetrator gained access to the victim. To identify potential predictors of the approach method used in sexual homicides, this study analyzed the preferences and behaviors of sexual murderers who target strangers based on their approach method. The results of the logistic regression analysis showed that in comparison to offenders using "blitz" or "surprise" attacks, those using a deceptive "con" approach tended to have more male victims, exploit vulnerability, and exhibit post-crime organization by relocating the victim's body and successfully disposing of the weapon used in the crime. Their crimes also more frequently involved oral sex and had lower rates of victim beating. This study discusses the investigative implications of these findings.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".