Male and Female Single-Victim Sexual Homicide Offenders: Distinguishing the Types of Weapons Used in Killing Their Victims
Bibliographic record
Abstract
Most studies have focused on male sexual homicide offenders (SHOs) without testing whether sex differences exist. Accordingly, little is known about the distinctions between male and female SHOs, particularly with respect to their use of weapons in killing their victims. This study used a sample of 3,160 single-victim sexual homicide cases (3,009 male and 151 female offenders) from the U.S. Supplementary Homicide Reports database to explore sex differences in the types of murder weapons used by offenders in killing victims over the 37-year period 1976 to 2012. Findings indicated that significantly more male SHOs used personal weapons (43%) and more female SHOs used firearms (63%) in their offense commission. In general, female offenders predominantly used weapons that were physically less demanding (e.g., firearms and edged and other weapons; 89%). Different trends in the murder weapons used by male and female SHOs from different age groups were observed. Interestingly, findings showed that the type of weapon used by SHOs was in part influenced by the victims and their characteristics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".