Lost Highways: An Examination of the Question of Risk Involved in Sexual Homicides of Hitchhiking Victims
Bibliographic record
Abstract
Despite cultural references to the dangers of hitchhiking, particularly for sexual homicide, no published research investigates these incidents from both an offender and crime scene perspective. Using the Sexual Homicide International Database (SHIelD), we explore lifestyle risk by comparing sexual homicide cases involving hitchhiking victims to those involving victims engaged in sex trade work. The results, based on the use of bivariate and multivariate statistics, indicate that offenders view hitchhiking victims as opportunities for confinement without physical restraint, often engaging in sexual acts and theft. While not primarily sadistic or sexually deviant, many offenders partake in criminal activities, exhibit psychological disorders, and possess weapons. Hitchhiking facilitates perpetrator-victim encounters due to its environmental characteristics. Victims in the sex trade, typically found in isolated locations, are at the mercy of offenders who drive them to unknown destinations. In contrast, murderers targeting low-risk victims display more sexual preoccupations, inserting foreign objects and engaging in postmortem activities. These distinctions suggest distinct offender profiles for each lifestyle.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".