Decision Making in the Crime Commission Process
Bibliographic record
Abstract
Based on a rational choice approach, this study compares the decision making involved in the crime commission process of rapists ( n = 30), child molesters ( n = 17), and victim-crossover sex offenders ( n = 22). Using a mixed-methods framework and following Clarke and Cornish’s decision-making model, the authors organized offenders’ narratives collected during semistructured interviews into three major areas: (a) offense planning (i.e., premeditation of the crime, estimation of risk of apprehension by the offender, and forensic awareness of the offender); (b) offense strategies (i.e., use of a weapon, use of restraints, use of a vehicle, and level of force used; and (c) aftermath (i.e., event leading to the end of crime and victim release site location choice). Results emphasize the important role of situational factors and age of the victim on the decision-making process of serial sex offenders. Moreover, results show that because of particular choice-structuring properties, the decision making varies across different groups of serial sex offenders.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".