Rape and sexual assault in investigative psychology: the contribution of sex offenders' research to offender profiling
Bibliographic record
Abstract
Abstract Research on sex offenders has mainly guided clinical practice for risk assessment and therapeutic intervention. However, the current scientific knowledge on these offenders and their crimes is, in many aspects, of great importance to criminal investigations. Consequently, there is a need to build bridges between investigative psychology and the research being conducted on sex offenders. Four areas of research on sex offenders that have clear implications to investigative psychology can be identified: (1) the consistency or ‘crime‐switching’ patterns of sex offenders; (2) the recidivism patterns of different types of sex offenders; (3) the police response to specific victim characteristics; and (4) the A → C equation of sexual assaults. This paper argues for a need to establish a dialogue between these two fields of research so that knowledge about sex offenders keeps growing whilst being able to inform policing practices in investigative psychology. Copyright © 2009 John Wiley & Sons, Ltd.
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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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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".