Preliminary insights and analysis into weapon enabled sexual offenders
Bibliographic record
Abstract
Purpose – Weapon use is recognised as a key crime concern in England and Wales but has received relatively little focused research. The purpose of this paper is to examine weapon use by sexual offenders to develop new insights relevant for a police audience. Specifically, to examine the prevalence of weapons within sexual offenders and explore the differences between weapon and non-weapon enabled offenders on a range of characteristics. Design/methodology/approach – A sample of 1,618 single, stranger, solved, serious sexual assaults were provided by the Serious Crime Analysis Section of the Serious Organised Crime Agency. In all, 20 per cent of offenders were weapon enabled. Findings – There were almost no demographic differences between weapon enabled and non-weapon enabled offenders. In terms of the offence itself, there were many significant differences between the groups in terms of precautions used, victim involvement, injury, attack behaviours, victim approach and attack location. Further multivariate analysis revealed aspects of the offence that were associated with weapon use; these are broadly discussed within themes of violence and evidence of planning. Originality/value – The authors argue that an examination of weapon use is valuable in illustrating how offenders differ in their offence and provide insights for the investigation of such crime.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".