Exploring Potential 'Extra-Familial' Child Homicide Assailants in the UK and Estimating their Homicide Rate: Perception of Risk--The Need for Debate
Bibliographic record
Abstract
High-profile child murders lead parents to fear for their children’s safety, but perception of risk is often at variance with reality. We explore the numbers of potential ‘Extra-familial’ child homicide assailants in the United Kingdom and estimate their actual murder rate to determine risk levels. A South of England study, equivalent to a 4 per cent sample of the UK population, of a decade of consecutive child homicides identified the characteristics of child homicide assailants, finding that the most frequent assailants—the ‘Intra-familial’—were very different from ‘Extra-familial’ assailants. ‘Extra-familial’ killers were all males, aged nineteen to forty-two, with convictions for Violent-Multi-Criminal-Child-Sex-Abuse (VMCCSA) offences and Multi-Criminal-Child-Sex-Abuse (MCCSA), whose victims were aged seven-plus years. Projecting these characteristics onto the male UK population enables us to estimate the numbers of potential UK ‘Extra-familial’ assailants, which are set against known UK child (five to fourteen) homicides (WHO, 2005). To account for any ‘hidden’ child homicides, deaths in the ‘undetermined’ violent death category, designated ‘Other External Cause’ (OEC), are calculated to provide a ‘maximum’ child homicide rate. There were potentially 912 VMCCSA and 886 MCCSA ‘Extra-familial’ offenders in the United Kingdom, who could be responsible for the WHO-reported UK three-year average of ‘Extra-family’ fifteen child homicide and seventeen OEC deaths per annum; a homicide rate of 12,061 per million (pm) for VMCCSA and 3,386 pm for MCSA, which is 1.21 and 0.34 per cent; however, the VMCCSA homicide rate was 403 times greater than the all children accident and cancer death rates. Though the vast majority of these potential assailants did not kill, comparatively, they are extremely dangerous. Practice and ethical issues are debated, which considers active outreach for the ‘treatable’ to possible ‘reviewable’ custodial sentences for the VMCCSA.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".