Safer communities: investigating the international response to knife crime
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Violent crime is a frequent occurrence in the UK, predominantly due to knives, with both urban and rural areas significantly impacted. Personal casework experience of the author has involved the forensic laboratory examination of bladed weapons from including murder, sexual offences, armed robberies, aggravated burglaries, wildlife crime, cold case reviews and terrorism offences. The September 2017 Crime Survey of England and Wales recorded 37,443 knife offences; a 21% annual rise impacting 38 of 44 police forces. This has a profound societal impact on the multi-agency response. Critically, the NHS (National Health Service) reported a 7% increase in emergency hospital admissions resulting from knife related injuries. Other countries have similar experiences. In particular 2 Commonwealth nations are of particular interest due to encountering the use of bladed weapons. In particular, Australia (knives reportedly the most used weapon) and Canada (stabbing is deemed the most frequent homicide method). The Winston Churchill Memorial Trust facilitates travel fellowships for British citizens to visit other countries to obtain new knowledge for pertinent issues for dissemination upon their return. This particular Fellowship project will involve vital research being undertaken to form best practices to assist UK knife crime investigations. It is intended that federal and state/province police forces, forensic science facilities and academic institutions will be approached within Australia and Canada for interaction with practitioners and researchers. An insight into laboratory procedures, crime scene processing, police strategies and novel research developments could aid the UK in its response. Ultimately, a dual legacy is envisioned, in firstly aiding detections and convictions, whilst, in future, by also preventing crimes and reducing injuries. This presentation may facilitate the sharing of best practice and will therefore be of interest to law enforcement agencies and Criminal Justice Systems around the world.
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.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it