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The research used police reported public place VAWG data over ten years(2013 to 2022) and the Cambridge Crime Harm Index to map and analyse micro-geolocations for their incident, harm and their longitudinal concentration.
50% of VAWG crime and harm are concentrated in 3.03% and 2.15% of public places, with smaller hexagonal sizes resulting in higher harm concentrations.
The unsupervised machine learning analysis for longitudinal k-means clustering (KmL) identified the most stable hotspots and harm spots. By finding the overlap between these public places, the research identified the 19 most persistent hotspots of high harm for targeting crime reduction initiatives. This method bypasses the limitations of simple crime counts and solely harm-based mapping. The central and local government's response and funding for interventions need to be targeted and evidence-based rather than taking a scattergun approach.
The crime spiked between 3 pm and 5 pm on weekdays, and the harm spiked at midnights, but their concentrations were in different locations. The commercial city centres saw ham spikes at night when they lacked capable guardianship from businesses.
The Risk-Adjusted Disparity Index analysis identified that 15–19-year-old victims suffered 21 to 45 times more harm than the over-30 group. This was closely followed by 10–15-year-olds. Suspects from within their age groups caused the highest levels of crime and harm for 10–19-year-old girls. Collaboration between police, safeguarding partners, and educational institutions is crucial for providing guardianship of places and educating against misogyny and unhealthy relationships.
Black women and girls suffered four times the harm per thousand population than the Asian group in 2013, and this worsened over time to ten times by 2022, despite the area becoming more ethnically diverse. Systematic intersectional strategies are required to enhance understanding and preventative responses to racial disparity.