Opportunities for violence prevention in the night-time economy using agent-based modeling
Lead Research Organisation:
University of Leeds
Department Name: Law
Abstract
The NHS estimates that more than 10 million people in England drink above the safe recommended limits. Not only does this have severe health implications, but an association between alcohol consumption and violent behaviour has been routinely identified. To ameliorate alcohol-related violence there is a need to better understand how pubs and clubs influence drinking behaviour and the associated violent crime that often occurs in city centres at night. However, the relationships between the alcohol and violence are complex. Many biological, psychological and social factors shape drinking practices. From a social perspective, drinking patterns are necessarily context dependent, shaped by characteristics of the drinking location and the company with whom drinking takes place. attempts to leverage quantitative methods to better understand the complex drinking phenomenon have been hampered by difficulties in accounting for heterogeneity across the population of individuals, the effects of group dynamics, and the impacts of variations in practices across licensed premises. To resolve these issues, this project will apply agent-based modelling to explore drinking practices in the night-time economy in order to better understand their association with violent behavioural outcomes. Agent-based models attempt to represent the individuals, rather than merely considering the behaviour patterns of larger groups and demographics. ABMs represent a more natural description of a system and can act as a bridge between verbal theories and mathematical models. This research will aim at better understanding the cause of alcohol-related violence in the night time economy of Leeds city centre specifically, but eh models and academic insights will be more broadly applicable.
This research will enable an assessment of known strategies for preventing alcohol-related harm such as modifications to alcohol pricing and taxation, pub trading hours and clustering of licensed premises. In terms of policy impact, I envisage this research and its resultant findings being of interest to policing and community safety partners. The project also has broader relevance to the College of Policing and the local Council's planning and licensing departments.
This research will enable an assessment of known strategies for preventing alcohol-related harm such as modifications to alcohol pricing and taxation, pub trading hours and clustering of licensed premises. In terms of policy impact, I envisage this research and its resultant findings being of interest to policing and community safety partners. The project also has broader relevance to the College of Policing and the local Council's planning and licensing departments.
Organisations
People |
ORCID iD |
Daniel Birks (Primary Supervisor) | |
Natacha Chenevoy (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ES/P000746/1 | 30/09/2017 | 29/09/2027 | |||
1949468 | Studentship | ES/P000746/1 | 30/09/2017 | 29/06/2022 | Natacha Chenevoy |
Description | N8PRP Workshop on Machine Learning |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | Created in 2018, the N8PRP's Data Analytics and Training and Learning strands aims to deliver an ambitious Continuous Professional Development programme to a cohort of participants from 11 North of England forces. It seeks to make a practical step towards the digital transformation of policing by providing a foundation in essential data science methods and emergent technologies in machine learning and predictive analytics. The event at the Univeristy of Leeds was part of the Data Analytics and Training and Learning series of workshops. It received excellent feedback and triggered many interesting discussions about how the police could use such emergent technologies to reduce crime. |
Year(s) Of Engagement Activity | 2019 |
URL | https://github.com/nickmalleson/n8-prp-ml-practicals |
Description | Talk at Environmental Criminology and Crime Analytics conference 2019 (China) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | I presented my PhD research at the International Criminology conference ECCA and received valuable feedback. |
Year(s) Of Engagement Activity | 2019 |
Description | Visit to Durham Constabulary |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | I visited Durham Constabulary to discuss the terms of our partnerhsip (data exchange, expectations on both sides etc). This visit was very useful as I was shown around the control room, giving me a better understanding of police operations. |
Year(s) Of Engagement Activity | 2019 |