Professor Ian Brunton-Smith

Visiting Professor

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Ian Brunton-Smith is Professor of Criminology and Research Methods at the University of Surrey. He has wide ranging interests in the application of advanced quantitative methods across the Social Sciences including new developments in multilevel modelling, bayesian statistics, and survey methodology. He currently holds an evaluation fellowship with the Ministry of Justice (funded by ESRC and ADR UK) to explore the research opportunities available from the new administrative data linkages across the Criminal Justice System. He is also Principal Investigator of an ESRC funded project examining the impact of measurement error in crime data.

Professor Brunton-Smith is associate editor for Sociology and the Journal of the Royal Statistical Society Series A and sits on the editorial board of the British Journal of Criminology. He is co-director of the Surrey Centre for Criminology, member of the Police Funding Formula Technical Reference Group and on the steering group of the Crime Surveys Transformation Project. He was also a REF panel member for the 2021 exercise (Sociology).

Research Interests

In Criminology Ian has been working to understanding the impact of measurement error on recorded crime data. His work also examines the impact of prison effects, as well as the role of neighbourhood context in shaping residents' experiences. In Survey Methodology his research has tended to focus on the role of interviewer effects.

Recounting Crime - Accounting for Measurement Error in Recorded Crime Data
It is well known that police recorded crime data are an imperfect measure of crime. Not only do the police fail to record some offences, but the public also regularly choose not to report things to the police in the first place. Taken together, this 'dark figure' of crime can have serious implications for the validity of any empirical work using recorded crime data. In this research project we treat this as a measurement error problem, exploring different ways to assess the sensitivity of empirical results to the presence of these errors.

Prison Effects
This work explores the impact of prison experience on reoffending and employment amongst a cohort of nearly 4,000 prisoners using survey data from the Surveying Prisoner Crime Reduction (SPCR) survey linked to the Police National Computer. This includes the application of multilevel models to adjust for prison context, and longitudinal models to examine changes in prisoner experience and attitudes over time.

Neighbourhood Context
Ian’s work has examined the potential impact that neighbourhood context has in shaping local residents perceptions. This has involved the application of multilevel models to crime survey data in order to identify the contribution of neighbourhood context, and combining this with contextual information from the census of England and Wales.

Methodology
Ian’s research in survey methodology focuses specifically on the potential contribution that interviewers make to estimates of measurement error in face to face surveys. This is examined with the application of cross-classified multilevel models with a complex error structure to face to face survey data. He has also been involved in work looking at the potential for interviewer observation data collected during the interview to adjust survey estimates for nonresponse bias, as well as the potential for panel conditioning effects in longitudinal surveys.

Chapters and Reports within the last five years

Brunton-Smith, I., Buil-Gil, D., Pina-Sánchez, J., Cernat, A., and Moretti, A. (forthcoming) ‘Using synthetic crime data to understand patterns of police under-counting at the local level’, in Huey, L, and Buil-Gil, D (eds) The Crime Data Handbook.

Shoesmith, H., Brunton-Smith, I., Tseloni. A., Thompson, R., and Druckman, A. (forthcoming) ‘The carbon footprint of crime and security’, in Gill, M (ed) The Handbook of Security. (3rd edition).

Buil-Gil, D., Pina-Sánchez, J., Brunton-Smith, I., and Cernat, A. (2022) ‘Bad Data, Worse Predictions: How Measurement Error in Crime Data Affects Crime Prevention’. CREST Security Review Magazine.

Buil-Gil, D., Brunton-Smith, I., Pina-Sánchez, J., Cernat, D., and Moretti, A. (2021). ‘Synthetic crime data in England and Wales (version 0.1)’. Zenodo. doi.org/10.5281/zenodo.5767752

Sutherland, A., Brunton-Smith, I., Hutt, O., and Bradford, B. (2020) ‘Violent crime in London: Trends, trajectories, and neighbourhood effects’. Report for the College of Policing.

Sturgis, P. Brunton-Smith, I., and Jackson, J. (2019) ‘Regression-based response probing for assessing the validity of survey questions’, in Beatty, P., Collins, D., Kaye, L., Padilla, J-L., Willis, G., and Wilmott, A. (eds) Advances in Questionnaire Design, Development, Evaluation and Testing. Wiley (in press).

Brunton-Smith, I. (2020) ‘Chapter 31 – Systematic Social Observation’ in Johnson, S., and Bruinsma, G. (eds) The Oxford Handbook of Environmental Criminology, Oxford University Press.

Jackson, J., Bradford, B., Brunton-Smith, I., and Gray, E. (2018) ‘In the eye of the (motivated) beholder: Towards a motivated cognition perspective on disorder perceptions’ in Lee, M., and Mythen. G. (eds) International handbook of fear of crime. Routledge. Oxon.

Brunton-Smith, I. (2018) ‘Fear 2.0: Worry about cybercrime in England and Wales’ in Lee, M., and Mythen. G. (eds) International handbook of fear of crime. Routledge. Oxon.