
About
Biography
I returned to the University as Professor of Criminology and Research Methods in Summer 2017, having previously worked at the University of Warwick where I was Director of the Warwick Q-Step centre. I have always been a bit of a 'jobbing researcher' with wide ranging interests in the application of advanced quantitative methods across the Social Sciences. Currently my interests in Criminology include prison effects, the spatial patterning of crime and perceptions of crime, and the role of neighbourhood context. In methodology I am particularly interested in new developments in multilevel modelling, bayesian statistics, and survey methodology. I have also retained an interest in the public understanding of science, an area of work I got into before starting my PhD.
I am an associate editor for Sociology and the Journal of the Royal Statistical Society Series A. I am a member of the Royal Statistical Society Social Statistics Committee (secretary 2015-2021), sit on the editorial board of the British Journal of Criminology and I am co-director of the Surrey Centre for Criminology. I was also a REF panel member for the 2021 exercise (Sociology).
ResearchResearch interests
The main areas of research that I am currently involved in cover areas of Criminology and Survey Methods. In Criminology I have been particularly interested in understanding the impact of measurement error on recorded crime data, prison effects, as well as the role of neighbourhood context in shaping residents' experiences. I am also increasingly interested in the spatial patterning of crime and disorder. In Survey Methodology my 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. You can read more about the project here.
Key findings from this work can be found in:
Pina-Sánchez, J., Brunton-Smith, I., Buil-Gil, D., and Cernat, A. (under review) ‘rcme: A Sensitivity Analysis Tool to Explore the Impact of Measurement Error in Police Recorded Crime Rates’. International Journal of Social Research Methodology.
Pina-Sánchez, J., Buil-Gil, D., Brunton-Smith, I., and Cernat, A. (forthcoming) ‘The Impact of Measurement Error in Models Using Police Recorded Crime Rates’. Journal of Quantitative Criminology
Buil-Gil, D., Cernat, A., Brunton-Smith, I., Pina-Sánchez, J. (2022) ‘Comparing Measurements of Crime in Local Communities: A Case Study in Islington, London’. Police Practice and Research: An International Journal. Online first.
Cernat, A., Buil-Gil, D., Brunton-Smith, I., Pina-Sánchez, J., and Murrià-Sangenís, M. (2021) ‘Estimating Crime in Place: Moving Beyond Residence Location’. Crime and Delinquency. Online first.
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.
Key findings from this work can be found in:
McCarthy, D., and Brunton-Smith, I. (2018) 'The effect of penal legitimacy on prisoners' post-release desistance'. Crime and Delinquency, 64 (7): 917-938.
Brunton-Smith, I., and McCarthy, D. (2017) ‘The effects of prisoner attachment to family on re-entry outcomes: A longitudinal assessment’. British Journal of Criminology. 57 (2): 463-482.
Brunton-Smith, I., and McCarthy, D. (2016) ‘Prison legitimacy and procedural fairness: the view from prisoners across England and Wales’. Justice Quarterly. 33(6): 1029-1054.
Brunton-Smith, I., and Hopkins, K. (2014) 'The impact of experience in prison on the employment status of prisoners after release: Findings from the first 3 waves of Surveying Prisoner Crime Reduction (SPCR)' Report for Ministry of Justice.
Hopkins, K., and Brunton-Smith, I. (2014) 'Prisoners' experience of prison and outcomes on release: Results from Surveying Prisoner Crime Reduction (SPCR)' Report for Ministry of Justice.
Brunton-Smith, I., and Hopkins, K. (2013) 'The factors associated with reconviction following release from prison: Findings from the first 3 waves of Surveying Prisoner Crime Reduction (SPCR)' Report for Ministry of Justice.
NEIGHBOURHOOD CONTEXT
I am particularly interested in 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.
Key findings from this work can be found in:
Brunton-Smith, I., Sturgis, P., and Leckie, G. (2018) ‘How collective is collective efficacy? The importance of consensus in judgments about community cohesion and willingness to intervene’. Criminology
Brunton-Smith, I., Sutherland, A., and Jackson, J. (2014) 'Bridging structure and perception; On the social ecology of beliefs and worries about neighbourhood violence in London'. British Journal of Criminology. 54 (4): 503-526.
Sturgis, P., Brunton-Smith, I., Jackson, J., and Kuha, J. (2014) 'Ethnic diversity and the social cohesion of neighbourhoods in London'. Ethnic and Racial Studies, 37 (8): 1286-1309.
Sutherland, A., Brunton-Smith., I., and Jackson, J. (2013) 'Collective efficacy, deprivation and violence in London'. British Journal of Criminology, 53 (6): 1050-1074.
Brunton-Smith, I., and Sturgis, P. (2011) 'Do Neighborhoods Generate Fear of Crime?: An Empirical Test Using the British Crime Survey'. Criminology, 49 (2): 331-369.
METHODOLOGY
My research within the field of 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. I have 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. More recently I have been applying multiple imputation models to survey data with high attrition, including data with a multilevel structure.
Key findings from this work can be found in:
Brunton-Smith, I., Sturgis, P., and Leckie, G. (2017) ‘Detecting and understanding interviewer effects on survey data by using a cross-classified mixed effects location-scale model’. Journal of the Royal Statistical Society, Series A. 180 (2): 551-568.
Sturgis, P., Williams, J., Brunton-Smith, I., and Moore, J. (2017) ‘Fieldwork effort, response rate and the distribution of survey outcomes: a multi-level meta-analysis’. Public Opinion Quarterly. 81 (2): 5223-542.
Brunton-Smith, I., and Tarling, R. (2017) ‘Harnessing paradata and multilevel multiple imputation when analysing longitudinal survey data’. International Journal of Social Research Methodology, 20 (6): 709-720.
Brunton-Smith, I., Sturgis, P., and Williams, J. (2012) ‘Is success on the doorstep correlated with the magnitude of the interviewer design effect?’ Public Opinion Quarterly, 76 (2): 265-286.
Research projects
Re-counting crime: New methods to improve the accuracy of estimates of crimeJuly 2020-March 2022, £299,261, Economic and Social Research Council: Principal Investigator (with Pina-Sanchez, J., Cernat, A., and Bui-Gil, D)
Academic advisor for violent crime and vulnerabilityOctober 2020-March 2021, £8,400, College of Policing: Consultant
February 2019-March 2020, £18,000, College of Policing: Consultant
Violent crime in London: Trends, trajectories, and neighbourhood effectsMarch 2019, £35,000, College of Policing: Co-Investigator (with Bradford, B., Sutherland, A., and Hutt, O)
ICMS Workshop: Mathematical Criminology and Crime ScienceApril 2018, £21,700, Engineering and Physical Sciences Research Council: Co-Investigator (with Lloyd, D., Ramage, A., Short, M., and Wilson, S)
Evaluation of theft and drugs sentencing guidelinesAugust 2016 – October 2016, £11,207, Office of the Sentencing Council: Co-Investigator (with RAND Europe)
September 2015 – September 2016, £93,718, Sentencing Council: Co-Investigator (with RAND Europe, and Pina-Sanchez, J)
Missing Data in the Second Longitudinal Study of Young People in EnglandMarch 2016 – June 2016, £62,042, Department for Education: Co-Investigator (with RAND Europe, and Vignoles, A)
Understanding the impact of prison based diversion schemes on young people and prisonersJune 2015 – May 2018, £92,000, Dawes Trust: Co-Investigator (with Bullock, K)
Evaluation of the Green Deal and ECO programmes: Examining potential bias in the cluster sampling methodologyMarch 2014 – June 2014, Department of Energy and Climate Change: Co-Investigator (with Sturgis, P).
Spatial modelling of crime and perceptions of crimeJuly 2014 – May 2015, £7,273, British Academy: Principal Investigator (with Jones, K)
Curriculum Innovation: Integrating quantitative methods and substantive teaching for HE level one sociology studentsJanuary 2012 – December 2013, £60,000, Economic and Social Research Council: Co-investigator (with Bullock, K., and Meadows, R)
Surveying Prisoner Crime Reduction (SPCR) Analytic ProjectNovember 2011 – December 2012, £39,000, Ministry of Justice: Principal Investigator
Processes Influencing Democratic Ownership and ParticipationMay 2009 – April 2012, €1,495,000, European Commission Seventh Framework Programme: Co-ordinator Work Package 5 – Modelling Existing Survey Data (with Barrett, M., et al)
An assessment of the utility of interviewer observation variables for nonresponse adjustment in the National Survey for WalesSeptember 2011 – November 2011, Welsh Assembly Government: Co-investigator (with Sturgis, P) Surveying Prisoner Crime Reduction (SPCR) missing data projectOctober 2010 – March 2011, £59,000, Ministry of Justice: Principal Investigator (with Carpenter, J., Kenward, M., and Tarling, R)
The effect of demographic make-up on perceptions of ASB in LondonDecember 2009 – March 2010, £18,783, Government Office for London: Principal Investigator (with Tarling, R., and Sindall, K)
Research interests
The main areas of research that I am currently involved in cover areas of Criminology and Survey Methods. In Criminology I have been particularly interested in understanding the impact of measurement error on recorded crime data, prison effects, as well as the role of neighbourhood context in shaping residents' experiences. I am also increasingly interested in the spatial patterning of crime and disorder. In Survey Methodology my 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. You can read more about the project here.
Key findings from this work can be found in:
Pina-Sánchez, J., Brunton-Smith, I., Buil-Gil, D., and Cernat, A. (under review) ‘rcme: A Sensitivity Analysis Tool to Explore the Impact of Measurement Error in Police Recorded Crime Rates’. International Journal of Social Research Methodology.
Pina-Sánchez, J., Buil-Gil, D., Brunton-Smith, I., and Cernat, A. (forthcoming) ‘The Impact of Measurement Error in Models Using Police Recorded Crime Rates’. Journal of Quantitative Criminology
Buil-Gil, D., Cernat, A., Brunton-Smith, I., Pina-Sánchez, J. (2022) ‘Comparing Measurements of Crime in Local Communities: A Case Study in Islington, London’. Police Practice and Research: An International Journal. Online first.
Cernat, A., Buil-Gil, D., Brunton-Smith, I., Pina-Sánchez, J., and Murrià-Sangenís, M. (2021) ‘Estimating Crime in Place: Moving Beyond Residence Location’. Crime and Delinquency. Online first.
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.
Key findings from this work can be found in:
McCarthy, D., and Brunton-Smith, I. (2018) 'The effect of penal legitimacy on prisoners' post-release desistance'. Crime and Delinquency, 64 (7): 917-938.
Brunton-Smith, I., and McCarthy, D. (2017) ‘The effects of prisoner attachment to family on re-entry outcomes: A longitudinal assessment’. British Journal of Criminology. 57 (2): 463-482.
Brunton-Smith, I., and McCarthy, D. (2016) ‘Prison legitimacy and procedural fairness: the view from prisoners across England and Wales’. Justice Quarterly. 33(6): 1029-1054.
Brunton-Smith, I., and Hopkins, K. (2014) 'The impact of experience in prison on the employment status of prisoners after release: Findings from the first 3 waves of Surveying Prisoner Crime Reduction (SPCR)' Report for Ministry of Justice.
Hopkins, K., and Brunton-Smith, I. (2014) 'Prisoners' experience of prison and outcomes on release: Results from Surveying Prisoner Crime Reduction (SPCR)' Report for Ministry of Justice.
Brunton-Smith, I., and Hopkins, K. (2013) 'The factors associated with reconviction following release from prison: Findings from the first 3 waves of Surveying Prisoner Crime Reduction (SPCR)' Report for Ministry of Justice.
NEIGHBOURHOOD CONTEXT
I am particularly interested in 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.
Key findings from this work can be found in:
Brunton-Smith, I., Sturgis, P., and Leckie, G. (2018) ‘How collective is collective efficacy? The importance of consensus in judgments about community cohesion and willingness to intervene’. Criminology
Brunton-Smith, I., Sutherland, A., and Jackson, J. (2014) 'Bridging structure and perception; On the social ecology of beliefs and worries about neighbourhood violence in London'. British Journal of Criminology. 54 (4): 503-526.
Sturgis, P., Brunton-Smith, I., Jackson, J., and Kuha, J. (2014) 'Ethnic diversity and the social cohesion of neighbourhoods in London'. Ethnic and Racial Studies, 37 (8): 1286-1309.
Sutherland, A., Brunton-Smith., I., and Jackson, J. (2013) 'Collective efficacy, deprivation and violence in London'. British Journal of Criminology, 53 (6): 1050-1074.
Brunton-Smith, I., and Sturgis, P. (2011) 'Do Neighborhoods Generate Fear of Crime?: An Empirical Test Using the British Crime Survey'. Criminology, 49 (2): 331-369.
METHODOLOGY
My research within the field of 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. I have 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. More recently I have been applying multiple imputation models to survey data with high attrition, including data with a multilevel structure.
Key findings from this work can be found in:
Brunton-Smith, I., Sturgis, P., and Leckie, G. (2017) ‘Detecting and understanding interviewer effects on survey data by using a cross-classified mixed effects location-scale model’. Journal of the Royal Statistical Society, Series A. 180 (2): 551-568.
Sturgis, P., Williams, J., Brunton-Smith, I., and Moore, J. (2017) ‘Fieldwork effort, response rate and the distribution of survey outcomes: a multi-level meta-analysis’. Public Opinion Quarterly. 81 (2): 5223-542.
Brunton-Smith, I., and Tarling, R. (2017) ‘Harnessing paradata and multilevel multiple imputation when analysing longitudinal survey data’. International Journal of Social Research Methodology, 20 (6): 709-720.
Brunton-Smith, I., Sturgis, P., and Williams, J. (2012) ‘Is success on the doorstep correlated with the magnitude of the interviewer design effect?’ Public Opinion Quarterly, 76 (2): 265-286.
Research projects
July 2020-March 2022, £299,261, Economic and Social Research Council: Principal Investigator (with Pina-Sanchez, J., Cernat, A., and Bui-Gil, D)
October 2020-March 2021, £8,400, College of Policing: Consultant
February 2019-March 2020, £18,000, College of Policing: Consultant
March 2019, £35,000, College of Policing: Co-Investigator (with Bradford, B., Sutherland, A., and Hutt, O)
April 2018, £21,700, Engineering and Physical Sciences Research Council: Co-Investigator (with Lloyd, D., Ramage, A., Short, M., and Wilson, S)
August 2016 – October 2016, £11,207, Office of the Sentencing Council: Co-Investigator (with RAND Europe)
September 2015 – September 2016, £93,718, Sentencing Council: Co-Investigator (with RAND Europe, and Pina-Sanchez, J)
March 2016 – June 2016, £62,042, Department for Education: Co-Investigator (with RAND Europe, and Vignoles, A)
June 2015 – May 2018, £92,000, Dawes Trust: Co-Investigator (with Bullock, K)
March 2014 – June 2014, Department of Energy and Climate Change: Co-Investigator (with Sturgis, P).
July 2014 – May 2015, £7,273, British Academy: Principal Investigator (with Jones, K)
January 2012 – December 2013, £60,000, Economic and Social Research Council: Co-investigator (with Bullock, K., and Meadows, R)
November 2011 – December 2012, £39,000, Ministry of Justice: Principal Investigator
May 2009 – April 2012, €1,495,000, European Commission Seventh Framework Programme: Co-ordinator Work Package 5 – Modelling Existing Survey Data (with Barrett, M., et al)
October 2010 – March 2011, £59,000, Ministry of Justice: Principal Investigator (with Carpenter, J., Kenward, M., and Tarling, R)
December 2009 – March 2010, £18,783, Government Office for London: Principal Investigator (with Tarling, R., and Sindall, K)
Supervision
Postgraduate research supervision
I would be very interested to hear from potential PhD students interested in the use of quantitative methods to address important social questions, as well as students interested in aspects of survey methodology.
I currently supervise the following students:
Megan Georgiou (from October 2018)
Daniel Ennis (with Mathematics, from October 2018)
Natasha Kinloch
Eva Martinez-Cruz
Liam Fenn
Nicola Spencer Godfrey
Teaching
I am currently Director of Postgraduate Taught Degrees and Programme Leader for the MSc Social Research Methods. In October 2018 we changed the delivery of our advanced research methods modules, moving from semester-long to an intensive short course structure. This has allowed us to introduce a number of new modules (including Agent Based Modelling, Social Network Analysis, Advanced Qualitative Data Analysis, and Multilevel Modelling) and is the perfect way for students to learn advanced topics. If you would like to find out more about the new MSc, please feel free to get in touch.
Current teaching
- Social Data Analytics (MSc)
- Statistical Modelling (MSc Short Course)
- Multilevel Modelling (MSc Short Course)
I recently produced some NCRM training videos on multilevel modelling that you may find useful if you are unfamiliar with the technique. Being filmed is WAY outside of my comfort zone, so the results are less natural than I had hoped!
A few years ago I developed an online resource (with Karen Bullock and Rob Meadows) to assist students learning quantitative methods for the first time. If you would like to play around with the resources, you can register for free here.
Publications
Highlights
Sturgis, P., Brunton-Smith, I., and Jackson, J. (online) ‘Trust in science, social consensus and vaccine confidence’. Nature Human Behavior.
In this paper we make use of a global survey to explore levels of vaccine hesitancy across the world. We demonstrate the importance of trust in science for vaccine uptake with less vaccine hesitancy in countries where trust is high. We also highlight the central role of social consensus, with the positive link between trust and vaccine support only evident in countries where consensus is high.
You can read the full paper here, or take a look at this short blog.
Allum, N., Besley, J., Gomez, L., and Brunton-Smith, I. (2018) 'Disparities in science literacy'. Science, 360 (6391), 861-862.
This was the first detailed study to look at disparities in science knowledge between adults from different racial and ethnic backgrounds. We found that people from black and Hispanic backgrounds were less able to answer questions about scientific facts and processes compared to white Americans. The study, published in Science (!), looked at potential reasons behind the disparity, including differences in basic literacy skills, attitudes to science (some minority groups expressed less trust and confidence in science), demographic factors such as education, gender, where people live and religion. After adjusting for all of these factors, a persistent science literacy gap remains, which could be related to the difference in the quality of education experienced day to day and year over year by underserved groups. This suggests the quantity and quality of science education needs to be looked at and we may also need training and public awareness campaigns to help scientists, teachers and employers to be more sensitive to the subtle manifestations of bias.