Dr Peter Barbrook-Johnson
Pete joined PSI in June 2016 as a Research Associate. He is currently working on the ESRC/NRF/Newton Fund funded ISULabaNtu project concerning community-led upgrading of informal settlements in South Africa, the H2020 MIN-GUIDE project, concerning EU mineral policy, and the ESRC funded Centre for the Evaluation of Complexity across the Nexus. In addition to his research activities, Peter is part of the core team delivering the module ‘Environmental Change & Transition to a Low Carbon Society’ on the MA course, Energy and Environmental Change.
Pete has experience in a range of research methods including agent-based modelling of social and policy systems, stakeholder causal mapping, and qualitative and quantitative social research methods. His main research interests focus on the interaction between environmental policy, social and behavioural science, and complexity science. Pete regularly delivers short courses and teaching on agent-based modelling, and has experience delivering social research methods teaching (including statistics) to undergraduates, PhD students, and early-career researchers.
Prior to joining PSI, Pete worked at the University of Surrey, in the Centre for Research in Social Simulation (CRESS), as a Research Fellow. He also completed his PhD in Computational Social Science at CRESS and is a Visiting Research Fellow there. He worked on topics including, farmer behaviour and soil conservation, household adoption of solar panels, protective behaviour during epidemics, commons-based peer production, watershed management, and industrial ecology. Pete has a BA in Economics from the University of East Anglia, and an MSc in Environmental Technology from Imperial College London, where he specialised in Environmental Economics and Policy.
Pete is on Twitter - @bapeterj - and his personal website can be found at www.barbrookjohnson.com
- Computational modelling (especially agent-based modelling)
- Using models as discussion tools
- Social and behavioural science
- Complexity science applied to social science and policy issues
- Stakeholder mapping (eg, fuzzy cognitive mapping)
- Use of models in policy
- PhD Computational Social Science, University of Surrey
- MSc Environmental Technology: Environmental Economics and Policy, Imperial College London
- BA Economics, University of East Anglia
January 2017 to August 2021
March 2016 to March 2019
February 2016 to January 2019
February 2016 to February 2019
Barbrook-Johnson, P., Badham, J., Gilbert, N. (2016) Uses of agent-based modeling for health communication: The TELL ME case study. Health Communication. DOI: 10.1080/10410236.2016.1196414
Anzola, D., Barbrook-Johnson, P., Cano, J. (2016) Self-organisation and Social Science. Computational and Mathematical Organization Theory. DOI: 10.1007/s10588-016-9224-2
Johnson, P. (2015). Agent-Based Models as “Interested Amateurs”. Land. 4(2), 281- 299. doi:10.3390/land4020281
Gilbert, N., Anzola, D., Johnson, P., Elsenbroich, C., Balke, T., Dilaver Kalkan, O. (2015). Self- organizing dynamical systems. In: James D. Wright (editor-in-chief), International Encyclopedia of the Social and Behavioral Sciences, 2nd edition, Vol 21. Oxford: Elsevier. pp. 529-534. Elsevier.
Johnson, P. (2014). Using the Telephone to Interview Professionals: Understanding the Use of Models in Environmental Policy. SAGE Research Methods Cases.