An Agent-Based Model approach to understanding changes in ethnic relations: applications to
neighbourhood ethnic composition and health.
Applications are invited for a 3-year Economic and Social Research Council (ESRC) PhD Studentship based at
the new ESRC-funded Centre on the Dynamics of Ethnicity (CoDE) under the supervision of Professor James
Nazroo, Dr Laia Bécares, and Dr Nick Shryane. The project provides a studentship covering UK/EU tuition fees
and an annual tax-free stipend at Research Council rates (£13, 590 in 2012/13). Funding will be for three years of full-time study (+3 Scheme), starting in October 2013 with an expected submission date of September 2016.
Background
Ethnic minority people living in areas with higher concentrations of other ethnic minority residents tend to be
healthier, to report higher social cohesion and decreased experiences of racism, and to be less detrimentally
affected by experienced racist events.
Neighbourhood effects on health consist of complex mutually dependent processes in which individuals interact
with each other and with their neighbourhoods, and where both individuals and areas adapt and change over
time. Incorporating the exploration of the role of ethnicity in the association between place and health adds an
extra layer of complexity, involving the interaction between place and ethnicity in the racialisation of both areas
and individuals. Recent years have seen a surge of national and international studies examining the association
between neighbourhood ethnic composition and health, with a view of understanding the mechanisms by which
residential composition impacts on health; however, work to date has been limited to statistical analyses of crosssectional datasets which aim to isolate area-level from individual-level effects on health, failing to model the
dynamic mechanisms by which individuals and areas interact with each other and change over time. Although the association between ethnic residential composition and health has been ascertained, the mechanisms and
processes by which ethnic residential composition impacts on health are still poorly understood, partly due to the limitations of the statistical methodologies currently used to study these processes.
Agent-based models provide an innovative way of understanding neighbourhood effects, as they can be used to
model the dynamic process related to place and health by examining mechanisms that involve interactions
between diverse individuals, and interactions between individuals and environments. Agent-based models also
allow for the specification of agents at several levels (individuals, neighbourhoods, and higher-level organisms),
providing additional information on how macro-level characteristics influence interactions occurring at the microlevel, and vice versa.
Research Objectives
This PhD project aims to model the dynamic processes related to changes in ethnic relations, and how these play out in terms of area effects on health.
The work is an independent course of enquiry that will add great value to the main aim of the project of
understanding of the contemporary patterning of ethnic inequalities and how this relates to the ways in which
ethnic identities are perceived, acted upon and experienced.
Methods
This interdisciplinary PhD project will apply a novel agent-based modelling approach to the study of
neighbourhood effects on health, examining how dynamics at the macro-level emerge from micro-level
interactions and adaptations, involving a bottom-up approach that will complement the contextual focus of the
large grant it is linked to.
Location
The PhD will be hosted at the Cathie Marsh Centre for Census and Survey Research (CCSR), University of
Manchester. The University of Manchester is part of the ESRC North West Doctoral Training Centre (NWDTC),
and the student will be based in the Social Statistics accredited pathway. NWDTC is characterised by the
emphasis placed on training and support in a wide spectrum of quantitative and qualitative methods. This is
enabled by placing at the centre of the NWDTC a methodology unit, MethodsNorthWest, built upon the
established success of the Cathie Marsh Centre for Census and Survey Research, Methods@Manchester and
the Lancaster Postgraduate Statistics Centre. The PhD student will have access to the latest developments in
social science methodology through MethodsNorthWest conferences and will be able to take full advantage of
existing resources in each of the institutions within the NWDTC (Universities of Manchester, Lancaster and
Liverpool).
Supervision
The student will be embedded within the research team at the University of Manchester, and will be supervised by Professor James Nazroo and Dr Laia Bécares. Dr Nick Shryane, a research fellow within the Social Statistics
Discipline Area at the University of Manchester, will also be included in the supervisory team to provide support on social simulation. Dr Shryane has experience in applying the use of agent-based models to the study of
immigration and diversity, and the PhD student will benefit from his methodological expertise.
Admissions Criteria
Applicants should hold a minimum upper-second honours degree (or equivalent) in sociology, geography,
epidemiology, computational social science, or related area, and a Masters-level degree in a relevant discipline.
Experience of programming and/or simulation is a plus.
How to apply
Applicants are required to provide: (i) an academic CV; (ii) official academic transcripts; (iii) contact details of two suitable referees; and (iv) a cover letter outlining your suitability for the study and your research experience to date.
Applications (research proposal, statement and CV) should be emailed to: [email protected]. The
successful candidate will be required to submit a full University of Manchester on-line application, plus supporting
documents (two academic references and degree transcripts) to fulfil the normal admissions process.
Any enquiries relating to the project and/or suitability should be directed to Dr Bécares at the address above.
Deadline
The deadline for applications is January 31st 2013. Candidates may be called for interview in early February
2013