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Complexity and Method in Social Sciences

Complexity and Method in Social Science









This is an ESRC Seminar Series (2014-2017) co-organised by Dr Emma Uprichard (PI, Centre for Interdisciplinary Methodologies, Warwick, UK), Professor David Byrne (Durham University, UK) and Professor Brian Castellani (Kent State University, USA).


Seminars


Organisers and Participants


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complexity

Overall aims

  • To create an interdisciplinary network of scholars working on the methodological challenges of applying complexity to social science research problems;
  • To develop a mixed-methods toolkit to more effectively model complex social systems;
  • To improve complex systems methodological pedagogy of social science students by:
    • Developing a set of pedagogical and policy recommendations relating to complexity related research methods;
    • Providing feedback to the Nuffield/ESRC/HEFCE funded Q-Step Centres.

Key methodological questions

  • How do we capitalize on big data and real-time data for complexity social science research?
  • How might we describe and explain patterns of change and continuity through time and space, and, importantly, how to do this whilst also accounting for a dynamic context?
  • Conversely, how do experiences and processes of time, temporality, space and place impact on the possibilities of change and continuity?
  • How might we explore causality in complex social systems for policy planning and intervention?
  • How can we bridge quantitative, qualitative and computational methods to better understand complex social systems empirically (e.g. via government surveys, public and commercial transactional data, neural nets, agent-based models, clustering techniques, network analysis, geographical modeling, visual complexity, case-based modeling, qualitative narratives etc.)?
  • How might we bring together different epistemological approaches to researching complexity in general, and conduct better inter- and multi-disciplinary complexity social science specifically?

Supported

ESRC