CECAN Seminar - 3rd April 2017 - Professor Phil Haynes
BEIS, 1 Victoria Street, London 12.45pm - 2pm
Dynamic Pattern Synthesis (DPS) : A mixed method for exploring longitudinal patterns in social science data.
Dynamic Pattern Synthesis (DPS) is a new mixed method designed by Philip Haynes that seeks to maximise the advantages of Cluster Analysis and Qualitative Comparative Analysis (QCA) to search for dynamic patterns in data. First trials with the method have been with macro country comparisons, including a study of the first ten years of the Euro currency membership - seeking to understand the complexities of economic convergence and divergence. This also included comparing welfare state regimes from the first twelve Euro member countries.
When: – Friday 7th July 2017 (1 day)
Location: – University of Surrey, Guildford, UK
Purpose: The complex socio-technical arenas (nexus issues) that government seeks to improve (e.g., health, food, water, safety, infrastructure) are not driven by a single factor or consequence. Instead, they are driven by multiple factors at multiple levels, which lead to different trends or outcomes for different areas/groups of people.
The challenge is how to model such diversity and complexity? The complexity sciences, data mining and big-data offer some useful solutions. The challenge, however, is stitching these methodological solutions together into a user-friendly platform and APP, which policy makers, social scientists, evaluation commissioners and civil servants can use – hence our creation of COMPLEX-IT and the SACS TOOLKIT.