© 2018 – Routledge
How is it possible to understand society and the problems it faces? What sense can be made of the behaviour of markets and government interventions? How can citizens understand the course that their lives take and the opportunities available to them?
There has been much debate surrounding what methodology and methods are appropriate for social science research. In a larger sense, there have been differences in quantitative and qualitative approaches and some attempts to combine them. In addition, there have also been questions of the influence of competing values on all social activities versus the need to find an objective understanding. Thus, this aptly named volume strives to develop new methods through the practice of 'social synthesis', describing a methodology that perceives societies and economies as manifestations of highly dynamic, interactive and emergent complex systems. Furthermore, helping us to understand that an analysis of parts alone does not always lead to an informed understanding, Haynes presents to the contemporary researcher an original tool called Dynamic Pattern Synthesis (DPS) - a rigorous method that informs us about how specific complex social and economic systems adapt over time.
A timely and significant monograph, Social Synthesis will appeal to advanced undergraduate and postgraduate students, research professionals and academic researchers informed by Sociology, Economics, Politics, Public Policy, Social Policy and Social Psychology.
I highly recommend this book which has several case-studies of complex change over time. Complexity theory fits the social sciences well because there is both stability and instability in the social patterns. Here we find good empirical examples. The author observes patterns over time using three main methods: a complex cluster analysis, the discerning of prime implicants from among the configuration’s characteristics, and Boolean truth-table analysis. The author thus reduces and simplifies the findings. The book makes extensive use of Qualitative Comparative Analysis (QCA) while extending this ‘mixed method’ to an intertemporal range.
Wendy Olsen, Reader in Socio-Economic Research, The University of Manchester, UK
This book responds to two important currents influencing contemporary social science: critical realism and complexity science. It provides an account of a promising new analytic method, Dynamic Pattern Synthesis, and illustrates how one can use the method with examples including the analysis of health and social care. I look forward to the application of this innovative and powerful method to a wide range of policy-relevant topics.
Nigel Gilbert, Professor of Sociology, University of Surrey, UK
List of Boxes
List of Figures
List of Tables
Chapter One: Methodology: towards a representation of complex system dynamics
The classical reductionist method
Beyond reductionist science
Sensitivity to initial conditions
Summarising the influences of complexity theory
Understanding system change as patterns
Complexity in economic systems
Time and Space
Case similarity and difference
Convergence and divergence
Chapter Two: the Method - introducing Dynamic Pattern Synthesis (DPS)
Cluster Analysis (CA)
Cluster Analysis: specific approaches
Hierarchical and non-hierarchical cluster analysis
Using SPSS to calculate and compare cluster methods
Further considerations of the effects of clustering algorithms
Understanding variable relationships within cluster formulation
Repeating Cluster Analysis over time
Qualitative Comparative Analysis (QCA)
Crisp set QCA
Accounting for time in case based methods
Combining the two methods: Cluster Analysis and QCA
QCA and software packages
An alternative confirmation method: ANOVA
The application of Custer Analysis and QCA as a combined method
Dynamic Pattern Synthesis: seven cities, three years later
Threshold setting for binary crisp set conversion
Primary Implicant ‘near misses’
Other considerations for the Dynamic Pattern Synthesis
The stability of variables in DPS
Stability of cases in the chosen sample
The size of the chosen sample
The number of time points in the DPS
Chapter Three: macro examples of Dynamic Pattern Synthesis (DPS)
Macro case study 1: health and social care in Europe
Macro Case study 1, wave 1, 2004
Macro case study 1, wave 2, 2006
Macro case study 1, wave 4, 2010
Macro case study 1, wave 5, 2013
Macro case study 1: conclusions
Macro case study 2: the evolution of the euro based economies
Macro case study 2, wave 1, 2002
Macro case study 2, wave 2, 2006
Macro case study 2, wave 3, 2013
Macro case study 2: conclusions
Chapter Four: A meso case study example: London Boroughs
Meso case study: 2010
Meso case study, 2011
Meso case study, 2012
Meso case study: conclusions
Chapter Five: micro case study example: older people in Sweden
Micro case study: older people in Sweden born in 1918
Micro case study: wave 1, 2004
Micro case study, wave 2, 2006
Micro case study, wave 4, 2010
Conclusions for the micro case study
Chapter Six: Conclusions
Dynamic Pattern Synthesis (DPS) and different dynamic typologies
The stability of case and variable interactions: towards some typologies
Reflections on complexity theory and DPS
Short and long range interactions and feedbacks
System openness and dynamics
Case and Data Patterns
Case dynamics and complexity theory
This interdisciplinary series encourages social scientists to embrace a complex systems approach to studying the social world. A complexity approach to the social world has expanded across the disciplines since its emergence in the mid-to-late 1990s, and this can only continue as disciplines continue to change, data continue to diversify, and governance and responses to global social issues continue to challenge all involved. Covering a broad range of topics from big data and time, globalization and health, cities and inequality, and methodological applications, to more theoretical or philosophical approaches, this series responds to these challenges of complexity in the social sciences – with an emphasis on critical dialogue around, and application of these ideas in, a variety of social arenas as well as social policy.
The series will publish research monographs and edited collections between 60,000–90,000 words that include a range of philosophical, methodological and disciplinary approaches, which enrich and develop the field of social complexity and push it forward in new directions.
David Byrne is Emeritus Professor at the School of Applied Social Sciences, Durham University, UK.
Brian Castellani is Professor in Sociology and Head of the Complexity in Health and Infrastructure Group, Kent State University, USA. He is also Adjunct Professor of Psychiatry, Northeastern Ohio Medical University.
Emma Uprichard is Reader at the Centre for Interdisciplinary Methodologies, University of Warwick, UK. She is also director of the Nuffield, ESRC, HEFCE funded Warwick Q-Step Centre aimed at promoting quantitative methods across the social sciences.