New open access book, published by Springer, on alternative approaches and critiques to social science coming out of an EU project.
Edmonds, B. (2017) The Room Around the Elephant: Tackling Context-Dependency in the Social Sciences. In Johnson, J. et al. (eds), Non-Equilibrium Social Science and Policy, Springer. http://www.springer.com/us/book/9783319424224
Abstract
Context is crucial for understanding social phenomena, but is not being
addressed. Contexts can become socially entrenched and acquire their own labels,
allowing different social coordination systems to be developed for different kinds of
situation. Three ways to avoid context are discussed. Fitting data to mathematical
models which ‘explain’ the data using significance tests avoids the problems of
context, but may average over different contexts inappropriately. ‘Behavioural
foundationalism’, which assumes a generic model of behaviour that is valid across
different contexts, avoids the context problem by producing models based on a
micro-specification to see if the macro-consequences match the available data, e.g.
neo-classical decision theory and some agent-based simulations. A third strategy
to avoid the context problem is to retreat into specificity, providing so much detail
that the context is unique with no attempt at generalisation. Three ways forward are
proposed (1) using data mining techniques to look for models whose output ‘fits’
various target kinds of behaviour, (2) context-dependent simulation modelling, with
the memory of the agent being context-sensitive, and context-relevant knowledge
and behaviours being applied in decision-making, and (3) combining qualitative and
formal approaches, with neither qualitative nor quantitative evidence being ignored.
Agent-based modelling can use qualitative evidence to inform the behavioural
strategies that people use in given situations. Simulations based on micro-level
behaviours can produce numbers for comparison with macro-level quantitative data.
This supports experimentation to understand emerging processes, and investigate
the coherence of the qualitative assumptions and the quantitative evidence. Explicitly
recognising and including context-dependency in formal simulation models
allows for a well-foundedmethod for integrating qualitative, quantitative and formal
modelling approaches in the social sciences. Then some of the wealth of qualitative
ethnographic, observational and interviewing work of the social sciences can enrich
formal simulation models directly, and allow the quantitative and the qualitative to
be assessed together and against each other. Before the advent of cheap computing
power, analytic mathematical models were the only formal models available, but
their simplicity ruled out context dependency, leading to a focus on what generic models might tell us. New information and communication technologies have
resulted in a lot more data on social phenomena to distinguish different contexts and
behaviours. We no longer have to fit generic models due to data paucity and limits
to storage and processing, or ignore context or over-simplify what we observe to
obtain and use formal models. Addressing context has huge potential for the social
sciences, including: better models and understanding of human behaviour; more
effective ways of collecting, integrating and analysing data; and the prospect for
a well-founded means of integrating the insights from quantitative and qualitative
evidence and models.
About the book its in….
Non-Equilibrium Social Science and Policy
Introduction and Essays on New and Changing Paradigms in Socio-Economic Thinking
Editors: Johnson, J., Nowak, A., Ormerod, P., Rosewell, B., Zhang, Y.-C. (Eds.)
Springer, 2017.
http://www.springer.com/us/book/9783319424224
About the book:
The overall aim of this book, an outcome of the European FP7 FET Open NESS project, is to contribute to the ongoing effort to put the quantitative social sciences on a proper footing for the 21st century. A key focus is economics, and its implications on policy making, where the still dominant traditional approach increasingly struggles to capture the economic realities we observe in the world today – with vested interests getting too often in the way of real advances.
Insights into behavioral economics and modern computing techniques have made possible both the integration of larger information sets and the exploration of disequilibrium behavior. The domain-based chapters of this work illustrate how economic theory is the only branch of social sciences which still holds to its old paradigm of an equilibrium science – an assumption that has already been relaxed in all related fields of research in the light of recent advances in complex and dynamical systems theory and related data mining.
The other chapters give various takes on policy and decision making in this context. Written in nontechnical style throughout, with a mix of tutorial and essay-like contributions, this book will benefit all researchers, scientists, professionals and practitioners interested in learning about the ‘thinking in complexity’ to understand how socio-economic systems really work.