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Bootstrapping Knowledge About Social Phenomena Using Simulation Models

There are considerable difficulties in the way of the development of useful and reliable simulation models of social phenomena, including that any simulation necessarily includes many assumptions that are not directly supported by evidence. Despite these difficulties, many still hope to develop quite general models of social phenomena. This paper argues that such hopes are ill-founded, in other words that there will be no short-cut to useful and reliable simulation models. However this paper argues that there is a way forward, that simulation modelling can be used to "boot-strap" useful knowledge about social phenomena. If each bit of simulation work can result in the rejection of some of the possible processes in observed social phenomena, even if this is about a very specific social context, then this can be used as part of a process of gradually refining our knowledge about such processes in the form of simulation models. Such a boot-strapping process will only be possible if simulation models are more carefully judged, that is a greater selective pressure is applied. In particular models which are just an analogy of social processes in computational form should be treated as "personal" rather than "scientific" knowledge. Such analogical models are useful for informing the intuition of its developers and users, but do not help the community of social simulators and social scientists to "boot-strap" reliable social knowledge. However, it is argued that both participatory modelling and evidence-based modelling can play a useful part in this process. Some kinds of simulation model are discussed with respect to their suitability for the boot-strapping of social knowledge. The knowledge that results is likely to be of a more context-specific, conditional and mundane nature than many social scientists hope for.

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File URL: http://jasss.soc.surrey.ac.uk/13/1/8/8.pdf
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Article provided by Journal of Artificial Societies and Social Simulation in its journal Journal of Artificial Societies and Social Simulation.

Volume (Year): 13 (2010)
Issue (Month): 1 ()
Pages: 8

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Handle: RePEc:jas:jasssj:2009-20-2
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  1. J. Gary Polhill & Bruce Edmonds, 2007. "Open Access for Social Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(3), pages 10.
  2. Guillaume Deffuant & Frederic Amblard & Gérard Weisbuch, 2002. "How Can Extremism Prevail? a Study Based on the Relative Agreement Interaction Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(4), pages 1.
  3. Joshua M. Epstein, 2008. "Why Model?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(4), pages 12.
  4. John Curtice & David Firth, 2008. "Exit polling in a cold climate: the BBC-ITV experience in Britain in 2005," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(3), pages 509-539.
  5. José Manuel Galán & Luis R. Izquierdo, 2005. "Appearances Can Be Deceiving: Lessons Learned Re-Implementing Axelrod's 'Evolutionary Approach to Norms'," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(3), pages 2.
  6. Robert Axtell & Robert Axelrod & Joshua M. Epstein & Michael D. Cohen, 1995. "Aligning Simulation Models: A Case Study and Results," Working Papers 95-07-065, Santa Fe Institute.
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