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Simulating the Social Processes of Science

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Abstract

Science is the result of a substantially social process. That is, science relies on many inter-personal processes, including: selection and communication of research findings, discussion of method, checking and judgement of others' research, development of norms of scientific behaviour, organisation of the application of specialist skills/tools, and the organisation of each field (e.g. allocation of funding). An isolated individual, however clever and well resourced, would not produce science as we know it today. Furthermore, science is full of the social phenomena that are observed elsewhere: fashions, concern with status and reputation, group-identification, collective judgements, social norms, competitive and defensive actions, to name a few. Science is centrally important to most societies in the world, not only in technical, military and economic ways, but also in the cultural impacts it has, providing ways of thinking about ourselves, our society and our environment. If we believe the following: simulation is a useful tool for understanding social phenomena, science is substantially a social phenomenon, and it is important to understand how science operates, then it follows that we should be attempting to build simulation models of the social aspects of science. This Special Section of JASSS presents a collection of position papers by philosophers, sociologists and others describing the features and issues the authors would like to see in social simulations of the many processes and aspects that we lump together as "science". It is intended that this collection will inform and motivate substantial simulation work as described in the last section of this introduction.

Suggested Citation

  • Bruce Edmonds & Nigel Gilbert & Petra Ahrweiler & Andrea Scharnhorst, 2011. "Simulating the Social Processes of Science," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(4), pages 1-14.
  • Handle: RePEc:jas:jasssj:2011-67-1
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    1. Moses Boudourides & Gerasimos Antypas, 2002. "A Simulation of the Structure of the World-Wide Web," Sociological Research Online, , vol. 7(1), pages 9-25, March.
    2. N. Gilbert, 1997. "A Simulation of the Structure of Academic Science," Sociological Research Online, , vol. 2(2), pages 91-105, June.
    3. Ismael Rafols & Alan L. Porter & Loet Leydesdorff, 2010. "Science overlay maps: A new tool for research policy and library management," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(9), pages 1871-1887, September.
    4. Christopher Watts & Nigel Gilbert, 2011. "Does cumulative advantage affect collective learning in science? An agent-based simulation," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 437-463, October.
    5. Derek De Solla Price, 1976. "A general theory of bibliometric and other cumulative advantage processes," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 27(5), pages 292-306, September.
    6. Ismael Rafols & Alan Porter & Loet Leydesdorff, 2009. "Overlay Maps of Science: a New Tool for Research Policy," SPRU Working Paper Series 179, SPRU - Science Policy Research Unit, University of Sussex Business School.
    7. Andreas Pyka & Nigel Gilbert & Petra Ahrweiler, 2006. "Simulating Knowledge-Generation and -Distribution Processes in Innovation Collaborations and Networks," Discussion Paper Series 287, Universitaet Augsburg, Institute for Economics.
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    Cited by:

    1. Pawel Sobkowicz, 2017. "Utility, Impact, Fashion and Lobbying: An Agent-Based Model of the Funding and Epistemic Landscape of Research," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(2), pages 1-5.
    2. Juste Raimbault, 2019. "Exploration of an interdisciplinary scientific landscape," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 617-641, May.
    3. David Chavalarias, 2017. "What’s wrong with Science?," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 481-503, January.
    4. Francisco Grimaldo & Mario Paolucci & Jordi Sabater-Mir, 2018. "Reputation or peer review? The role of outliers," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1421-1438, September.
    5. Loet Leydesdorff, 2015. "Can intellectual processes in the sciences also be simulated? The anticipation and visualization of possible future states," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2197-2214, December.

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