David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Philosophical Studies 143 (1):33 - 57 (2009)
The paper presents an argument for treating certain types of computer simulation as having the same epistemic status as experimental measurement. While this may seem a rather counterintuitive view it becomes less so when one looks carefully at the role that models play in experimental activity, particularly measurement. I begin by discussing how models function as “measuring instruments” and go on to examine the ways in which simulation can be said to constitute an experimental activity. By focussing on the connections between models and their various functions, simulation and experiment one can begin to see similarities in the practices associated with each type of activity. Establishing the connections between simulation and particular types of modelling strategies and highlighting the ways in which those strategies are essential features of experimentation allows us to clarify the contexts in which we can legitimately call computer simulation a form of experimental measurement.
|Keywords||Simulation Modelling Experiment Calculation Material systems|
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References found in this work BETA
Vadim Batitsky (1998). Empiricism and the Myth of Fundamental Measurement. Synthese 116 (1):51 - 73.
Rudolf Carnap (1936). Testability and Meaning. Philosophy of Science 3 (4):419-471.
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Citations of this work BETA
Eran Tal (2013). Old and New Problems in Philosophy of Measurement. Philosophy Compass 8 (12):1159-1173.
Claus Beisbart (2012). How Can Computer Simulations Produce New Knowledge? European Journal for Philosophy of Science 2 (3):395-434.
Miles MacLeod & Nancy J. Nersessian (2013). Coupling Simulation and Experiment: The Bimodal Strategy in Integrative Systems Biology. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):572-584.
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