In this episode we explore different classifications of models and dicuss problems such as the problem of accuracy (what does it mean for a model to be accurate and is it always something to strive for?), the problem of style (what are the different ways of representing?), and the problem of ontology (what types of things are models).  We also discuss idealizations (omissions or distortions that make a model more explanatory or that allow it to be used mathematically) and the role it plays in scientific modelling. 

Some references:

• Frigg, Roman and James Nguyen, 2016, “The Fiction View of Models Reloaded”, The Monist, 99(3): 225–42.
• Frigg, Roman, and Stephan Hartmann. "Models in science." (2006).
• Niiniluoto, Ilkka, 1988, “Analogy and Similarity in Scientific Reasoning”, in Analogical Reasoning: Perspectives of Artificial Intelligence, Cognitive Science, and Philosophy, D.H. Helman (ed.), Dordrecht: Kluwer, 271–98.
• Toon, Adam, 2010, “Models as Make-Believe”, in Frigg and Hunter 2010: 71–96.

• Vaihinger, Hans, 1911 [1924], The Philosophy of ‘as If’: A System of the Theoretical, Practical, and Religious Fictions of Mankind, 1924 English Translation, London: Kegan Paul.

• Weisberg, Michael, 20072013, Simulation and Similarity: Using Models to Understand the World, Oxford: Oxford University Press.