Titlebook: How to Do Science with Models; A Philosophical Prim Axel Gelfert Book 2016 The Author(s) 2016 Mathematical Models in Science.Model-based Re

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Book 2016 are and what their function is. Reliance on models is pervasive in science, and scientists often need to construct models in order to explain or predict anything of interest at all. The diversity of kinds of models one finds in science – ranging from toy models and scale models to theoretical and m

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Between Theory and Phenomena: What are Scientific Models?,osophy of science, and by a discussion of the more recent proposal that models are best thought of as fictions. The final section discusses how a shift in attention, from questions of how science can be formalized to questions of scientific practice, poses a challenge also to traditional accounts of scientific models.

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Scientific Representation and the Uses of Scientific Models,out the latter. Both accounts reflect a growing recognition of the pragmatic dimension of model-based representation. The chapter closes with a discussion of the issue of realism in relation to models, and of possible non-representational uses of models.

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https://doi.org/10.1007/978-3-319-27954-1Mathematical Models in Science; Model-based Representation; Scientific Modelling; Scientific Models and

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How to Do Science with Models978-3-319-27954-1Series ISSN 2211-4548 Series E-ISSN 2211-4556

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Between Theory and Phenomena: What are Scientific Models?, mathematical models, toy models, scale models, etc. This bewildering array of different types of models naturally gives rise to the ontological question ‘What is a model?’, which the present chapter sets out to answer. The genealogy of scientific models can be traced back to the use of mechanical a

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Scientific Representation and the Uses of Scientific Models, scientific representation in general (as explored by Nelson Goodman, Bas van Fraassen, and others) this chapter discusses two specific proposals of how model-based representation comes about: first, R.I.G. Hughes’s ‘DDI account’, according to which the representational capacity of models is due to