Epistemic representation beyond models: thought experiments, specimens, and pictures

Abstract

Scientists often make use of epistemic representations in order to perform investigations about the real world. So far, philosophers of science interested in epistemic representation of this sort have mostly focused on scientific models. In this thesis, I argue that there are other interesting instances of representation besides models: thought experiments, experimental organisms, and mechanically-produced pictures. These represent portions of the world in the same way as models do, if the concept of epistemic representation is properly understood. In Chapter 1, I introduce and develop the idea that a system functions as an epistemic representation of a designated target system insofar as it is interpreted as a symbol that both possesses and highlights some properties that are then to be imputed to that target system via a proper de-idealising function. In the main body of the thesis, I analyse the above-mentioned types of representations and argue that they function as representations in the same way as scientific models. Chapter 2 discusses the use of thought experiments in physics, with particular focus on Galileo’s thought experiment that illustrates the principle of inertia. Chapter 3 focuses on experimental organism research in biology, with specific attention to the Drosophila melanogaster. Finally, Chapter 4 is about the epistemic use of mechanically produced pictures with the picture of a black hole as the primary case study. In each chapter, I further show that by studying these types of representation through the lens of the account developed in Chapter 1, one can (dis)solve specific issues about thought experiments, model organisms, and pictures respectively. In Chapter 5, I further defend my proposal from scepticism about the concept of representation and its application to these different cases. Chapter 6 concludes the thesis by illustrating the most general implications of my analysis and proposing routes for future enquiry.

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Lorenzo Sartori
London School of Economics

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