Philosophy of Science and the Curse of the Case Study
We can divide the philosophy of science into two projects. Let’s call the first philosophy-directed. Here, we seek to describe, systematize and explain scientific practice, and draw on this to argue for philosophical positions. Science informs philosophy.1 The second could be named science-directed. We aim to clarify, clean-up and unify scientific concepts. Philosophy informs science.2 Both projects lean on generalizations about scientific method, practice, development and so on. Frequently, such generalizations are made in reference to case studies - particular, detailed descriptions of scientific activity. Here, I defend the use of case studies in both philosophy-directed and science-directed contexts.
Unable to display preview. Download preview PDF.
- Craver, C. (2007). Explaining the Brain: Mechanisms and the Mosaic Unity of Neuroscience. Oxford University Press, Clarendon Press.Google Scholar
- Crombie, A. (1981). ‘Philosophical perspectives and shifting interpretations of Galileo’, in Theory change, ancient axiomatics and Galileo’s methodology: proceedings of the 1978 Pisa conference on the history and philosophy of science.Google Scholar
- Devitt, M. (2013). ‘The ‘Linguistic Conception’ of Grammars’, Filozofia Nauki 2.Google Scholar
- Dupré, J. (1993). The Disorder of Things: Metaphysical Foundations of the Disunity of Science. Harvard University Press.Google Scholar
- Godfrey-Smith, Peter (2009). Darwinian Populations and Natural Selection. OUP Oxford.Google Scholar
- Ladyman, J & Ross, D. (2007). Every Thing Must Go: Metaphysics Naturalized. Oxford University Press.Google Scholar
- Lakatos, I. (1970). ‘History of Science and Its Rational Reconstructions’, PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association.Google Scholar
- Levy, A & Currie, A (2014). ‘Model Organisms are Not (Theoretical) Models’, British Journal for the Philosophy of Science (online first) doi: 10.1093/bjps/axt055.Google Scholar
- Nersessian, N. (1999). ‘Model-Based Reasoning in Conceptual Change’, in Magani L., Nersessian N, Thagard P (eds), Model-based reasoning in scientific discovery. Kluwer/ Plenum, New York, pp. 5–22.Google Scholar
- Skyrms, B. (2008). Signals. Evolution, Learning and Information. Oxford: OUP.Google Scholar
- Strevens, M. (2003). Bigger than Chaos: Understanding Complexity through Probability. Harvard University Press.Google Scholar
- Weisberg, M. (2013). Simulation and Similarity: Using Models to Understand the World. Oxford University Press.Google Scholar
- Wimsatt, W. (2007). Re-Engineering Philosophy for Limited Beings: Piecewise Approximations to Reality. Harvard University Press.Google Scholar