David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
Learn more about PhilPapers
Philosophical Studies 160 (1):1-29 (2012)
Critics of contemporary metaphysics argue that it attempts to do the hard work of science from the ease of the armchair. Physics, not metaphysics, tells us about the fundamental facts of the world, and empirical psychology is best placed to reveal the content of our concepts about the world. Exploring and understanding the world through metaphysical reflection is obsolete. In this paper, I will show why this critique of metaphysics fails, arguing that metaphysical methods used to make claims about the world are similar to scientific methods used to make claims about the world, but that the subjects of metaphysics are not the subjects of science. Those who argue that metaphysics uses a problematic methodology to make claims about subjects better covered by natural science get the situation exactly the wrong way around: metaphysics has a distinctive subject matter, not a distinctive methodology. The questions metaphysicians address are different from those of scientists, but the methods employed to develop and select theories are similar. In the first section of the paper, I will describe the sort of subject matter that metaphysics tends to engage with. In the second section of the paper, I will show how metaphysical theories are classes of models and discuss the roles of experience, common sense and thought experiments in the construction and evaluation of such models. Finally, in the last section I will discuss the way these methodological points help us to understand the metaphysical project. Getting the right account of the metaphysical method allows us to better understand the relationship between science and metaphysics, to explain why doing metaphysics successfully involves having a range of different theories, to understand the role of thought experiments involving fictional worlds, and to situate metaphysical realism in a scientifically realist context
|Keywords||Metaphysics Methodology Science Models Inference to the best explanation Intuitions Common sense Kant Theories Empirical equivalence Simplicity Theoretical virtues Explanation|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
Timothy Williamson (2007). The Philosophy of Philosophy. Blackwell Pub..
James Ladyman (2007). Every Thing Must Go: Metaphysics Naturalized. Oxford University Press.
Michael Strevens (2008). Depth: An Account of Scientific Explanation. Harvard University Press.
Tim Maudlin (2007). The Metaphysics Within Physics. Oxford University Press.
David Lewis (1973). Causation. Journal of Philosophy 70 (17):556-567.
Citations of this work BETA
David Rose (forthcoming). Folk Intuitions of Actual Causation: A Two-Pronged Debunking Explanation. Philosophical Studies:1-39.
L. A. Paul (2012). Building the World From its Fundamental Constituents. Philosophical Studies 158 (2):221-256.
Barry Loewer (2012). Two Accounts of Laws and Time. Philosophical Studies 160 (1):115-137.
James Andow (2015). Expecting Moral Philosophers to Be Reliable. Dialectica 69 (2):205-220.
David Rose (2015). Persistence Through Function Preservation. Synthese 192 (1):97-146.
Similar books and articles
C. L. Hardin & W. J. Hardin (2006). A Tale of Hoffman. Consciousness and Cognition 15 (1):46-47.
Richard M. Shiffrin (2010). Perspectives on Modeling in Cognitive Science. Topics in Cognitive Science 2 (4):736-750.
R. Eric O'Connor (1938). The Handmaiden of the Sciences. Thought: A Journal of Philosophy 13 (3):501-502.
Robert L. Ashenhurst (1996). Ontological Aspects of Information Modeling. Minds and Machines 6 (3):287-394.
Laurence Thomas (2012). Self‐Deception as the Handmaiden of Evil. Midwest Studies in Philosophy 36 (1):53-61.
Patrick Grim & Nicholas Rescher (2013). How Modeling Can Go Wrong. Philosophy and Technology 26 (1):75-80.
Norman J. Wells (1998). Descartes and Suárez on Secondary Qualities a Tale of Two Readings. Review of Metaphysics 51 (3):565 - 604.
Rasmus Grønfeldt Winther (2012). Mathematical Modeling in Biology: Philosophy and Pragmatics. Frontiers in Plant Evolution and Development 2012:1-3.
Ron Sun (2008). Introduction to Computational Cognitive Modeling. In The Cambridge Handbook of Computational Psychology. Cambridge University Press 3--19.
Timothy R. Colburn (1998). Information Modeling Aspects of Software Development. Minds and Machines 8 (3):375-393.
Arthur M. Jacobs & Jonathan Grainger (1999). Modeling a Theory Without a Model Theory, or, Computational Modeling “After Feyerabend”. Behavioral and Brain Sciences 22 (1):46-47.
Wesley Cooper (2008). An Eldritch Tale. Philo 11 (2):133-144.
Added to index2012-04-27
Total downloads197 ( #17,895 of 1,939,061 )
Recent downloads (6 months)24 ( #20,336 of 1,939,061 )
How can I increase my downloads?