Why Represent Causal Relations?
In Alison Gopnik & Laura Schulz (eds.), Causal Learning: Psychology, Philosophy, Computation. Oxford University Press (2007)
| Abstract | Why do we represent the world around us using causal generalizations, rather than, say, purely statistical generalizations? Do causal representations contain useful additional information, or are they merely more efficient for inferential purposes? This paper considers the second kind of answer: it investigates some ways in which causal cognition might aid us not because of its expressive power, but because of its organizational power. Three styles of explanation are considered. The first, building on the work of Reichenbach in "The Direction of Time", points to causal representation as especially efficient for predictive purposes in a world containing certain pervasive patterns of conditional independence. The second, inspired by work of Woodward and others, finds causal representation to be an excellent vehicle for representing all-important relations of manipulability. The third, based in part on my own work, locates the importance of causal cognition in the special role it reserves for information about underlying mechanisms. All three varieties of explanation show promise, but particular emphasis is placed on the third. | |||||||||
| Keywords | No keywords specified (fix it) | |||||||||
| Categories | ||||||||||
| Options |
|
|||||||||
Download options| PhilPapers Archive |
Upload a copy of this paper Check publisher's policy on self-archival Papers currently archived: 5,709 |
| External links |
  Try with proxy. |
| Through your library | Configure |
Similar books and articlesJim Bogen (2005). Regularities and Causality; Generalizations and Causal Explanations. Studies in History and Philosophy of Science Part C 36 (2):397-420.
Frederick Eberhardt (2009). Introduction to the Epistemology of Causation. Philosophy Compass 4 (6):913-925.
Daniel Hausman (1983). Are There Causal Relations Among Dependent Variables? Philosophy of Science 50 (1):58-81.
Paul Audi (2011). Primitive Causal Relations and the Pairing Problem. Ratio 24 (1):1-16.
Clark Glymour (1998). Learning Causes: Psychological Explanations of Causal Explanation. Minds and Machines 8 (1):39-60.
Riccardo Viale (1999). Causal Cognition and Causal Realism. International Studies in the Philosophy of Science 13 (2):151 – 167.
Daniel Murray Hausman (2005). Causal Relata: Tokens, Types, or Variables? Erkenntnis 63 (1):33 - 54.
Analytics
Monthly downloads |
Added to index2010-04-16Total downloads26 ( #47,731 of 550,802 )Recent downloads (6 months)2 ( #37,450 of 550,802 )How can I increase my downloads? |
My notes
Discussion
