David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Synthese 20 (3):308 - 334 (1969)
The distinction between explanation and prediction has received much attention in recent literature, but the equally important distinction between explanation and description (or between prediction and description) remains blurred. This latter distinction is particularly important in the social sciences, where probabilistic models (or theories) often play dual roles as explanatory and descriptive devices. The distinction between explanation (or prediction) and description is explicated in the present paper in terms of information theory. The explanatory (or predictive) power of a probabilistic model is identified with information taken from (or transmitted by) the environment (e.g., the independent, experimentally manipulated variables), while the descriptive power of a model reflects additional information taken from (or transmitted by) the data. Although information is usually transmitted by the data in the process of estimating parameters, it turns out that the number of free parameters is not a reliable index of transmitted information. Thus, the common practice of treating parameters as degrees-of-freedom in testing probabilistic models is questionable. Finally, this information-theoretic analysis of explanation, prediction, and description suggests ways of resolving some recent controversies surrounding the pragmatic aspects of explanation and the so-called structural identity thesis.
|Keywords||No keywords specified (fix it)|
|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
William H. Dray (1979). Laws and Explanation in History. Greenwood Press.
Herbert Feigl & Michael Scriven (eds.) (1956). Minnesota Studies in the Philosophy of Science. , Vol.
Joseph F. Hanna (1968). An Explication of 'Explication'. Philosophy of Science 35 (1):28-44.
Joseph F. Hanna (1966). A New Approach to the Formulation and Testing of Learning Models. Synthese 16 (3-4):344 - 380.
Carl Hempel (1965). Aspects of Scientific Explanation and Other Essays in the Philosophy of Science. The Free Press.
Citations of this work BETA
Joseph F. Hanna (1981). Single Case Propensities and the Explanation of Particular Events. Synthese 48 (3):409 - 436.
Similar books and articles
Nicholas Rescher (1963). Discrete State Systems, Markov Chains, and Problems in the Theory of Scientific Explanation and Prediction. Philosophy of Science 30 (4):325-345.
Joseph F. Hanna (1978). On Transmitted Information as a Measure of Explanatory Power. Philosophy of Science 45 (4):531-562.
Heather E. Douglas (2009). Reintroducing Prediction to Explanation. Philosophy of Science 76 (4):444-463.
Kristin Andrews (2003). Knowing Mental States: The Asymmetry of Psychological Prediction and Explanation. In Quentin Smith & Aleksandar Jokic (eds.), Consciousness: New Philosophical Perspectives. Oxford University Press.
James Woodward (1987). On an Information-Theoretic Model of Explanation. Philosophy of Science 54 (1):21-44.
Jon Williamson (2011). Models for Prediction, Explanation and Control: Recursive Bayesian Networks. Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 26 (70):5-33.
Rollin W. Workman (1964). What Makes an Explanation. Philosophy of Science 31 (3):241-254.
David Michael Kaplan (2011). Explanation and Description in Computational Neuroscience. Synthese 183 (3):339-373.
Added to index2009-01-28
Total downloads80 ( #17,873 of 1,099,863 )
Recent downloads (6 months)4 ( #90,276 of 1,099,863 )
How can I increase my downloads?