The undeniable effectiveness of mathematics in the special sciences
| Abstract | In many of the special sciences, mathematical models are used to provide information about specified target systems. For instance, population models are used in ecology to make predictions about the abundance of real populations of particular organisms. The status of mathematical models, though, is unclear and their use is hotly contested by some practitioners. A common objection levelled against the use of these models is that they ignore all the known, causally-relevant details of the often complex target systems. Indeed, the objection continues, mathematical models, by their very nature, abstract away from what matters and thus cannot be relied upon to provide any useful information about the systems they are supposed to represent. In this paper, I will examine the role of some typical mathematical models in population ecology and elsewhere. I argue that while, in a sense, these models do ignore the causal details, this move can not only be justified, it is necessary. I will argue that idealising away from complicating causal details often gives a clearer view of what really matters. And often what really matters is not the push and shove of base-level causal processes, but higher-level predictions and (non-causal) explanations. | |||||||||
| Keywords | No keywords specified (fix it) | |||||||||
| Categories | No categories specified (fix it) | |||||||||
| 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 | Only published papers are available at libraries |
Similar books and articlesDavid Pineda (2011). Non-Committal Causal Explanations. International Studies in the Philosophy of Science 24 (2):147-170.
Not By Me (1992). Mathematics in the Biological Sciences. International Studies in the Philosophy of Science 6 (3):241 – 248.
Marthe Chandler (1988). Models of Voting Behavior in Survey Research. Synthese 76 (1):25 - 48.
James R. Griesemer & Michael J. Wade (1988). Laboratory Models, Causal Explanation and Group Selection. Biology and Philosophy 3 (1):67-96.
Jay Odenbaugh (2005). Idealized, Inaccurate but Successful: A Pragmatic Approach to Evaluating Models in Theoretical Ecology. Biology and Philosophy 20 (2-3):231-255.
Analytics
Monthly downloads |
Added to index2009-09-05Total downloads23 ( #53,940 of 549,699 )Recent downloads (6 months)2 ( #37,450 of 549,699 )How can I increase my downloads? |
My notes
Discussion
