From: Dave Zachariah <davez@kth.se>

Date: Thu Feb 10 2011 - 13:54:39 EST

Date: Thu Feb 10 2011 - 13:54:39 EST

On 2011-02-10 18:48, Jurriaan Bendien wrote:

*> Sure, you can construct an elegant metaphor and test out the quantitative
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*> implications of the metaphor, but there is no guarantee it captures anything
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*> about reality. A model is not a theory. A model is a likeness, an
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*> isopmorphism, a simplifying analogy for some of the features of the subject
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*> studied. A theory provides an in-depth, comprehensive causal explanation.
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When I wrote 'model' before I didn't mean a formalized model. Instead it

was a carefully chosen analogy, in that theories *model* underlying

causal mechanisms. As such all theories are models of reality.

Some theories are indeed possible to formalize into mathematical or

logical models, and can then improve in-depth, comprehensive

explanations, i.e. reliably infer empirical outcomes. Take Boolean

algebra for instance. Once you have a theory that explains how basic

digital components can perform, or approximately perform, Boolean

operations under certain conditions, the formalism of Boolean algebra

allows for an in-depth, comprehensive explanation of the observed

behaviour of very complicated digital circuits.

Similarly, probability theory allows for the formalization of a few

basic laws in statistical mechanics with remarkably predictive power

based on quite simple assumptions. Again, the formalized model provides

in-depth, comprehensive explanations of the property of gases without

ever requiring knowledge of individual particle trajectories.

In short, any theory that can reliably infer empirical outcomes is a

good model of the underlying causal mechanisms. Whether its uses

mathematical language or not.

//Dave Z

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Received on Thu Feb 10 13:56:03 2011

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