  Shannon's classical information theory uses probability theory to analyze
channels as mechanisms for information flow. In this paper, we generalize
results of Martin, Allwein and Moskowitz for binary channels to show how some
more modern tools - probabilistic monads and domain theory in particular - can
be used to model classical channels. As initiated Martin, et al., the point of
departure is to consider the family of channels with fixed inputs and outputs,
rather than trying to analyze channels one at a time. The results show that
domain theory has a role to play in the capacity of channels; in particular,
the (n x n)-stochastic matrices, which are the classical channels having the
same sized input as output, admit a quotient compact ordered space which is a
domain, and the capacity map factors through this quotient via a
Scott-continuous map that measures the quotient domain. We also comment on how
some of our results relate to recent discoveries about quantum channels and
free affine monoids.
