This text is about explanation in
practice. Thus while the philosophical
literature re scientific realism is rather vast,
the bulk of that literature is too technical to be
a heuristic for everyday actions. To
accommodate this emphasis on the everyday, we
approach scientific realism from a constrained
pragmatic perspective. There are, for
example, important differences between the ways in
which scientists and practitioners construct and
use explanations. The scientist aims to use
established explanations as a starting point for
the production of further, true
explanations. In practice, the scientist
makes use of explanations as the basis on which to
make predictions. Successful predictions, in
turn, help to generate the theories which then
become the basis for further explanations.
The practitioner's aims are different --
relying on explanations only insofar as they are
useful. For the scientific realist, an
explanation is good if it is accurate. Pragmatic
success is, at best, a secondary desideratum.
Pragmatic scientific realism relies on the
fundamental beliefs that reality is independent of
the observer, that truth is foremost, that science
offers a means by which we can gain access to
better representations of the underlying reality
or truth and that it is foundational to act as if
those representations are themselves
true. Explanations in the form of
"how" are thus revelatory of truth.
Explanations in the form of "why" are truth
revealing to the extent that they offer a "fit"
with respect to the previously revealed
order. Measures of degree of fit have
explanatory meaning. Both how and why then can be
used as the basis for prediction. Reliable
prediction becomes the guide for action.
But a caution is in order. This pragmatic
scientific realism works well in a world focused
on regularities rather than individuals and
defines "truth" often in the form of
indexicals. Pragmatic scientific realism has
been shown to work well in the Science 1
domains. Science 2 by contrast offers
challenges to this perspective.