Our wise and noble host, Rick, says:
>I have done a little engineering, and a lot of model building and
>statistical data analysis in my career. For many problems, it is extremely
>helpful to break them into parts. But, *good science* would be especially
>attentive to whether this is a satisfactory approximation, whether this is
>a good model, given the system being examined and the objective of the
>examination.
>I believe it would be foolish to stop breaking things into parts, not
>ever do it. We would lose too much progress.
>But, we must learn to see wholes and interconnections and become more wise
>about *when* to break into parts, when this is a satisfactory assumption.
>And, we must *always* be on the look-out for systemic considerations,
>always on the look-out for what we can only see if we look at the whole.
Thanks for reminding us that "for everything there is a season." It is the
very nature of changing paradigms, in Kuhn's sense of the word, that we
rail against what came before as "old" and see our way as "new." In the
process, we throw the baby out with the bath water. The real learning, as
Rick points out, is to know when to apply what tool. The only way to know
that is to know what it is we want to accomplish.
I haven't read Thomas Kuhn's _Structure of Scientific Revolution_ for a
long while, but Peter Vaill recounted for me this summer that Kuhn
stressed that the "old" paradigm was, and continued to be, useful for 95%
(or some high number) of the situations encountered. The difference was
that the other 5% were marginalized in the "old" school, and that 5%
became the center of attention in the "new" school. (Has anyone else read
Kuhn recently? If so, please correct any misinterpretation I might be
unintentionally passing along.)
I don't know what the best and highest use of "taking things apart"
could/should be in the *good science* of OL, but it might be interesting
to consider. Do we ever get in our own way by refusing to dip into our
"old" mechanistic models?
Thanks Rick!
Marilyn Darling
Signet Consulting Group/GKA
mdarling@warren.med.havard.edu
[Host's Note: Just for the record, I think my good friend Marilyn is
pretty wise and noble as well! ...Rick
--mdarling@warren.med.harvard.edu
Learning-org -- An Internet Dialog on Learning Organizations For info: <rkarash@karash.com> -or- <http://world.std.com/~lo/>