Dear Dog Pile,

All nick ever said was that we have to mind our words, and that when words
like selection and fitness get used in a technical context, the argument
may go astray because of surplus meanings of the constructs being used.  He
would like to add that paying attention to the words (examining the
metaphors) rigorously often has a heuristic value. He even provided a paper
which (he thought) exemplified that principle.   He would never argue
against studying  differences between women who had  3 children survive to
adulthood and women who had, say, none.  But he would be VERY careful what
he called such research.  Some have called Darwinian Psychology.   What is
NOT is evolutionary psychology, because evolutionary psychology was based
on the concept of the Environment of Evolutionary Adaptedness, the idea
that there was a time by (or for) which our current behavioral performances
were designed. Therefore, knowing the conditions of Pleistocene life could
warrant predictions about how human beings would behave today, whether or
not those behaviors actually resulted in greater reproductive success now.
The concept of design, implicit in Cosmides and Tooby's manifesto of
Evolutionary Psycholgoy, has been overlooked by many of their followers,
but it is central to that project.  When eliminated the research becomes
like DES's 2a and 2b ( or not "Tooby")  in that it tells us only some other
features of the winners other than that they won.  Each of these
constitutes a hunch about why they won, of course.  But it relates only
distantly to Darwin's hunch that there is some higher-order property of
sucessful organisms which, if we knew it, could predict their success.

Nick


On Tue, Mar 31, 2026 at 2:16 PM Santafe <[email protected]> wrote:

> Hi EricC
>
> I will drop out of this soon because of time conflicts.  But an edit or
> two below:
>
> > On Mar 31, 2026, at 15:47, Eric Charles <[email protected]>
> wrote:
> >
> > I'll also note that "function" can't do the work on its own to explain
> evolution. We still need to know why some functions are favored by
> selection and others are not. EricS seemed to indicate that we assess "fit"
> by determining if animals are "happy"….
>
> In this case, no.  Exactly not that.  The long tedious first post from me
> was an objection to vague gestures at what “fit” means, using “happy” as an
> example of vagueness.  The aim in the passage was to explain the role of
> Fisher’s supplying specific constructions of summary statistics defined on
> instances of population processes.
>
> Not to say that we have to do things Fisher’s way; I had other comments on
> that question.  Rather, to say that one doesn’t generate a tautology by
> first providing a definition of what quantity you are pulling from data, to
> which you are trying to fit a regression model.
>
> > but the metaphor of "fit" is like a key in a lock. To explain evolution
> you need the matching of form-and-function-to-a-particular-environment.
> That matching *sometimes* increases reproductive success, and *sometimes*
> the traits in question are hereditary.
>
> All the sometimeses and hedges are certainly right.  I didn’t belabor
> them.  But for sure, if one writes regression models, it is because there
> is supposed to be data scatter that the model isn’t trying to account for.
> Also the other comments here and there in the threads about all the things
> that one or another regression model will leave out; where they go in a
> Price equation decomposition, and the question of whether your regression
> model falls apart when some formerly-unconsidered dummy variables are added.
>
>
> I didn’t end up saying as much about flavor text in these threads as I
> guess the main thread would have motivated.  I guess that is because I got
> sidetracked on trying to provide language for an account of what
> geneticists and others are doing, behind the various human-language terms,
> since it wasn’t clear to me that all that was familiar.
>
> > Population genetics combined with field research can be very powerful
> along those lines, but the math of population genetics on its own, floating
> out in the ether, can't do it at all.
>
> Again, yes.  Both of the last two replies to Nick today were meant to say
> something specific about those limitations.
>
> There is _much_ more that can be said.  A regression model at all is, only
> in a _very_ generous widening of the notion of “causation”, a “causal
> model”.  But I have comments littered here and there in the messy posts
> about how other domains in functional biology go after those other forms of
> descriptions.
>
> Anyway, I agree with you; time for me to stop.  I will hope that in there,
> there was some commentary on extant practice that Nick will at some point
> find useful.
>
> Eric
>
>
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-- 
Nicholas S. Thompson
Emeritus Professor of Psychology and Ethology
Clark University
[email protected]
https://wordpress.clarku.edu/nthompson
https://substack.com/@monist
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