Dear Colleagues - I have combined my responses to a number of
comments (from Ted, Stan and Loet) in one email. My comments are in
red and the comments of the others that I am commenting on are in blue.
Hi Ted - I did not understand why you clain Kauffman's approach is
algrebraic.
At the highest level, I think, there's a decision each of us has to
make about the nature of the abstraction space we want to work in.
Kauffman is famously on record as believing that the preferred space
is algebraic. He goes further in stating that it is the ONLY space,
all others illusory, or less fundamental. Without burdening you with
that rather indefensible weight, its clear to me that what you have
presented is clearly in this camp.
Hi Stan - once again I enjoyed your remarks amplifying your original
comment. I would like to add that science only deals with formal
cause and not final cause. Final cause is for philosophers, social
critics and theologians.
Bob said:
Hi Stan - interesting ideas - I resonate with the thought that the
meaning of info is associated with Aritostle's final cause -
cheers Bob
Here I follow up with an extract from a text I am working on at present,
just to amplify this a bit more:
Finally, what is the justification for considering meaning
generally to be
associated to finality? Why not formal causes as well? Final cause
is the
'why' of events, while formal causes carry the 'how' and 'where',
material
causes the local 'readiness', and efficient cause the 'when' (Salthe,
2005). It seems clear when choosing among these, that the meaning
(significance, purport, import, aim -- Webster's New Collegiate
Dictionary)
of an event must be assigned to its final causes. Formal and material
causes are merely enabling, while efficient cause only forces or
triggers.
The example of a New Yorker cartoon captures some of my meaning
here. Two
Aliens are standing outside of their spaceship, which has apparently
landed
on Earth, as we see spruce trees burning all around them in a fire
that we
infer was triggered by their landing. One them says: I know what
caused it
-- there's oxygen on this planet. If we think that is amusing, we know
implicitly why formality cannot carry the meaning of an event. In
natural
science formality has been used to model the structure of an
investigated
system, and so is not suited to carrying its teleo tendencies as well.
Formality marks what will happen where, but not also 'why' it
happens. The
causal approach itself is required if we are trying to extend semiosis
pansemiotically to nature in general. Natural science discourse is built
around causality, and so attempts to import meaning into it requires
it to
be assimilated to causation.
Loet - if your claim is true then how do you explain that a random
soup of organic chemicals have more Shannon info than an equal number
of organic chemicals organized as a living cell where knowledge of
some chemicals automatically implies the presence of others and hence
have less surprise than those of the soup of random organic
chemicals? - Bob
On 7-Oct-07, at 6:47 AM, Loet Leydesdorff wrote:
Dear Bob and colleagues,
Although I know that this comment was made in responding to another
comment, let me react here because I think that this is not correct:
The point I am making is that organization is a form of
information which Shannon theory does not recognize.
Shannon's theory is a mathematical theory which can be used in an
application context (e.g., biology, electrical engineering) as a
methodology. This has been called entropy statistics or, for
example, statistical decomposition analysis (Theil, 1972). The
strong methodology which it provides may enable us to answer
theoretical questions in the field of application.
An organization at this level of abstraction can be considered as a
network of relations and thus be represented as a matrix. (Network
analysis operates on matrices.) A matrix can be considered as a two-
dimensional probability distribution which contains an uncertainty.
This uncertainty can be expressed in terms of bits of information.
Similarly, for all the submatrices (e.g., components and cliques)
or for any of the row or column vectors. Thus, one can recognize
and study organization using Shannon entropy-measures.
The results, of course, have still to be appreciated in the
substantive domain of application, but they can be informative to
the extent of being counter-intuitive.
Best wishes,
Loet
Loet Leydesdorff
Amsterdam School of Communications Research (ASCoR)
Kloveniersburgwal 48, 1012 CX Amsterdam
Tel.: +31-20- 525 6598; fax: +31-20- 525 3681
[EMAIL PROTECTED] ; http://www.leydesdorff.net/
Now available: The Knowledge-Based Economy: Modeled, Measured,
Simulated. 385 pp.; US$ 18.95
The Self-Organization of the Knowledge-Based Society; The Challenge
of Scientometrics
