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Loet:

You are mixing, in my opinion, a realist and a constructivist discourse
about systems. From my perspective, the systems remain constructs. The
hypotheses are disturbed by the observations. Thus, it becomes important
to
develop measures when the variation exhibits more systemness or not.
However, this presumes specification of the system(s) of reference. I am
not
intending to set boundaries. We can quietly leave that to management and
politics.
 
Ryan:

I'll try to summarize (not too succinctly) what I think and what I think
I said:

15 Assertions about the Philosophy and Future of SNA

1. Networks are a form of classification method. Membership is
constructed (i.e. perspective-based). There are no natural networks
just as philosophers have found no natural classifications.

1A. The primary purpose of SNA is to create discrete bounded sets.

2. The underlying premises of SNA in establishing sets are dichotomies
between linkage and actor and between actor and context. These
dichotomies were theorized to enable discrete mathematics to be applied
to networks in the form of measurements. They also followed cybernetic
models that simplified computing networks.

3. Measures (e.g. centeredness) are expressions of relationships
(ontologies) made from a given perspective. Because the underlying data
is constructed, the measures are constructed. This is not an assertion
that they are useless--only that they are cultural.

4. Stability and consistency are the primary problems of network
membership because the hoped-for structure is non-existent. Systems are
not predictable and membership in classification schemes is problematic.


5. Assertions about lasting stability refer to "structure." For
structure to exist there would need to be stable classifications.

6. The problems experienced with stability of membership (or
relationships) are quite similar to those previously found in artificial
intelligence.

7. The standard response to such problems (hoping to maintain discrete
sets) would be probabilistic memberships.

8. The response after this one is typically to look into how cultures
evolve (e.g. the Boyd and Richardson/Bowles/Bienhocker, Gunderson and
Hollingesque Panarchy and other Santa Fe sorts of works). The result is
a turn to "complexity studies" where cycles and long-term trends are
sought in the evolution of "structures."

9. Increasingly there is a crisis between stability (structure) and
change (innovation) where innovation is the definition of all factors
acting as solvents to social stability.

10. This crisis seems to evolve in the same sorts of cultural relativism
problems and clash of structure issues that have been under
consideration in anthropology for a generation--resulting in innovators
like Bruno Latour, Saskia Sassen and Aihwa Ong amongst others. It also
seems to spawn structural reactionaries like Samuel Huntington and fence
sitters like Francis Fukuyama.

11. SNA will tend to move toward network dynamics and deep
classification description in response. Within 3 years, publications of
static social network research will be considered passé.

12. New forms of technology analogous to, say, Feynman diagrams, will
emerge that describe the relationships of actants to contexts.

13. Qualitative methods will enjoy a period of notice as means of thick
description in networks are explored. These will, as usual, be more
broadly rejected as unworkably complex and subjective but they will
create anxieties and awareness about data sources and constructiveness.

14. The future of business SNA will be a race toward mass customization
of the evolutionary properties of specific networks--e.g. how a
consumer's decisions evolve--based on aging children, personal age, life
situation, etc. Or, how a medical history evolves. The key will be to
model people based not on their simple past decisions but how their past
decisions changed...and when...the goal (as always) will be to more
comprehensively anticipate needs JIT a la TiVo.

            

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