Comments on Chapter 9: Subdynamics in Knowledge-based Systems

June 15 2022

Core question

• How are meaning and information processing related, and how are they re-combined in the shaping and self-organization of discursive knowledge?
• Can they be modeled and measured in ways that help understand and illuminate the system for decisionmakers?

Subdynamics…

• Systems dynamics are structural: they operate in terms of variety and selection mechanisms
• Meaning of science and technology in society
• Shared meaning creates structures
• Micro-operation of the social system*

Not very helpful to policymaker…

Need to move towards operations that are connective or have the ability to create systems (Luhmann)

Model the possibility of social order …

May require self-organization

​

​

Order and policy

• Luhmann: “How is Social Order Possible?”
• Within any social order, how do we create knowledge
• Retain it?
• Disseminate and use it?
• Are there structures in social order that are more amenable to creating new knowledge, and if yes, what are they?

Power of knowledge, objectified…

• Each of us (Ego) expects the other (Alter) to entertain expectations as we entertain them ourselves… (p.7)
• This is the “double contingency”
• Micro-operation of social system
• The knowledge system operates, as society does, outside the individual
• Double contingency is the auto—catalyst of social processes

Triple Contingency

• Loet’s goal: create simulation of communication system
• To do so, must create equations
• …And a base case
• Loet’s addition to DC: “Triple Contingency”
• Serves as a base case (non-zero)
• Enables generation of redundancies
• Do we want to get to macro-structures…? must have a way to incorporate micro-structures into model

“Triangles symbolize the act of moving forward in life and becoming the harbinger of change you seek”

Complex systems theory helps here

• If we are concerned about innovation within the science and technology system, then we are interested in constructedness
• Radical constructedness (Knorr-Cetina)
• The agent is not the focus
• Purposes/motivations of the researcher is not focus
• At first, the person creates the network, then the network constrains the person
• Any construct needs to account for self-organization (p. 188-189)

• Leads us to Luhmann, who incorporated the idea of open systems within communications processes, borrowed from biology, to explain why entropy does not occur and why order is created instead… (p. 28)

​

• Recently showed that open countries have stronger scientific impact (Nature, 2018)

Rules of Complex Systems

• H.A. Simon’s observations about systems in attempt to define complexity outside of specific discipline
• Begin with simple rules
• Non-linearity (whole is greater than the sum of parts)
• Tend towards hierarchy, or structured subsystems
• Relations among sub-systems are possible
• Distinguish among and within subsystems
• ‘Hierarchy’ can relate to degrees of freedom

​

How Does System Constrain Action?

• We know that international collaboration is perhaps the ‘freest’ level of scientific communication
• Growing rapidly
• Least constrained by institutions
• Almost completely self-organizing
• No global ministry of science is ordering it
• Gets lots of attention, but how does it organize?

Preferential attachment mechanism

• Researchers link to one another to gain access to reputation, resources, visibility, and complementary capabilities
• Can be studied as network
• Highly connected nodes increase their connectivity faster than their less connected peers
• P(k) ∼ k-γ
• Scale-free distribution is seen at international level
• Small worlds are highly efficient at localized exchanges of information

Wagner, C. S., & Leydesdorff, L. (2005). Network structure, self-organization, and the growth of international collaboration in science. Research policy, 34(10), 1608-1618.

Self-organized criticality

• Examined aggregated citation links between (n) journals seeking dynamics
• The knowledge base can be considered as a large set of meta-stable constructs which are continuously disturbed by new knowledge claims bringing also new citation relations
• While effects are local, meta-stable regions endure

​

Leydesdorff, L., Wagner, C. S., & Bornmann, L. (2018). Discontinuities in citation relations among journals: Self-organized criticality as a model of scientific revolutions and change. Scientometrics, 116(1), 623-644.

Questions

• If historically observable networks serve as retention mechanisms…but…we want innovation, novelty…can we better structure networks for variety?
• Can triple contingency help here?
• Have we gained insight into effective environments for recombining knowledge?

​