1. INCOSE International Workshop - January 27, 2014
FOUNDATION FOR
THE ADVANCEMENT
OF SOCIAL THEORY
Analyzing our theories & models: A "science of conceptual systems" approach
Steven E. Wallis, Ph.D.
Director, FAST
Adjunct Faculty, Capella University
Fulbright Specialist Roster
INCOSE International Workshop - January 27, 2014

2. Today, we’ll cover…
Introduction – A systems approach to theories and models
Background
Conceptual, Historical, Philosophical, Empirical
Integrative Propositional Analysis (IPA)
Methods, Examples, Pop Quiz!
IPA – Uses
Informing Research, Informing Collaboration, charts and graphs
IPA – Limitations
Hands On – Analysis & Integration
Possible Future Projects
Conversation – wide open!

3. The Old and the New (at least) FIVE structures of logic
Science One
Science Two
Toulmin logic of claim, warrant, support, proof…
Linear / Atomistic
Striving to clarify correspondence between concept & reality
Working to separate truth from non-truth
Competing
(at least) FIVE structures of logic
Complexity & systems
Striving to clarify coherence between concepts in the model
Working to integrate concepts
Collaborating

4. Science of Conceptual Systems
In the systems sciences, we have spent considerable time and effort studying:
physical systems
chemical systems
computer systems
biological systems
social systems
We have placed comparatively little effort
in the study of conceptual systems

5. Some Words for Conceptual Systems
Lens
Map
Model
Diagram
Narrative
Schema
Law
Theory
Ethics
Policy
Mind map
Assumptions
Conceptual map
Strategic Plan
DEFINITION:
A conceptual system is a set of interrelated propositions.
(they are all useful for understanding and engaging the world)

6. One Simple Assumption
If we live in a world of systems, that world would be best described by theories that are systemic

7. Importantly
If… we can quantify the systemicity of our theoretical models “on paper” Then… we can predict which ones are more likely to be more effective in practical application

8. Some Related Research Through History
1955 –Kelly “Personal Construct” 1955 – Cronbach & Meehl “Nomological Network” 1961 – Harvey, et al. “Integrative Complexity” 1967 – Schroder, et al. “Paragraph Completion Test” 1976 – Axelrod “Causal Mapping” 1976 – Suedfeld & Rank Revolutionary Leaders 1982 – Raphael Forecasting Crisis 2010 – Curseu, et al. Learners and Testing Wallis “Propositional Analysis”

9. Atomistic Difficulties of the Purely Empirical A
is real / true / important

10. Difficulties of the Purely Empirical
Linear
More A
More B
More C

11. Difficulties of the Purely Empirical
Tautology
More A
More C
More B

12. Difficulties of the Purely Empirical
Branching
More A
More B
More C

13. Solution to some Difficulties of the Purely Empirical
Concatenated
More A
More B
More C

14. Concatenated structure relates to:
Philosophical Base
Concatenated structure relates to:
Dual description
Holon
Dialectic
Multiple variables
Partial Cause

15. This leads to 2 (or so) Key Guiding Ideas
1 - Nothing can be deeply understood except by its effects on other things (so, we privilege causal relationships) 2 – Things are better understood through dual description, Emergence, Holons, Dialectic, Partial Causes/partial Results, Multiple Independent Variables (so, we privilege concatenated structures) 2-1/2 - ‘simple’ complexity also plays a role…

16. Integrative Propositional Analysis (IPA)
Identify propositions within one or more conceptual systems (models, etc.).
Diagram those propositions with one box for each concept and arrows indicating directions of causal effects
Find linkages between causal concepts and resultant concepts between all propositions
Identify the total number of concepts
Identify concatenated concepts
Divide the number of concatenated concepts by the total number of concepts in the model

17. IPA – Step 1 Identify propositions within one or more models
For Example:
More Synergy will lead to more stability.

18. IPA – Step 2 Diagram propositions
one box for each concept
arrows indicating directions of causal effects
Proposition #1
“Concept A” More Synergy
“Concept B” More Stability
Causes

19. IPA – Step 3. Find linkages between causal
IPA – Step 3 Find linkages between causal concepts and resultant concepts
P #1
P #2 A
Causes B B C
Causes OR A B C
Causes
Causes

20. IPA – Step 4 Identify the total number of concepts
Causes
Causes
Total Number of Concepts = 3

21. IPA – Step 5 Identify concatenated conceptsB C
Causes
Causes
Number of Concatenated Concepts = 1

22. IPA – Step 6. Divide the number of. concatenated concepts by the
IPA – Step 6 Divide the number of concatenated concepts by the total number of concepts A B C
Causes
Causes
Number of Concatenated Concepts = 1
Total Number of Concepts = 3
Systemicity / Robustness = 0.33
(result of one divided by three)

23. Pop Quiz. Example from Complex Adaptive Systems:
Pop Quiz!!! Example from Complex Adaptive Systems: Three Simple Propositions
CASs that are closer to the edge of chaos (EOC) will experience more self-organization.
Members (agents) self-organize toward more stable patterns of activity
The more that agents follow rules and the more they interact, the more they will improve on their behavior.

24. Pop-quiz #1 … Closer the CAS is to the EOC More self-organization
Causes
Total number of concepts =
Number of concatenated concepts =
Systemicity / Robustness =
(number of concatenated concepts
divided by total number of concepts)

25. Pop-quiz #2 … More stable patterns of activity More self-organization
More Agents interacting
Causes
Causes
Total number of concepts =
Number of concatenated concepts =
Systemicity / Robustness =
(number of concatenated concepts
divided by total number of concepts)

26. Pop-quiz #3 … More interactions More improved behavior
Causes
More improved behavior
More rule-following
Causes
Total number of concepts =
Number of concatenated concepts =
Systemicity / Robustness =
(number of concatenated concepts
divided by total number of concepts)

27. Systemicity / Robustness
Comparing Models
Model
Systemicity / Robustness
Complexity #1
S/R = 0.0
C = 2 #2
C = 3 #3
S/R = 0.33

28. Integrating Three models into One
Closer the CAS is to the EOC
Causes
More self-organization
More stable patterns of activity
Causes
More interactions
Causes
Causes
More improved behavior
More rule-following
Causes
Total number of concepts =
Number of concatenated concepts =
Systemicity / Robustness =
(number of concatenated concepts
divided by total number of concepts)

29. Integrated Models are Improved Because…
More Complex
(greater breadth)
More Systemic
(more likely to be effective in a systemic world)
Clarifies opportunities for research
Suggests directions for practice

30. Soft / Fuzzy Fragmented
General Purpose…
From:
Soft / Fuzzy Fragmented
Towards: Harder Reliable Useful

31. Uses: Finding Evolution in Systemicity
Systemicity / Robustness

32. Uses: Finding Evolution in Complexity

33. Sample: Complexity of Theories of Conflict from Sociology
1950s & 1960s
Slowly declining complexity – may disappear circa 2044?

34. Sample: Systemicity of Theories of Conflict from Sociology
1950s & 1960s
Slow Decline – Wrong Direction!

35. Uses: Creating a Snapshot (Theories of Entrepreneurship)
Systemicity / Robustness
Lower C, Higher R
Higher C, Higher R
0.50
Lower C, Medium R
Higher C, Medium R
0.45
0.40
Integrated Theory
0.35
0.30
0.25
Robustness
Lower C, Lower R
Higher C, Lower R
0.20
0.15
0.10
0.05
0.00
Complexity 10 20 30 40 50 60
Complexity

36. Uses: Predicting success (Two Comparable Economic Policies of the 2012 Election Cycle)
Republican
C = 6
R = 0
Democratic
C = 15
R = 0.13

37. Uses: Clarifying Research Needs
Poor understanding
Closer the CAS is to the EOC
Causes
More self-organization
More stable patterns of activity
Causes
Poor
understanding
Poor
understanding
Poor
understanding
More interactions
Causes
Causes
More improved behavior
More rule-following
Causes
Good understanding
Good understanding

38. Uses: Evaluating Models for Research
From: Ong, Lai & Wang – Factors affecting Engineers’ Acceptance of Asynchronous E-learning systems in High-Tech Companies

39. Uses: Identifying “core” and “belt” of a body of theory (suggests areas of theory that are better known (core) or need more research (belt)
“Core” concepts are those with MORE connections
“Belt” concepts are those with FEWER connections

40. Possible way to “define” what are the “same”
Causes
Causes
Causes
Causes ? ??
Causes
Causes
Causes
Causes C D C D

41. Uses: Evaluating Strategic Plans
3-1. More leveraging of financial resources
3-2. More leverage of board and staff commitment
3-6. More work by the OD network
3-4. more maximization of results
3-5. More effective and efficient infrastructure
3-7. More best governance practices
3-9. More clear roles and responsibilities
3-8. More leadership succession planning
3-3. More leveraging of volunteer time
Uses: Evaluating Strategic Plans
1-2. More design and development of healthy human systems (individuals, teams, organizations, communities)
1-4. More exchange of ideas and best practices
1-1. More work of ODNET membership
1-3. More training, networking, mentoring, employment opporuttunities by ODNET
C = 21
R = 0.14
1- 5. More segmentation of members (by experience, industry, professional specialty)
1-6. Better support of needs of each segment
4-1. Better ability to manage operations
4-3. Longer survival and more growth of ODNET
4-2. More financial reserves
2-1. More building a culture in the OD Network (of inclusion, values and creatively uses its diversity inviting us all to participate in and lead this field and the work of the Network)
2-3. More building of new leaders in the work and the world
2-2. more economic success for ODNET members and stakeholders

42. Uses: Some Implications for Collaboration
Larger models require more collaboration (each researcher takes a piece – linked by causal relationships)

43. Yes… another 2 Key Ideas
In addition to external correspondence (reality-to-concept fit), good theory requires Internal coherence (concept-to-concept fit). At this level of abstraction, theory can be used to bridge disciplines and communities of practice.

44. Some Opportunities and Limitations
IPA is an emerging methodology – research suggests benefits, track record is not extensive
Integrative Complexity is a related methodology – track record goes back to the Eighties
IPA may be used as process for accelerating the process of integration
Clear “prejudices” in favor of causal relationships
(others may also be valuable)
Clear “prejudices” in favor of concatenated concepts

45. A few things to keep in mind during the EXERCISE...
Use “scalar” concepts
Fewer assumptions is better – keep it “on the page”
Look for OVERLAPS of concepts – Ask what concepts are legitimately the “same thing?”
Look for CAUSAL – Ask what causal relationships may be legitimately inferred?
It IS OK to reject data as non-valid (send it back to the author for clarification and/or more research
ASK if it is legitimate to shift a concept up/down on some scale of abstraction to make it “fit” with another concept?

46. A few Potential Projects using IPA
Choose the best theories for teaching (most systemic)
Create a “Periodic Table” of systems theories
Explore the “blank quadrant” – where are the theories that are highly complex AND highly systemic?
Identify “core” (more structured) & “belt” (less structure – more in need of research) for bodies of theory
Choose and body of systems theories to analyze trends over time (are they getting simpler? Becoming more systemic?). May also evaluate journals to see if ranking reflect systemicity
Categorize BOK - By topic, complexity, systemicity
Analyze wider range of theories (to include more from physics and other fields)
Look at TOEs (try not to step on them?)
Identify “web” of interconnected theories
Like genome mapping – conduct an accelerated analysis (in parallel with the SoSPT working group
Look for larger logic structures – what other patterns might be found?
“Same Thing” studies – where are the overlaps that are causing confusion (due to re-naming)?

47. To Conclude…
Using a Science of Conceptual Systems perspective IPA provides an innovative and rigorous tool for:
Analyzing theories based on Systemicity and Complexity
Integrating theories
Moving the field of systems thinking from soft to solid
Bridging disciplines, synthesizing knowledge
Supporting collaborations in research and practice to achieve more effective & useful results

48. MANY THANKS I look forward to collaborating with you
FOUNDATION FOR
THE ADVANCEMENT
OF SOCIAL THEORY
MANY THANKS I look forward to collaborating with you
Steven E. Wallis, Ph.D.
Director, Foundation for the Advancement of Social Theory
Adjunct Faculty, Capella University
Fulbright Specialist Roster