The Radical New Reality of Systems Science
Our Next
World View
Netology
A Network Perspective Reveals the Emergent Wholeness of Phenomena
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Systems science enables us to perceive things and events as patterns of networked relationships
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These can be static, dynamic, predictable, or unpredictably variable yet characteristically self-similar
- As networks, parts and events appear 'constellated' as as inextricably connected, integrated wholes
- these wholes are further understood and identified by how they are networked into external contexts and systems
- seen as networks, no thing or event is simply 'one thing,' from atoms to persons phenomena are 'complexes'
- Network vision constellates parts, their properties or effects, actions and interactions, into identifying relationships
- Those relationships can involve one-way or recursive feedback influence between parts
- they can produce deterministic causation or interdependently emergent effects and properties
- We cannot know 'how phenomena happen' without examining those relationships
- collectively these relationships charcteristically identify
- CAS are emergent thus unpredictably variable dynamic networks that can only be anticipated characteristically
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- Even the dependently deterministic relationships of static objects can be seen as revealing an emergent whole
- ​Things can be engaged as 'constellations' of relationships that constitute something 'more than their parts'
- These have internal and external aspects -- as relationships between parts, then these and their environments
- Thus the 'identity' of any thing or event is relative to an 'extended network' of origins, contexts, and functions
- ​Distinguishing static, repeating, and variably characteristic networks reveals emergent ordering and agency
- That view shows us how most of the order in and around us arises from emergent interdependencies
- Smaller scale systems become networked into meta-scale systems like ecologies and societies
- But these integrated wholes emerge from conflicting and turbulent internal relationships​
- As adaptive systems are unpredictably variable, we can only anticipate them in terms of their characteristic traits
- So 'seeing networks' leads to an 'archetypal understanding' of type, origins, function, and behavioral character
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Network Science and Perceiving Systems as 'Relational Regimes'
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Network Structure and Connectivity: Network science is a fundamental aspect of overall systems science. Study of computational systems has facilitated modeling phenomena as networks of connected parts and how these influence each other to produce larger scale effects. How parts of phenomena are connected and influence flows between them can be represented as abstract diagrams. It is in this manner that we can 'see' things, events, and discrete systems as "structured" networks having "connective" relationships. This perspective provides some basic concepts for how parts are connected and that gives indications of how influence might flow between those parts.
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When we apply this perspective to 'real world' systems in nature and society, it becomes evident that most systems are configured with multiple 'loops' of connection between parts, as in the "mesh" and "fully connected" models shown above. These more fully 'constellated' modes of "connectivity" between parts promote more complex systems with interactively interdependent, recursive feedback network relationships. That type of connectivity and feedback flow is more likely to produce unpredictably emergent self-organization. So we must think in terms of both how a network is structured by connections and how influence and feedback circulate across those connections.
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System Networks as Static versus Dynamic Relational Regimes:
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--Networks as 'Bounded' Constellations of Relationships Among Parts that Reveal 'Integrated Wholes'
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--Things and Events as Networks of Identifying Patterns of Relationships
--Networks Static and Dynamic, Dependent and Interdependent, Hierarchical and Heterarchical
​no change, sequential process, reiterative, variable yet characteristically self-similar
dependently determined or interdependently emergent
categorically definitive or archetypally characteristic
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--Networks as Internal and External Sets of Identifying Relationships
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--Networks of Networks of Networks
nested nets among overlapping boundaries
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