The Radical New Reality of Systems Science

 

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'Network Vision' Beyond the Science

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Non-Technical Aspects of a Generalized Perspective for Perceiving Network Dynamics

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Thinking Relationally as 'Dynamically Constellating Consciousness'

'Perceiving'  phenomena as 'relational networks' involves awareness of what 'goes on' between aspects or 'parts' things, events, and systems. In one sense, that means perceiving in terms of 'parts' that are 'constellated' into a network by the ways these act upon or interact with each other. However, if the aim is to 'see' phenomena as 'fields relationships,' rather than parts, one's focus must be upon the 'wholeness' of those relationships. In the case of complex adaptive systems, that means attempting to perceive the 'wholeness' of a dynamically variable, never exactly repeating, though typically "self-similar' over time -- yet sometimes dramatically changing 'field of interacting relationships. Thus, in one regard, thinking or representing 'relationally' means 'seeing' sets of actions and interactions, while in another sense, it means 'seeing' the irregular regularity and transformative capacities the 'characterize' a complex adaptive system. We could term this effort 'dynamically constellating consciousness,' in which one seeks to 'hold in mind-ing' an changing network of interactions which syntergistically generate some recognizable, if ultimately irreducible or precisely definable, 'systems.' That is, just as quantitatively reductive scientific analysis can reveal that such phenomena are actual, without being able to entirely describe or explain these in causal terms, we can seek to perceive and represent them in non-technical 'approximations' that enhance our awareness and appreciation of their existence.

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The implication here is that awareness of phenomena as the 'wholeness' of 'constellated' as 'relational fields' actuall requires an alteration of the more ordinary 'organization' of our mind-ing, or 'consciousness.' When it comes to complex adaptive systems, our awareness or consciousness must become 'ordered' around or by interactive interdependencies, rather than separated things and events perceived as progressive sequences.  That can be considered as a shift in emphasis from the reductive impulse of left brain hemisphere attention to the more inclusive modality of right brain hemisphere inflected consciousness. Such aspects of 'constellating consciousness' are fundamental to promoting perception and representation of complex network dynamics. While we cannot directly 'see' these mostly invisible relationships, we must attempt to form some 'sensing' of them in our mind-ing and embodied experience. We might term this effort 'network vision-ing.'

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The Role of Non-Ordinary Language Usage and Imagery in Perceiving Network Interdependencies

That shift in our perceptual and representational modalities necessarily involves corollary changes in how we use language and imagery. It becomes important to deploy both in ways that emphasize dynamical instability, interdependency, and unpredictably emergent ordering. Those aspects of network dynamics we cannot specify precisely require some more 'impressionistic' representation. That means representing less in terms of progressive sequences or states or actions and more in terms of concurrent, mutually influencing interactions. Examples involve shifting from emphasizing definitive nouns toward verbs, as in representing our cognitive intelligence as 'minding' rather than 'mind.' A further aspect is using more active adverb and adjective-oriented language, as well as promoting dynamically suggestive imagery that 'makes meaning' in a more metaphorical manner.  

 

This involves thinking and representing in terms of 'like-ness,' or using non-literal associations to indicate qualities and behaviors. These shifts can influence representation by making it less quantitative or definitive and more qualitative, thus providing an 'impression' of dynamical activity and relationships. That, in turn, can influence both our perception and ultimate intuitive understanding of complex phenomena. These are ways of 'reorienting' how our mind-ing or consciousness models or reflects both 'how things happen' and thus what meanings we derive from interdependently interacting network relationships. This effort is particularly relevant to articulating the purposefulness or 'why-ness' of phenomena,-- or how these are expressions of agentic system behavior.  The more exaggerated mode of such language usage could be associated with poetic diction. Importantly, systems science actually provides technical references for assessing whether such non-literal use of language and imagery are more or less realistic as representations of complex system network dynamics.

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Language as an Exemplary Illustration of Network Dynamics to be 'Seen" ​

In general, tacking the originating and interacting relationships of systems as fields helps reveals both internal and external network configurations, along with the ways influence flows across these. Language itself is a dynamically active, complex adaptive system, in which its properties of meaning emerge from shifting referential interdependencies among its 'parts' of words. Each word is a 'system of meaning' that actually manifests as a relational network between other words. The word 'bed' represents the concept of an object upon which one sleeps. As 'thing,' beds are a system of physical parts that collective constitute a 'place to sleep.' Just like that 'object of interacting parts,' the word bed derives its properties of meaning from a network of interacting associations.  A physical 'bed' is typically associated with concepts of 'mattress, sheet, blanket, and pillow.' Yet it can have virtually infinite configurations. The word bed is part of an extended network of associations that make its property of meaning manifest 'from elsewhere,' from that network, and in various ways depending upon the context in which this word is used. The very word itself derives from other words that meant 'dig a hole.' But it no longer means that because it currently manifests from a different network of relationships in the larger system of language usage.

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​The word bed derives its meaning from other words in a specific network of relationships, which derive their meaning from other extended networks of mutually derivational relationships. The word bed then 'makes meaning' through these interdependent interactions. And, its meaning becomes connected to other words which have relationships with other words that seem unrelated.  Yet all of this can shift depending upon the context of 'usage,' of where, when, and why the word bed is used to represent some specific meaning.

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​Some of the words whose derivational networks contribute to the meaning 'bed,'

and the association of 'bed' with other words that associate with other words.

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The point here is, that language, as a larger scale complex system of 'purposeful meaning making,' derives from many subsystems, whose interacting relationships are interactive, unstable, and even contradictory. Such are the network dynamics we must somehow perceive and attempt to represent. By reflecting upon this underlying character of how language makes meaning we can directly experience the reality of complex system networks, then use language to 'unpack' or explore the infinitely interdependent, dynamically variable relational fields of seemingly separate, static phenomena. That is a fundamental way to 'constellate consciousness' in a more realistically complex manner..

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How do We Represent the Network Phenomena Revealed by Systems Science in a Non-Technical Way?

The reductive precision of scientific analysis that reveals the existence of self-organizing system networks also demonstrates how these cannot be known with exact precision. Consequently, there is a need for less technically reductive methods of thinking about and representing these phenomena to our understanding. Somehow, we must foreground the concurrent interactions, interdependencies, unpredictable ordering, and self-asserting aspects of ourselves and the world we inhabit. The basis for such thought and expression can be distilled from the scientific knowledge as some basic precepts to enhance our awareness. 

 

Firstly, the science indicates we must somehow 'elude' an impulse to equate a system with its identifiable parts or physical properties. The terms we use to 'name' things is a kind of practical 'short hand' that obscures much complexity: 'This is a machine. That is a financial market.'  The categories we use to define phenomena are often simplistically exclusive: as in 'Order is the opposite of disorder. Every action has an equal and opposite reaction. One thing follows another.' Our summary reductions give the impression that what is named or classified is fully known as a unitary phenomena. But from the perspective of systems science, events and systems often manifest as turbulent, variable, partly unknowable, 'flows' of interdependent relationships. How then to accurately perceive and understand these entities composed of 'moving parts' that can reconfigure their 'selves' out of their own disorder to manifest unpredictable yet purposeful properties and behaviors -- behaviors that have a "teleological" future-oriented purpose of maintaining a system's continued existence? We require ways to understand the 'why' of these behaviors, particularly the 'behavioral character' of self-asserting "super organism" human system -- to understand them as 'creaturely' entities with no capacity for empathy toward other systems.

 

'Network Vision-ing' as a Trans-Temporal Perspective on Concurrently Interactive Network Relationships

Perceiving the dynamics and feedback flows in relational networks involves a kind of 'trans-temporal' perspective. Firstly, we must track a network's 'history' to consider how its past formations might be active in its present activity. Secondly, we must try to notice what simultaneous activities might be part of the 'now' -- what are the various impulses of its synergistic 'many things happening all at once.' Thirdly, there is the consideration of what potential future formations it might be tending toward -- or what 'purposes' might be influencing its emergent formations. So, there is both a longitudinal factor of time in the interdpendencies of 'past <> present <> future' relationships, and also one of 'breadth' or 'latitude' in the concurrently interactive influences in each instant.

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We can also think of this expanded scale of awareness in spatial terms -- as in, 'where is what happening' in a network relational field. Many systems have accessible physical structures to their networks, such as ecologies and social institutions with various sub-systems. These aspects make it easier to 'locate' where and when specific actions and interactions might be occurring.  However, the potential formation of recursive feedback loops, with simultaneous flows of influence in multiple directions, and resulting interdependencies among these 'locatable' network "nodes" and connections, are not easily tracked in terms of spatial location and time sequences. Thus, it becomes necessary to think in terms of simultaneous actions occurring in response or relationship to each other, as well as to a network's 'history,' which might result in unpredictably emergent system behaviors. This is the realm of network dynamics that eludes exact analysis. Getting some understanding of what is happening and why thus requires interpreting a system's 'outputs,' or specific traits and behaviors, relative to a larger scale perspective on its past behaviors and extended interactions with other system networks. There is always much of significance 'going on betwixt and between' the identifiable 'parts' of complex systems, as well as between them and other systems. 'How things happen,' from a network perspective, involves interdependencies that defy our ordinary sense of time and space.

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'Network Vision-ing' as Correlation of both Internal and External Relational Fields

The context dependent aspect of system network manifestation also requires any assessment of what one is 'doing' and 'how,' as well as 'why,' or 'for what purpose,' to examine not only its 'internal' relational field but also that field 'in relation to' an 'external' one. 

The question, 'how did the batter hit the ball out of the ball park?' can be described in exact terms from the perspective of material physics by assessing determinstic causality in the batter's actions, the pitcher's throw, plus atmospheric conditions, etc. However, from a complex systems perspective, such a seemingly simple event becomes vastly more intricate and subtle. In that view, the physical events are consequences of ultimately obscure interdependencies both within the 'mind-body system' of the batter and with external network factors. The ball does not 'get hit out of the park' simply by physical forces. It does so because of numerous interacting networks that are 'acting' emergently to generate purposeful system self-direction. That home run does not manifest as 'mere physics' or as a discreetly isolated phenomena.

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A justice system that is configured for the purpose of ensuring fair and equal treatment of individuals according to 'the law' might manifest behavior that is racially biased. The source of that unintended system behavior might not be found in the internal structure of the system's network, nor the 'letter of the law,' nor the individual person's staffing it, but in flows of feedback that involve its networking with extended relational fields of cultural, social, political, and economic systems. 
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'​​Network Vision-ing' as Archetypal Elaboration

 

So, how then can we 'know' complex systems with any accuracy if these are unpredictably emergent -- if we cannot know them predictably or definitively? How might we anticipate their future formations and effects? One approach is to consider these in terms of the relative range of their dynamic behaviors over time, and in relation to various contexting factors. That means identifying the particularites of their internal relational constellations, then how those interact with external relational fields. Such references provide a 'characteristic' sense of their likely behaviors. But how can we compose some method for making these 'characteristic distinctions?'

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An Archetypal Concept of the Origins and 'Relational Identity' of Phenomena

The term archetype is derived from the ancient Greek word arkhetupon, translated as 'something first molded as a model,' and that word is a compound of arkhe, translated as 'primitive,' and tupos, translated as 'a model.' In contemporary usage, 'an archetype' has been regarded as representing the 'original form' of some thing, behavior, or concept. The term has also been used as an adjective, archetypal, and adverb, archetypically or archetypally. Here, there is a notion of 'being like' some particular 'type.' This usage has been employed to characterize how a given form or behavior derives from, or is an expression of, a range of somehow related forms and behaviors. Baseball is thus archetypally a form of game. The 'archetypal character' of baseball involves aspects of a broader 'archetypal field' of traits associated with the concept of games. This usage allows for understanding things, behaviors, and concepts as derived from a potential range of traits that are often found to be associated without defining them as exact 'copies' or 'identical with' a clearly defined, categorical type. An 'archetypal characterization' allows for identifying the unique particularities of a thing, behavior, or concept 'in relation to' a larger field of related phenomena. So, one can pose an 'archetypal field' of 'fathering' that includes a wide range of behaviors associated with 'being a father.' Then, an individual father can be characterized by identifying his 'fathering' as manifesting particular traits of the larger 'archetypal field' of 'fathering.'

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This mode of 'identifying' originating references and characterizing individual phenomena is clearly not definitive nor categorically precise and exclusive. It does, however, enable us to gain a sense of the potential relationships between a given phenomena and what it is 'related to' on an extended scale of associations.We could term it 'archetypal elaboration.'  It allows us to understand origins and identity as potentially inconsistent and even conflicted, yet still 'related.' The 'archetypal field' of 'fathering' could be said to include such contrasts as affectionate as well as abusive behaviors, thus that these behaviors are somehow 'related' in that 'field' of traits that can be noted in 'fathering.' Thus, a particular father could be assessed as an 'archetypally affectionate fathering,' an 'archeytpally abusive' one, or as the archetypally conflicted manifestation of  both. These phrasings do not define an individual father but characterize a prominent aspect of his behavior as a complex adaptive system. Linking such description with a systems science perspective, it indicates that his 'fathering demeanor' is emerging from feedback loops in his mental system networks that promote such 'characterizing behavior.'

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The 'relational identity' of geese could be described as an archetypal 'expression' of the larger field of traits associated with birds. Geese are 'bird like' in their particular ways. Similarly, 'a goose' is a version of the related field of traits associated with all geese. It is 'goose like' but also an individualized manifestation of 'goose-ness.' It might be distinguishable as more or less aggressive or curious than many geese. But this distinction is necessarily relative or 'relational' to the larger traits of 'archetypal goose-ness.' Taking a larger scale perspective again, we could characterize geese as archetypal expressions of the broader archetypal field of animal forms, which are archetypal expressions of the larger field of complex adaptive systems.

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This archetypal  field-view provides 'derivational' references and 'relational identity' at multiple scales -- as in, 'from atoms to biospheres,' or animals to humans to societies. It gives us information about why systems act as they do 'in relationships to' other systems. It can also characterize the potential behaviors of fundamentally unpredictable complex systems, providing understanding 'beyond' what causal analysis and explanation alone can do, enabling us to have some anticipation of 'what they might do next.'

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Correlating Network Science and Archetypally Elaborating Perspective

This 'archetypal characterization' of the origins and traits of 'an entity' is obviously rather vague. But, as a means of conceiving the overlapping aspects of relational influences 'at work in the world,' it is a kind of 'network vision.' We might tern this perspective as 'tracking the archeytpal dynamism' of network formations, or  their 'relational fields,' by non-technical association. If we think of categorization as a more exclusively definitive mode of distinction, as 'it is this not that,' thereby 'non-contradictory,' then 'arche-typing' can be viewed as a less more inclusive associative attitude that can embrace contrast and conflict as 'relational parts of a whole.'  So, a system's network can be approached as an 'archetypal field' of interacting factors, origins, and effects.

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Systems science uses a concept of "dynamical attractors" to represent how a dynamical system's overall behaviors appear to be 'pulled,' or 'attracted,' into a range of patterned behaviors. A whirlpool in water appears to be swirling around as if it were a response to some 'force' that 'attracts' the water flow into that shape. An individual person's overall behaviors pose a similar, though far more complex, example of distinctive patterning which suggests the traits of a dynamical attractor. The qualitative characterisitcs of such variably networked relationships. A dynamical attractor is a way of identifying the characteristic 'morphology' of a dynamical systems network acivity. In a similar sense,  we can think of network configurations as having 'archetypal morphology,' or types of structural and dynamical relationships that tend to constrain flows of influence across the network in particular ways. There are 'artchetypal relational dynamics' that both identify and elaborate the properties and characteristic behaviors of things, events, and systems. With complex adaptive systems, network morphology necessarily includes conflicting factors and instabilities.

 

In the most general framing, we might characterize some systems, or aspects of these,  as more 'archetypally deterministic' versus as more 'archetypally emergent.' That distinction provides a way of identifying the origins of their behaviors and effects in reference to deterministic causation verses emergent ordering. But this archetypal perspective is particularly useful for investigating the interdependencies from which the wholeness of complex phenomena emerge. It can elaborate a more technical systems science analysis of a relational network in ways that provide a more tangible 'feel' for it.

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Systems science also employs a concept of "adaptive landscapes," which involves the use of graphs to represent the corresponding interdependent behaviors of multiple complex systems, such as animals in a given ecosystem. These provide some perspective on the 'external' relational field of 'net-working systems of complex systems.' Such relational fields can also be approached archetypally as the interplay of various archetypal system characteristics engaged in an overall interplay -- such as the 'personalities' of various people in a social group.

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​Knowing Agentic System Networks as Manifesting 'Archetypally Characteristic Behavior'

It we approach the notion of 'character' as indicating behavioral traits of a system, then we can think of networks as expressing some sort of 'personality.' The 'beaver-ness' of beavers would then be the diversity of that species' range of behaviors, which collectively configure the archetypal range of its 'personality.' However, being complex adaptive systems, there will be variation in how that larger range of characteristics manifests emergently in as individual beavers. Every plant and animal species configures some such range of behavioral traits, which collectively constellate their archetypally characteristic behavior or 'personality.' Ecosystems, cities, societies, economies, and social institutions can be regarded similarly. New York is experienced as having a different archetypal character than Paris.

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Analysis of the configuration and feedback flows across the networks of such systems can then be associated with these archetypal characterizations to provide insight into how types of behavior tend to emerge from identifiable traits of network configurations. That is, one can ask: what is about the network dynamics of the city of Paris that might promote the emergence of its archetypal behavioral character? Comparing and contrasting network configurations and dynamics of various cities with their archetypal behaviors than provides some references for understanding how such complex adaptive agentic systems express their distinctive traits.

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We could term such consideration the basis for an 'archetypal psychology of agentic system self-assertion.' The terminology of human psychology can then be employed to characterize the archetypal behaviors of particular agentic systems, as in which traits of network configuration and feedback dynamics tend to associate with empathic system self assertion, verses more socio- or psychopathic personality traits. Thus, such efforts can distill more abstract psychological forms of archetypal characterization similar to that of archaic mythologies in which gods and goddesses can be seen as representing, or 'standing for,' diverse ways agentic system self-assertion tends to manifest in real world systems.

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'​Network Vision-ing' as Symbolic Dynamical Modeling

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​Similarly to how 'archetypal characterization' derives from identifying the 'likeness' of something in relationship to types of formation and behavior, the use of overtly metaphorical symbolism involves the use of 'a representation' (an image, form, or words) as a 'likeness' of other phenomena. A distinction is often made between the terms "sign" and "symbol," in which a sign directly 'stands for' what it signifies, but a symbol suggest what it indicates indirectly or metaphorically. Numbers are explicit 'signs' of a 'count.' There is a direct relationship between the number "2" and the 'count of two things.' The 'sign' of '2' in effect 'equals' the count of two items.  But a symbol is not exactly what is being referenced. A symbol 'makes meaning' by implication, allusion, impression, or evocation. Thus, metaphoric symbolism is useful in representing complex dynamical interactions and relationships. It involves the use of some 'representation,' (an image, form, or words) to convey or express the traits of some phenomena by eluding or 'characterizing' it.

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The aim of symbolic representation as a mode of 'network vision' is to 'model' complex system dynamics and network. relationships. That can be done in non-ordinary language usage, such as poetic diction that manipulates word meaning networks to reveal complexities of real world networks. It can be done in the forms and imagery of artistic expression. It can also be done in story telling that subverts our normally literalistic, causally deterministic sense of phenomena. It can also be done through spiritual imagination that models agentic system behaviors as 'personified actors,' a in spirits, souls, ghosts, demons, and dieties.

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The Experiential Purposefullness of Network Vision-ing

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While such methods can enhance abstract intellectual understanding of both specific system networks and their general role in the 'real world.' But a primary purpose for 'network vision-ing' is to prompt a more experiential sense of these phenomena. Both archetypal elaboration and symbolic representation can stimulate and kind of 'embodied awareness' of complexity and network dynamics. It can facilitate a sense of those dynamics in terms such as 'shimmering resonance,' even 'spiritual numinosity' -- a direct 'feeling' of agentic system behaviors 'at work in the world.'

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Network Vision as Altered State of Consciousness

Approaching 'network vision-ing' in these ways, in attempts to prompt a 'constellating' mode of consciousness, can prompt a kind of "cognitive fugue state" of mental disorientation. When one gets closer to actually 'thinking' complex network dynamics and interactive interdepenedencies, the result could be termed an 'altered state of consciousness' -- relative to one's more ordinary, causally-based, 'state of mind-ing.'​​

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