In this final part, I attempt to outline in sufficient detail a minimum set of operational systems that are necessary for the functional integration of advanced systems sciences. These systems attempt to outline and define some of the key operational models and procedures of this science in its various applications to diverse fields of inquiry and complex problem resolution.
The point of departure for this second part is the mechanical model of the machine. All systems are at least possible machines. A machine is an applied construct of a metasystem. It is a heuristic device. A machine is a hypothetical construct used for the description of systems of all sorts. It is also used in the operational description of the functioning of a system. A conventional machine is derived from a paradigm of classcial mechanics. It is to be seen that many naturally occurring machines can be considered to be non-standard in the sense that they exhibit patterns that are non-linear and relativistic in operation. We can call these machines 2nd order machines.
I have identified and attempted to construct five such systems (including symbolic mathematics, relational logic, intercorrelational statistics, experimental design heuristics and alternative intelligence programming.) These operational methodologies are those that I have developed in relation to different forms of research over the years and which appear to be congruent within one another in the functional-operational framework of the articulation of advanced systems. They are not the only or even the best methodologies for attempting to understand and apply advanced systems science, but they are a good starting point for the alternative conceptioning and operationalization of such a system.
I believe that these different operational systems share a common core foundation that is situated in the practical logic and functional framework of advanced systems science. In other words, they are designed and defined within the functional parameters of the requirements of advanced systems science, tailored to suit its needs at multiple levels. They are thus unique and have been designed as much as possible to fit the meta-paradigm that advanced systems science inherently and implicitly encompasses. They are also therefore inherently eclectic and synthesizing, to the extent that they tend to borrow and embrace techniques and methods from a broader spectrum of similiar kinds of procedures in more conventionally defined areas of their application.
There is a paradox in the development of such operational procedures. Systems that appear complex may in fact be quite simple and straightforward to model. Systems that appear simplex may in fact be infinitely complex and difficult to represent. We cannot know directly or only from the phenomenal appearance of things alone the system that underlies the patterning we observe. The basis for all operational procedures in advanced systems sciences is a presumed intrinsic discrepancy between reality and our ability to know reality. We assume several things.
1. Reality is minimally self-organizing in a manner that invites stratified determination of segregated systems relative to one another.
2. We are able to imperfectly comprehend systematically the structural ordering of the phenomenal event patterning we can observe or experience in reality.
3. We comprehend systems through the understanding of structural changes they undergo.
All phenomenal patterning is in this sense epiphenomenal and therefore the consequence of the operation of the underlying system. The challenge of our operational procedures is to backtrack and infer the operational structure underlying the phenomena that we are able to observe.
In general, it can be said, that observable phenomena are always limited in the amount of information contained about its underlying order. Phenomena itself may be multiplex in that it is in fact multiply determined by several different structural systems at the same time. It must be seen as well that all observable phenomena are transitive and in the structure of the long run temporary. It appears as if temporal constraint is the key defining variable of all systems occurring in nature. The structures we attempt to get at underneath are in fact "event" structures that mark the state-transitions of systems.
This is an important aspect of advanced systems science, and this distinguishes it as something different from conventional systems science which emphasizes functional reiteration of systems in an ideal and steady state, but which fail to adequately account for such systems in larger frameworks of dynamics and systematics. We do not seek synchronic and static descriptions of systems except perhaps in discrete states that are relatively stable. Rather we seek the dynamic and developmental aspects of systems as they change as alternative state-stages through time.
Thus, operational procedures in advanced systems sciences proceeds on the basis of elaborating the core models of systems in concise and clear-cut ways, and in their transformational application to actually occurring phenomenal event patterns through time. This kind of "dynamic clock work" model is the key operational archetype for our operational procedures. It assumes that there is always some sense of discrepancy between at least three sets of things: our ability to observe; what we are observing; and our models of what we are observing. There is always critical feedback between these three areas, such that they all influence one another in dynamic ways. Hence, we get a dynamic metasystem of the following kind:
Several points about this kind of model must be made. It is itself, as a representation of operational systems, a complex system of interaction between phenomena and our models and our own awareness of these things. The entire system, including the phenomenal systems being represented, exhibit the following relations:
1. They all relate to and cooccur within the infinite background of total reality that encompasses all systemic relations.
2. They all move synchronistically and simultaneously forward with time's arrow, albeit in a manner that is dynamic and infinitely complicated.
3. There are critical feedback relationships throughout the system that affects variables in all areas of the system. Hence, our observations influence the data we observe, and our models influence both the observations and our phenomenal experience, and the objectifying procedures of measurement we impose also influence all these things.
Detailed construction of such operational methodologies as dynamic systems is a good starting point in the elaboration of the alternative field of advanced systems science. They provide the techniques and conceptual foundation for their subsequent application to other problem sets that serve to demarcate the cross-disciplinary boundaries of this field.
There is one other set of points I wish to emphasize at the beginning of this first part. Operational procedures in advanced systems sciences involve the analytic-synthetic dialectic at every point and in every way. We analysis what we observe with the implicit model of some system operating in the background, in order that we might then synthesize an accurate but simplified model of such a system. We perform a hypothetical synthesis of such models in order that we might then compare them to the actual phenomenal patterns in sophisticated and non-trivial ways, and in order to compare them to alternative constructs. We can thus reanalyze our subsequent models in a dialectical process that results in the progressive refinement and increasing realism and parsimonious simplification of our models.
Conventionally, our analytical procedures in routine science are wonderful and extremely sophisticated. In fact, many people gain access and achievement in these fields primarily for their superlative analytical capabilities. But synthetic procedures of model construction and testing are less systematic and less sophisticated, though I see no inherent reason that they need to be this way. From the standpoint of advanced systems science this kind of dichotomy between analytic and synthetic procedures is both unfortunate to the history of science and unnecessary. Thus it is intrinsic to the elaboration of these operational systems that we reemphasize the systematic development of synthetic procedures of model construction and testing as well as the appropriate analytical procedures that complement these constructive processes.
Blanket Copyright, Hugh M. Lewis, © 2005. Use of this text governed by fair use policy--permission to make copies of this text is granted for purposes of research and non-profit instruction only.
Last Updated: 04/19/05