A glance through a simple microscope to view the cellular structure of some tissue of life is enough to reveal the profound complexities of nature hidden in even small spaces. When we come to realize that an average Eukaryotic cell is constituted by as many as a billion instantaneous large molecular structures and undergoes thousands if not millions of instantaneous reactions in a minute, we are hard-pressed in our laboratory experiments and procedures to be able to recreate all of these functions, or the general synergistic system we call simply "the cell" that they provide. Simply multiplying these cellular functions by the millions to cover the tissue structures of a few organisms or even just a few organs, does not thereby do justice to even a micro-habitat of a living eco-system. A glance through a simple telescope, out across the stars scattered across the night-sky, reveals a sense of largeness and vastness of scale that, in our astronomical calculations of cosmological being, become simply unimaginable. Wherever we encounter natural phenomena, we encounter a scale and magnitude of complex organized patterning that is far, far beyond our simple mathematical accounting systems or our poor linguistic abilities to summarize. We are left only with uncertain estimates and approximations that preclude the kind of accuracy we expect from mathematical formulations. And yet, this is the natural world in all its full-blown glory--it is the real world that we encounter every second of every day of our being, regardless of what we choose to believe or look at or not.

We have therefore called in General Systems theory and methodologies to rescue us from the shear explosion of natural complexity in the world. We know that the right theory, correctly stated in just so few words, in the right order, can be worth billions of costly, time-consuming calculations. We know that the correct set of mathematical formulations, equally concise, can save the day in our experimental attempts to handle the complexities presented to us by our attempts to unlock the mysteries of Nature. 

We therefore invoke the great spirit of General Systems, believed to be residing in all Natural Systems, to reveal itself to us in its wonderful, sublime simplicity. We pay lip service at least to its promise and prospect for a new comprehensive paradigm of unified sciences, if if this remains so far but a dream and a wish largely lacking in any substantive credibility. With each increase in our resolving power in the turn of the knob of our scientific instrumentalities of observation, we add an entirely new level and order of magnitude to our understanding of reality, and nature presents us with the ultimate paradox that there may be no effective limit to this process of adding realities on top of other realities.

General Systems theory and systems-based approaches to various sciences have increased over the years and have, wherever they've been applied, yielded highly productive dividends of new knowledge and understanding. But general systems approaches to the sciences have not yet come of age, and have yet to mature to a level at which we can claim a special place for it as a new paradigm of general science. They remain largely to date a disparate set of procedures and perspectives covering an even more disparate set of problems across a range of disparate knowledge domains. In terms of the central strategic challenge of comprehensive integration of the sciences, whether theoretically or methodologically, they have remained underdeveloped and insufficient to the task.

My terms for meta-systems and "meta-science" represent both a philosophy of systems and a science of systems, and provide alternative dialectical frameworks for the conceptualization and operationalization of science and systems together. We are concerned therefore not only with the abstract rationalization of why we do systems science, but with the redefinition of systems science as a comprehensive methodology for doing science. I will therefore approach the problem set in as exhaustive a manner as possible, dealing dialectically with both the philosophical and the operational aspects of advanced systems theory.

Ludwig von Bertalanffy first proposed a general systems framework in relation to the study of cellular structure and biological processes and patterns that could not be explained by a conventional reductionist analysis of the components. He called it originally organismic theory, or the theory of the organism as a whole, with the addition to the Aristotelian principle that the whole was more than the sum of the parts, but also was constituted by the organization of the parts and their contextual relationships to one another. The concept later became widely known as General Systems theory because it proposed the hypothesis that many different kinds of systems in nature evinced very similar kinds of patterns and processes that might be explained by a common set of principles.

The point was that there were far too many complex processes occurring in the analysis of the basic structures of living organisms than could be accounted for by a simple inventory or cumulative excoriation of all the components. Organismic theory later became adopted in holistic approaches to developmental psychology that similarly found conventional analytical methodologies insufficient to the problems of a full accounting for the complexities and patterns that human behavior presented to science.

Von Bertalanffy's critical point of departure in the definition of general systems was his hypothetical proposition of the general model of open systems marked by irreversible entropy and the occurrence of dynamic transport or transfer mechanisms between the internal and external environments of a system. This was contrasted to the conventional thermodynamic model of closed systems that characterized primarily our understanding of physical and especially chemical realities.

In extending the paradigm of General Systems theory somewhat, I have made a few of my own initial presuppositions that I have organized into a set of 10 basic precepts & sub-principles:

1. Objective reality is complexly organized as systems, and all systems are related to one another, however indirectly, within a larger natural hierarchy of meta-systems organization. The total structure of organization of reality may be said to constitute a universal meta-system comprehending and encompassing all systemic relationships that possibly occur. This total structure is isomorphic with the model of the total universe as a meta-state system.

• a. All real systems are composed of subsystems that occur in organized, ordered relationship to one another.
• b. All real systems are subsystems of some larger super-system or meta-systems context in which some part of its organization is constrained by its relationship to the larger meta-systems context.
• c. All real systems, upon whatever level or scale of analysis we are concerned with, are to be summarily characterized in terms of a set of emergent properties (recurrent developmental-epiphenomenal patterns) that are distinct to that type of system and unique to a particular system.

2. All real systems are partially open to a larger meta-systems context, and are also partially closed, and hence all systems may be characterized by both reversible and irreversible processes of entropy, and all systems may be said to be complexly underdetermined in situ to other co-occurring systems.

• a. All real systems are structurally defined by, for want of a better term, can be called boundary-maintenance or transport mechanisms that serve to mediate the relationship between external and internal environments, and that serve to maintain a sense of normal internal equilibrium of structure in relation to environmental fluctuations.
• b. All real systems may be summarized by a term "K" designated for holistic internal equilibrium, that can be said to be the overall synergy and pattern of the organization and function of the system in its environment, based upon a balance of net input (K_input) & (K_output) output factors.
• c. All real systems follow a typical life-cycle pattern that is defined by the stadial change in the K of the system from beginning, rising, balancing and decreasing ratios between net inputs and net outputs. Systems may begin in various initial start states and tend toward a common equi-final normal state marked by balancing K.

3. All real systems are subject to both random and non-random forces of change that tend to be both complicating and chaotic, and these patterns of change influence the state-path trajectory of a system, its instantaneous epiphenomenal patterning, and the unfolding structure of its development.

• a. All real systems operate within normal thresholds of tolerance for variable fluctuations, which, if surpassed, result in a systemic alteration or structural change in the system in order to reestablish equilibrium at a new level of order.
• b. All real systems must perform work at some normal range & thresholds of efficiency in order to maintain its normal instantaneous K.
• c. All real systems are subject in the long run and the large to structurally modifying perturbations that lead to the relational reorganization of the subsystems and subsequent changes of instantaneous and developmental K.

4. All real systems are subject to both the laws of thermodynamics & the laws of gravitational dynamics, and hence maintain organization or grow only as a consequence of work performed in a context of free and available energy.

The challenges of systems theory has been two fold: 

1. the parsimonious conceptualization & linguistic encoding of a consistent logical and metaphysical theoretical foundation for the organization of systems-based knowledge and understanding of reality;

2. the development of a coherent & consistent set of both pure and applied mathematical theories and formulaic operations that are sufficient to the tasks of description, explanation and application of a broad range of systems based phenomena and patterning.

These two sets of issues reflect directly the standard received approaches to conventional sciences that have existed for several centuries now. The empirical-inductive approach, championed by Francis Bacon in his essays of the 17th Century, reflects the second set of problems in the exploration of nature on its own terms for the discovery of new patterns and principles. The hypothetico-deductive approach, emergent clearly with the 19th Century scientists in biology, and going back to a classical Newtonian model, reflects the first problem set of developing a coherent conceptual view of the world, and employing systematic experiments to deductively derive verifications of conclusions forthcoming from theories of reality. These differences in fact reflect a fundamental schism in Western Thought and Philosophy, exemplified in the differences of thought of the British empiricists and the Continental schools of rationalism.

In terms of this dichotomy for systems based approaches, we have two basic forms of methodology that come to our rescue in our weak efforts to deal with the complexities and conundrums of Nature. The first is that of hypothetical generalization--the capacity to symbolically represent complex realities in simplified statements that summarize the structural principles articulating systems. The second is the experimental design application of models used to test our theories and to validate or falsify our ideas about reality. The basis of an experimental approach to systems-based research design and applications is to be found in modeling design representation for heuristic problem solving.  This of course requires the use of systematic procedures under controlled conditions to yield expected, if not completely predictable, results. If our small theory is correct, our results should be what we expect, and if not, then the results will be something other than what we expect.

A third approach has emerged as a result of systems-based approaches, and this is largely a computational-simulation approach that allows us for the first time to use computers to accurately and reliably replicate in virtual time real world patterns and processes, founded upon established scientific principles of relation and regulation. These approaches in the use of computing have permitted us to reexamine complexity underlying natural systems, and to query wider search solution spaces than we were ever able to do before. We can accurately set up and model experimental conditions in virtual time without having to resort to logistically problematic and expensive real world experiments. 

This third approach has really permitted a convergence and synthesis of the two approaches, for our computational simulations are based upon theoretical models and constructs, and they permit us to systematically explore and investigate the phenomenal patterns of reality, albeit in hypothetical search solution space rather than in real time.

Computing and systems based approaches to science have gone hand-in-hand and they demand one another in principle and practice. The information revolution engendered by rapid advancements in computing technology and power entails and indeed necessitates a systems-based approach to the reformulation of our sciences, for it permits us, pretty much for the first time, a means for gaining a methodological handle upon the problems of complexity and complication always evident for us in the patterning of natural phenomena. Thus, the computational approach provides the alternative paradigmatic foundation for the rethinking of sciences in general.

Computational approaches provide problem solving in all fields of science a common context for the construction and testing of models--this shared digital space is something all advanced fields of scientific research share, whatever their other methodological differences, and this very different problems of very different scales find common ground and common search-solution space in modern computer programs. Systems-based approaches to scientific problem solving are in fact implicit to advanced computational approaches and methodologies, and there is a growing recognition and acknowledgement of the systemic nature and structure of natural phenomena upon all levels that we encounter it. 

We will encounter this remarkable hierarchical property of nature throughout the book...Nature seems to be constructed like Russian dolls nesting within each other. One can pick out a doll of any dimension and appreciate it for itself. Unlike the dolls, however, one level of nature couples to the next layers above and below it in scale, and these interactions are described by the laws of nature. If natural phenomena did not have this hierarchical character, the practice of science itself would be nearly impossible. (William Kaufmann & Larry Smarr, Supercomputing and the Transformation of Science, Scientific American, 1993: pg. 13)

This passage from an authoritative and well-researched text on the main trends in computing in science, acknowledges directly the central systems-based principle of the natural hierarchical organization of nature, and the regulated relationships that occur between levels of this natural scheme. Computer simulations require of us that we think in terms of complex systems that are multi-factorial and non-linear in design, and that are founded upon multiple levels of organized phenomena hierarchically arranged according to the laws of nature.

The growth of mathematics in science has historically followed a trend reflecting the theoretical development of various fields. A classical and mechanical view of the world best expressed by Newton followed a form of mathematics based upon linear causality. The emergence of new theories and problem sets demanded dealing with large and random or disorganized sets, requiring the adoption of statistical applications in mathematics and the utilization of various theories of probability. With the advent of organized complexity and deterministic chaos, the requirement for non-linear differential equations and new extension of calculus have been in order.

The complex view of systems, and all systems, no matter how seemingly simple, are both complex and tend towards complication, demands means for dealing with complexity in numbers and accounting in equilibrium equations. Complex multi-variable non-linear differential equations that describe the flow dynamics and state-changes of delimited systems reach astronomical levels of difficulty in problem solving that can only reasonably be attempted through the use of computing and super-computing simulations. To date, these challenges in the development of advanced mathematical models and theories to handle complex systems in a consistent and coherent way have been daunting, and is marked more by the extensive elaboration of forced models and tried and true methods, than by the formulation of real simplifying solutions to the problems of complexity.

I have attempted my own integrated version of what I refer to as dynamic relational set-theory as a mathematical platform for a full-blown general systems paradigm. Not having been extensively trained in mathematics, I hope a fresh, self-taught attempt will not prove too trivial as a means of operationalizing systems-based approaches and applications to problem solving. Every System has its functional and structural schematics, and General Systems is not a complete science without its general systematics that serves to describe in an abstract or applied way any or all systems.

The model of dynamic relational set-theory I have adopted is one in which sets form basically non-linear multidimensional matrices, and the key terms of a set are constituted by what I refer to as relational variables, or variables that can be defined and factored in terms of other variables constituted other sets. This mathematical model & methodology may hopefully be expanded and modified under special circumstances to fit a broad range of different kinds of systems upon different levels of analysis, and may provide a means for the systematic modeling and topological/topographical translation of systems and systems change in multiple dimensions.

To some unknown extent, the models and problem solving applications of such an approach should be somewhat obvious if not entirely self-evident. They should lend themselves to alternative analogical and digital modeling by computers, as well as to providing readily available means for the simplified representation and handling of otherwise large and complex systems. 

When we speak of structure, we refer to some sense or order that is recognizable and distinctive within a background context. We use structure to predict and order our relations with things. And yet, for the most part, structures remain implicit only as part of the repetitious relational patterns of a system in its state-behavior.

Similarly, when we refer to system, we are implying the eidetic structure of relations that articulate to describe a holistic pattern that is somehow definite, demarcated and distinguished from surrounding relational patterns. Phenomenologically, we see systems and structures as processes that are stochastic and nonrandom, as an expectable patterning of phenomena that exhibits on some level or set of levels a complex sense of order.

Meta-systems theory is by definition a statement or set of statements describing and explaining the structural patterning of a system, both asynchronously across space and diachronically through time. It is essentially a variety of systems theory but it is a theory of all systems, or of any possible system, however these may be defined.

Meta-systems theory necessarily involves both a description of physical phenomena and a theoretical explanation that deals with the metaphysical aspects of the system in terms of its basic structural aspects or dimensions. The former description of physical aspects or traits of a system must necessarily involve the relevant physical context that defines the system as part of a larger framework of relationships. The latter explanation attempts to define that system in hypothetical terms that relate it, on an abstract level, to similar or different kinds of meta-systems.

Metaphysics as a traditional form of philosophical enquiry has been academically segregated as separate from science. Scientific thought arose out of a metaphysical preoccupation with reality, as an attempt to understand the essential structure of reality. Science, in seeking objective empirical criteria, threw out metaphysical speculation that did not rely upon empirical or experimental validation for its ground in reality. Nevertheless, much that scientists do in terms of theoretical speculation remains essentially a form of metaphysical inquiry and speculation upon the foundations of reality. Many a valid scientific insight has been achieved through metaphysical speculation without benefit of direct observational validation.

This relationship between metaphysics and the physical sciences becomes especially important when we consider the relationship of mathematics to both science and metaphysics, and how mathematics has served simultaneously as both a language of science and a valid area of philosophical inquiry. The number of philosopher's who have made valid contributions to the theory of mathematics indirectly influencing scientific thought has been remarkable.

Finally, meta-systems theory is also a form of information theory that deals with systems as information carrying and information producing structures. The theory of information has not been adequately elucidated. A structural theory of information systems is recounted below, but it must be kept in mind that such an abstract approach to informational systems leaves out a great deal of both the baby and the bath water. A comprehensive theory of information is to be undertaken in a companion work entitled The Philosophy of Knowledge. Herein I wish to treat only the basic structural and philosophical aspects of this theory and their bearing to meta-systems.

Beware the four idols of the human understanding

I have undertaken natural systems theory and metasystems science as an alternative method of framing and developing scientific knowledge. The central criticism of such an approach as it has yet been developed is that it lacks a strong and clear-cut empirical foundation but only stands upon the shoulders of scientific methodology. This is a legitimate if somewhat stilted critique of natural systems science. Natural systems science, like all science, is preoccupied with the unknown and the uncertain. If it is theoretically top-heavy in its early stages, it is so because it has a dual focus that should show a degree of parallactic convergence. Its first focus is the excoriation of reality in all its manifestations, to derive what can be considered its latent structures and order. Its second focus is to understand the constraints and dynamics of human knowledge systems that are used to represent these realities. Unlike conventional science, therefore, natural systems theory attempts to step beyond the boundaries of the scientific knowledge systems themselves, both in terms of the central object of interest (in a vague sense definable as the unknown) and in terms of the knowledge associated with that interest.

Hypothetical models are put forward in the initial stages of theoretical development of this perspective, not as the truth, but as heuristic devices that allow us to explore the ramifications and implications of our own knowledge about reality. Not every construction put forward in the course of natural systems theory development is necessarily interesting or even correct. These are promulgated not with the intention of imposing yet another human construction on the patterning of reality, be this whatever it may, but as a way of moving critically beyond the horizons of our own received constructions in the sciences. There are teleological implications to the received theories in the sciences that put to test, or at least should put to test, our collective imagination. It can be said that good science is in equal measure theory building and fact finding. Facts support the theories we build, and the theories allow us to find the facts.

There are also philosophical implications of our received view of reality that should be at some level approached and dealt with by science. All scientific theory demands some kind of explicated metaphysical framework, or at least exists in such a framework whether it has been fully explained or not. It becomes therefore a central aspect of meta-systems science to develop a natural metaphysic of science, which should include both an ontological view about reality, and an epistemological statement about our view of reality.

It has been a central contention of natural systems theory, arising out of the anthropology of knowledge, that science as it is articulated today largely lacks a clear-cut scientific worldview, or a comprehensive system of knowledge that can be said to be universal and natural and to take into full account the role and influence of a diverse range of human attitudes that are brought to such knowledge. Included in this scientific worldview would be not only humankind's relationship to nature, but also people's interrelationships to one another, especially in terms of our shared knowledge. It has been therefore a central objective of natural systems theory to construct and develop such a comprehensive perspective of the world in as scientific a manner as possible. Such a worldview must embrace an explicit metaphysic, as well as natural theory of systems in reality.

Implied in the name of natural systems theory is the starting premise that there exists an inherent order to reality that is latent to the manifest patterns of its phenomena as this has been found to occur at various levels. This natural a priori order cannot be discovered but by means of our language and knowledge capacity, which is inherently limited and constraining. The premise of a priori natural order goes even further to state that, in spite of all the variation of pattern found in reality, there are at its base a set of rules (or constraints) governing relationships and interactions, and in their fundamental form and function these rules can be said to be universal. The limits brought to this understanding by our knowledge entails that we will never fully or perfectly explicate these rules of order, but that our structural models and theories will be only rough approximations to the truth. Furthermore, if the second premise about reality made by natural systems theory holds true, that the structure of reality is infinite and open, we can see clearly that our knowledge of the known will always be faced by the shadowy paradox of the unknown that will circumscribe our knowledge at every point. Therefore, whatever models we develop based upon what we know, will always become in time relativized by all that we do not know. Therefore there should be no theoretical or empirical limit to the structure and order found by our knowledge, or of its knowledge itself, at least not as long as there are humans there to preserve it.

Francis Bacon probably would have criticized natural systems severely for its acute failure to develop a strong empirical orientation, and this would be a well deserved critique to make. On the other hand, natural systems science has its own operational foundation that leads directly to both empirical inquiry and practical application. But this empiricism can be said to be strongly theory-driven in meta-systems operation. This theoretical framework would be for the most part as explicit as possible.

There is nothing inherently wrong in freely entertaining ideas, or in using the human imagination, tempered by a close accounting with known facts, to solve problems that the intellect cannot otherwise solve by purely analytical and rational means, but this cannot be done at the expense ultimately of an empirical accounting of reality. If natural systems science is theory driven, it can also be said to be fact constrained to the nth-degree, as goodness of fit to the empirical evidence is the ultimate criteria for its success in the world. Erroneous theories at least let us know what we would otherwise not know and would remain unknown if we did not seek to empirically validate them.

This brings up a point in the natural sciences especially, and this is that data-bound and empirically driven systems of knowledge frequently tend to do a poor job of conceptual construction, often by failing to take into account the larger framework and implications of conceptual knowledge in the first place, especially in terms of its own constructive constraints. An empirically driving science that is well grounded to the facts of the matter, may be strong in one sense but less powerful conceptually than it might otherwise be. Reality that is strictly tied to what is known must be seen as being always overshadowed by the unknown as well as by what is hidden in our knowledge of reality but not unknown.

Coming out of the anthropology of knowledge, the development of natural systems theory is perhaps fortuitous in the sense that nothing known is so taken for granted that it cannot be questioned and critically evaluated. Nothing known is so non-arbitrary that it cannot be somehow alternatively framed or variably manipulated in order to arrive at some fresh perspective of possible reality. To a great extent, it can be said that natural systems theory is as concerned with the possible realities hidden in the unknown, as it is concerned with the limited realities contained in what we know. The aim of natural systems theory is to develop alternative constructs for purposes of the heuristic investigation of unknown realities. It can be held in the hypostatization of alternative plausible realities that can then be compared and tested against our knowledge. Often, such constructs may reveal hidden fallacies and contradictory implications in our own knowledge systems of which we may be unaware.

As Francis Bacon so clearly remarked so long ago, it is the nature of the human understanding to seize upon false idols regardless of their agreement with known realities. Even science itself, at this modern time, so advanced and sophisticated in its technical prowess, remains as yet not so far removed in some symbolic respects from Bacon's own time that was just dawning from the long sleep of the Dark Ages. At the edge of the unknown, even our advanced sciences fall back upon idols that are disguised as knowledge and understanding but which reveal a false sense of commitment to untested beliefs. The aim of a natural systems theoretic approach therefore is the testing of such belief structures by making explicit what would remain otherwise implicit, and by creating frameworks of comparison and contradiction where no such frameworks are otherwise found to exist. It can be called hypothetical and counterfactual in construction.

*****

The nature of the hypothetical models that have been proposed and revised represent what can be considered to be attempts at both comprehensive theories that are tied to general levels of the organization of natural phenomena, and at a unified metaphysical perspective, or what might be called a universal worldview, within which these models are articulated. Behind this approach stands what I believe to be an important form of natural human heuristic, which deals primarily with what can be called conceptual or symbolic problem solving.

For the first purpose, fairly specific models have been developed addressing the problems of integration and function at the physical, biological and human levels of natural patterning. In addition, other levels of patterning have also been addressed, alternative and applied systems, artificial or autonomous systems, abstract systems. In each area, specific general theoretical models obtain or have been proposed that embrace a number of covering law theories. There is no effort made to apply theories pertinent to one level to another level. Of course, no theory on the physical level can fail to take into account the phenomena of fundamental uncertainty, general relativity of space-time, or the cosmological principle. These theories only have metaphorical significance if they are applied to biological or human frames of reference. On the biological level, a systems model has been proposed that combines evolutionary theory with a dynamic ecosystems approach. The paradox is that on an analytical level, all biological systems may be reduced to their physical sub-components and the processes obtaining between them. But it is clear that as biological entities coalesce into organisms, populations and communities, there are emergent properties at multiple levels of synthesis that cannot e strictly accounted for in reductionistic terms alone. On the anthropological or human level, such modeling must take into account material, symbolic, constructive, psychological, social, environmental as well as biological dimensions and the theories pertinent in each of these areas. While frequent efforts are made to apply directly biological models to human cultural systems and processes, the tenuousness of these connections remain always suspect and uncertain. It is even more far-fetched to assume that indirectly all human processes are reducible to a purely physical level of description and explanation, which is possible, but remains partial and insufficient such that it can tell neither the whole story in terms of emergent properties indisputably attached to such systems, and that it cannot explain exactly how and why such systems developed or their state-path trajectory as complex and heterogeneous systems.

In other words, in systems theory, we do not mix our metaphors by using models developed at one level of analysis and synthesis to explain behavior at another level of complex organization. Of course, all natural systems are inherently stratified and thus are reducible to lower levels of analysis. Reductionistic analysis to the simplest, most basic terms is possible with any natural system we want to describe. We must remember that the entities at each level are comprised of forms determined by emergent properties from the elements composing it at the next lowest level of analysis, and this process forms an infinite regress to possibly a fundamental sense of "nothingness."

Metasystems methodology, as either an operational set of procedures aiming at analysis and synthesis, or as theory, provides what can be considered to be a metaphysical frame of reference about naturally occurring processes and patterns that can be called structural and scientific. The central thesis of metasystems theory is that underlying all processes and patterns in the natural world, at whatever level of analysis we may adopt, there are certain inherent structural design features which apply and which can be systematically described, and that, furthermore, provide us with a method for both analysis and synthesis in a systematic way. Such an underlying structural patterning should not be confused as the basis for theoretical modeling at different levels of stratification of natural order in reality. There are multiple levels of natural ordering, at each of which unique properties and pattern-producing processes apply. Principles regulate patterning in different ways at different levels, and the general principles that can be said to be the most pertinent to anthropological systems are not those most relevant to physical systems. We cannot explain one order of natural patterning primarily or exclusively in the terms and principles derived at another level. The models we develop at any one level of natural ordering, are pertinent only for that specific level, and may have at best only a metaphorical significance at any other level.

It follows that the kind of problem solving that is most applicable to the development of models in natural systems, or natural systems theories, is a form of problem solving that deals primarily with the ordering of relationships between things or complex sets of things, and which ordering can be said to be at best conceptually defined. This is to be compared to an alternative form of problem solving that is also important to the articulation of research in natural systems, and this has to do with analytical problem solving, or the kind of problem solving that is most associated with mathematics and experimental science. Conceptual problem solving can be said to be a form of dilemma resolution, whereas analytical problem solving can be said to be a kind of puzzle solution. A puzzle can be said to be a kind of dilemma with a finite or specific solution. A dilemma can be said to be a kind of puzzle without a finite or with a non-specific, or general solution. With a dilemma more than one kind of solution is possible, as solution of the problem in a complete sense is not sought, rather only resolution of the uncertainty that is associated with the problem. Hence, solutions to conceptual problems are more or less efficient and parsimonious, and some solutions are probably better than other solutions. Empiricism and inductive inference are fundamentally conceptual kinds of problems, in spite of the rhetoric of scientists and their conventional methods. We apply strategies of successive approximations to reach the best possible solution under the circumstances, without really knowing in any certain or exact sense whether or not some better solution may exist or be discovered. Precisely the opposite obtains in puzzle-type problems. Puzzle problems are abstract-deductive problems that use a strict form of two value logic to achieve results that are exact and completely unequivocal. Conceptual problem solving is based upon the achievement of "understanding" of a problem in a deep sense, and in a scientific sense such understanding takes the form of rational explanation and alternative hypothesis formulation. Conceptual problems are fundamentally linguistic problems, and concern the meaning, and possibly the structural order, of natural patterning. It is an error to think that puzzle-problems are the only interesting or sort of problems appropriate to any field of science, and that only the social sciences need be concerned or tied up with conceptual problems upon a conceptual and empirical level of complexity that precludes puzzle-type abstraction. It is clear that puzzle solving abstraction in this restrictive sense is far less useful at the level of the social sciences than it is in the natural sciences, but it is not without its purposes in the empirical and heuristic modeling of conceptually-based systems, especially when it comes to statistical sampling, analysis and knowledge representation. At the same time, it is equally clear conceptual problem solving is as important at the physical level of natural patterning as it is at the humanological or anthropological level, and it takes in many respects the same forms and functions at whatever level it is systematically applied.

Natural systems theory is mainly concerned with the explication, exemplification and experimentation of conceptual problem solving in terms of theoretical models and experimental/methodological constructs that have general applicability to the natural world. Efforts are made as well to systematically apply puzzle-type problems and methods to metasystems and natural systems models and theories, but this is not the main thrust of this work or the larger approach that it represents. To a great extent, the academically defined sciences and disciplines have achieved remarkable progress with puzzle-type problem solving, and tend to lag behind with the former kind of conceptual problem solving. The result has been the promulgation of scientific models in many different fields of active inquiry that are fundamentally weak and deficient in a conceptual problem frame of reference, largely because a more complete systems approach was not undertaken, and also because the fullest potential of conceptual problem solving in a systematic manner is seldom realized when hyper-specialization of focus is required for professional advancement and activity.

Conceptual problem solving demands the development of coherent "worldviews" that aim at comprehensivity of perspective as well as at achieving the greatest depth possible in such systems. It requires therefore a kind of backward chaining process of calling into explicit focus one's own background presuppositions and their implications. Superimposition of a systems approach, even if this can be variably defined by various people, entails what can be called setting a metaphysical and comprehensive frame of reference for defining scientific worldviews in a number of different areas of knowledge. This permits as well not only people to work in their own areas of knowledge with a greater sense of relevance to a larger natural reality, but it permits the interchange of information between different domains and between different levels that is useful heuristically for conceptual development of models. A systems approach, I would say, is the only appropriate approach for all the natural and human sciences, though such an approach may be variously defined and applied in different ways. Thus, when we claim a special status for natural systems theory in the philosophy and practice of science, we are claiming in fact status for natural systems theories in a plural sense that multiple models are always competing with one another at different levels of stratification/integration within a larger metaphysical framework. The models that result are analytic/synthetic in construction, and achieve success because they prove to be of the best overall fit and get the greatest mileage.

Conceptual problem solving and development appears to depend therefore upon the capacity to entertain competing alternative solutions at the same time, and to have the capacity to understand in some systematic manner the implications and presuppositions pertinent to any particular model that is proposed within a larger framework of understanding. It entails as well the capacity to create new solutions and to combine alternative solutions into a hybrid kind of model. It entails, in other words, a kind of conceptual and mental flexibility and agility of thought that mathematical puzzle-solving problems find inimical. The capacity to solve puzzle problems requires a single-track focus upon a narrow problem set, and systematic reduction through deduction to derive an answer.

*****

I believe that it is simply incredible and stultifying the extent to which all the scientific disciplines tend to lapse into dogmatic idolatry in their received knowledge at the edge of the unknown. This is almost an expected trait of all human knowledge systems, especially when there is a great deal of uncertainty involved. Even many of the methodological interests and focus becomes considerably compulsive and inflexibly employed when dealing with large sets of unknown variables. Uncertainty can be seen to be an almost chronic condition in some fields like the human sciences where there are few general laws or rules to anchor our frames of reference with, but the same thing can be said for any field of systematic study of natural systems. It is amazing that even in the physical sciences cosmological theories and physical constructs are typically received as is without almost any effort put into their critical evaluation and alternative reconstruction upon any level.

Natural systems theory can be said therefore to have a deliberate aim to call into question the received viewpoints of scientific systems, and to attempt at least to offer viable alternative candidates for the general description of reality at its various levels and areas. Beyond this intention, natural systems theory in terms of meta-systems science attempts deliberately as well to bring comprehensive unity to the various disciplinary orientations and to provide a framework for such unification of different and often disparate knowledge systems. Finally, it is the aim of meta-sciences to offer deliberate and clear-cut methodologies and methodological techniques for the heuristic modeling, empirical analysis, rational synthesis and experimental elucidation of natural and artificial systems. These then become the primary aims of this work and other related works.

My primary interest in science is in the study of basic theory of knowledge applied to natural and artificial systems in an objective sense, and to an objective understanding of the structure and limits of knowledge itself. It is an attempt to develop viable alternative models of what I call "meta-systems" that represents the world realistically and scientifically upon a number of basic levels of analysis and synthesis. I've come over the past year to revise the models to a point that a considerable degree of stability and continuity of structure can be said to exist for the framework as a whole. At the same time, I've come to extend the basic model as this was elaborated in the previous works in a number of different dimensions and directions of development, creating a larger framework for natural systems theory and meta-system's science as a whole.

Yet to get at these systems objectively I find it almost unavoidable to have to seek to get around the notion of "objectivity" from an paradoxically "objective" standpoint. In other words, I find it important to seek to understand knowledge itself as a system that is at least in theory separate from the world or worlds that it is used to represent. And in doing this, we must again resort to the meaning systems of knowledge.

To a great extent, achieving alternative perspectives in the sciences requires some measure of marginalization and what can be called a studied distanciation as well as a kind of self-alienation from the main or central forums in which such knowledge is articulated and played out. This has been done, in my own life, as much deliberately as it has been an inevitable consequence of my relationship to a larger world. Perhaps I have allowed it to happen, but in another way perhaps, considering the kind of person that I am, always questioning things in reality, it became unavoidable.

I've come to pay increasing attention to the socio-political aspects of the use of knowledge, especially for instance, in Academic settings, but everywhere else as well. To a great extent, most legal trials are political forums of conflicting interests, mediated by lawyers to decide the legitimate or "correct" interpretation to place upon a case. Cases must seem credible and "beyond any reasonable doubt." I do so because I think that even in science, there are paradigmatic aspects of the articulation of knowledge that are serve primarily socio-political interests, either those of professors who seek to monopolize research topics or resources relating to such topics, or of the state in the promulgation of certain administrative policies or even private-based interests.

The harm caused by what can be considered undue or disproportionate interest in the socio-political functions and aspects of knowledge systems, especially in scientific praxis, is that, I believe, of the negative sanctioning of dis-conformist views, and in the unnecessary frustration and stiffling of people's abilities, interests, motivations and directions in developing new lines of inquiry. The outcome is invariably a received paradigm and a field unnecessarily narrowed and restricted. This is reflected, for instance, in the narrowing of the scope of published materials in a discipline, and in the virtual censorship or derogation of "marginal" voices that enunciate alternative points of view. It is a potential loss of productive involvement that would be impossible to measure in the best of circumstances.

In the long run, such social praxis serves as resistance to the progress of a science, serving to put brakes and blinders on the entire program of research and scholarship aimed at increasing and improving our knowledge systems. It seems that scientific progress is often as not achieved in spite of these kinds of issues, rather than as a result of them, and thus, I believe, the reason for the title of Kuhn's book The Structure of Scientific Revolutions. When a paradigm shift finally does occur, it may be so sweeping in scope that it leads to a total collapse of the previously predominant point of view, along with all those who had a vested commitment to sustaining such a view perpetually.

My concern over these issues in particular has gradually arisen over the years in relation to anthropology as this is articulated in different forums and programs, and has come to take increasing attention because of the constructive and consequential nature of this discourse. It becomes a matter of whose point of view predominates or gets put forward, with a marked decreasing range of tolerance for alternative perspectives. Within such forums, there is much manipulation, negotiation, subterfuge and even, I would say, status control that occurs with the express intention of promoting some points of view while demoting other, anti-thetical ones. I have come to experience similar processes lately in programs other than anthropology departments, in the natural sciences especially where one would expect some degree of neutral objectivity and openness to alternative frameworks of interpretation.

I remark upon these issues because I believe firmly, or at least have come to a sense of conclusion, that these kinds of issues firmly impede us and stand in our way in the process of constructing new and better models of reality. A vast majority of Academics are caught up playing the Academic game, not so much to advance the knowledge of the field, but to advance their own somewhat restricted career interests in some department or university setting, or in some larger professional forum. The result I believe is a vast, bureaucratically administered army of highly trained brains marching to much the same tunes, and involved for the most part in the reproduction of "normal" science. The result I see is a narrowing of the scope of any and every field below what could be potentially achieved by the limited resources that are available.

I see the entire knowledge game as having come full circle, both in my own life, and in the larger history of knowledge in general. What started off a century ago as a critique of Western capitalism and imperial hegemony in the world by mainly European nations, and the rationalist viewpoints and sciences which largely supported these larger political economic formations, and what became in the 1960's a critique of the social construction of reality and the social relativity of knowledge, even scientific knowledge, and became in the late 1980's and the decade of the 1990's a call for a new form of political correctness and post-structural critique that appeared mainly self-deconstructive, seems to me to have reached a natural turning point, or should I say a "point of returning" to fill the void created in its own wake. Post-modern humanists, I should say, have created a negative debit in their own credibility, and they run the clear risk of not having anybody pay any attention to themselves, unless they can offer, in the wake of all their critique, a basis for new kinds of constructions and a new foundation for objectivity that is more or less free of the kinds of fallacies that they charged to the articulation of conventional knowledges in the world.

This work is about science, and not humanism per se, and humanists cannot be expected to successfully conduct scientific experiments on their own terms. The problem is not just bridging the gulf between the two Academic cultures and the worldviews and diametrically opposed ideological camps that they frequently represent. It is rather about seeing the larger sense of complementariness and unity of perspective between the subjective and the objective, and about developing a conceptual framework that puts this larger sense of integration of knowledge before the various and often competing and conflicting interests of different knowledge systems.

From an anthropological perspective, I offer a cultural basis for understanding knowledge and its articulation in the world as a potential meta-system, thereby substituting something that appears to be constructed and constructive for what has proven to be largely only destructive and critical about cultural and culturally derived theory. I define culture in a larger sociological and anthropological sense as something that is potentially emergent and reflective of the increased sharing and unification of people in the world. I offer furthermore the concept of culture as a basic meta-system for all knowledge systems and for their integration in the world, as a vehicle for achieving a new kind of world order that does not suffer as much from the kinds of contradictions our current world confronts. Many of the problems that we deal with in the world today can be analyzed in terms that are ultimately cultural in origin--much that stands in the way of achieving development and some sense of progress is due to cultural parameters that are narrow or stilted, usually to some coalitions advantage at the expense of many other people.

Knowledge systems, in other words, are invariably human based systems. We do the thinking, the learning, the knowing, the understanding and the communicating. We conduct the discourse for which our frameworks are constructed. All the mountains of stuff printed and published have no consequence or significance in the world unless they are read and used actively by people at least in thought if not in action. Scientific formulas mean nothing in themselves unless they are made significant by the human knower who can not only understand their significance but apply the formula to the world in some effective way. This is the basis for what I call the anthropological relativity of knowledge, and even purely scientific systems of knowledge are still contrained by the same kinds of factors in their human articulation and social praxis.

For myself, I have come full circle over the years in the sense that I have come to a reconciliation of my own frames of mind about my own professional identity and ambivalence as a professional vis-à-vis a larger community. I began my quest in this regard more than 24 years ago, in an attempt to overcome through understanding and alternative intellectual construction the desperate military circumstances that I had found myself thrust into. And so it has gone in every different context since that time. Its pursuit has led me to different foreign places, and to many different settings across the United States. The status aspects of knowledge, its politics, were never at the center of my being so much as they have come to occupy the center of my critical focus. I and my family have paid dearly for this sense of failure to participate in the political function and social articulation of knowledge, but on a basic level it is not this that I regret about my life. What I regret most in my life is not having carried such inquiry further than I have managed to do.

*****

All knowledge systems can have ideological functions in society. These functions are those of legitimization, creation of received authority and the capacity to determine social judgements of truth and falsehood. Ideologies have a universal claim and tend in this sense to be absolutizing over other knowledge systems. Absolutization of knowledge in terms of ideological belief structures has a fundamental function of masking the relativities inherent in knowledge. Furthermore, ideologies suffer the fallacies of naturalization, of reification and misplaced concretization. Social aspects of scientific knowledge, in particular what can be called paradigmatic, are essentially ideological in function. As ideology, sciences achieves its power institutionally by the repression of its own constructive functions, by disguising the history of their knowledge construction. As ideology, science becomes a form of self-contradiction that defeats its own purpose and function in reality.

Knowledge systems in ideological function have the aim at persuasion of people, and the cultivation of symbolic mythologies and the legitimization of structures of social action and belief that would otherwise lack symbolic realism and social motivation.

If all knowledge is socially constructed and potentially ideological, then it follows that its claims to realism must always be relativised by the acknowledgement, or at least awareness of its own social relativity that is a function of this construction. When science is taught as "objective truth" of the really real, it a approaches a kind of ideological dogmatism that takes its own social situatedness and origin for granted.

This claim is not the same as saying that there is not external reality that is the object of science to investigate, nor is it to assert that science cannot use objective method to arrive at a realistic understanding of this reality. It is to assert that this very function of science demands its own self-effacing as ideology, and a reflexive awareness of its own relativistic construction. This constitutes the anthropological relativity of scientific knowledge that is its own primary constraint in its articulation. The function of science as ideology is harmful to scientific praxis. The trouble with this fundamentally relativist stand, situated in the sociology and anthropology of knowledge, is that its own claim to objectivity must also come under critical self-reflexive investigation. We end up with a groundless ground upon which to base our meanings.

But if the claim of objective reality is a valid one, which I believe it to be, then the possibility and claim for a kind of objective knowledge of reality should also be warranted. Science largely attempts and achieves this, in varying ways and forms in different fields of its application and articulation. The fact of the social construction of reality, itself a reality taken for granted, is rooted in the basic and universal sociality of humankind, and in the communicative and symbolic function of its knowledge in the organization and functioning of this social reality. This social reality is as objective as any atom or animal that composes it, or as any space that contains it. It is the knowledge itself that is relative, because this knowledge is the intermediate form that occurs between our own awareness and sense of order in the world, and the experience of the world itself. All human experience is mediated by one form of knowledge or another, and usually by more than one, and all these forms of knowledge can be said to be symbolic in content, form, function and structure.

I have undertaken this work in natural systems theory coming from an advanced and hopefully sophisticated perspective that is by training and dent of experience grounded in the anthropology, sociology and psychology of knowledge. Issues of knowledge relativity and relativism are central in this understanding, as well as is the self-determination to escape the consequences of the ideological function of knowledge, its paradigmatic embrace, and to understand its consequences for our systems. Even further, it is to outline an approach that sees such reflexive understanding not as antithetical to a more objective approach to the representation and relation to reality, as this is especially embodied by scientific praxis, but to demonstrate that such an approach is a necessary precursor to a more objective worldview and means for achieving greater objectivity of our knowledge than is otherwise the case when such a perspective is either ignored or prejudiced against.

Only when formal knowledge systems, embodied in terms of their practitioners and the texts and forums they create, are understood from the standpoint of their own reflexive praxis and functions in society, as a kind of post-structural critique, is it then possible for science to step deliberately beyond the invisible boundaries of ideological paradigms that they create for themselves by their own cultural transparency. This is as true in the hard sciences as it is in the social sciences, even more true in some instances, albeit in different ways in different areas of knowledge and discourse.

*****

There has been at least for myself a disturbing trend throughout the sciences and within Academia in general. Perhaps it is only alarming for myself because I am an anthropologist who is supposed at least to be paying attention to such things. In academia, a rage for correctness and for diversity has led on one hand to a kind of intellectual inquisition and an emphasis upon conformist academic authoritarianism, and on the other, to the rise and prevalence at all levels of double standards and hypocrisy. Within the sciences, there is a general acceptance, or should I say unquestioning credibility, given to received views about how the world works, especially upon a general level of understanding. I would claim that academic programs and forums today are unprecedented, not for the open and free exchange of ideas in a common marketplace, but for fierce competition for status and resources, and for the dominance of received points of view over a humble and naïve attitude toward the unknown and the uncertain.

This is true, I believe, in the natural sciences, where received theoretical paradigms are no longer seriously questioned inspite of mounting counterevidence, and even more in the social sciences, where even good work of old is being discarded and devalued, not for its intrinsic merit, but for its failure to fit within the current paradigms that are promulgated. These approaches are no often no longer being taught as classics except perhaps in a dismissive and summary manner. Only in the biological sciences do we find the carry over of the older system of ideas, and its hybridization with new methods and information. But Biology enjoyed immense success within a Victorian framework, and has subsequently entered a plateau period of normal puzzle-solving that will not witness any "new synthesis" any time soon. And the paradigms that are being promulgated are being done so upon an unprecedented administrative and bureaucratic level of control that involves the collusion of private interests and public officials over the manipulation of government and academic resources. If there is a conspiracy about all this, then it was a conspiracy of chronies and of a modern business culture that was developed more than thirty years ago and is now at least into its second generation of sycophants and MBA's.

In short, I believe, we have created in global Academia a Brave New World, and it is therefore a world in which science can be nothing but normal and overdetermined. The metaparadigm of "correctness" has become entrenched upon a level of implicit, indirect sanctioning. We all know what is correct on a basic level--we sense it, though we cannot ever clearly define what it is or how we should be. Essentially, it becomes whatever our leaders want it to be. It has become embedded in the cosmopolitan culture of global academia, and its values of competition and monopolizations reflect the values of the capitalist political economy upon which it rests and to which it is attached as an institution of secondary symbolic legitimization. It is known now more in its violation than in its social articulation in society.

The main trouble and disturbing concern I have over the state of the academic mind is one of a failure upon certain levels to develop either an independent, coherent worldview, and, more importantly, a consistent and equally independent style and pursuit of life that reflects such a worldview and that adds to it in basic ways. A genuine interest and involvement in the reality of the world, has largely become replaced by an insincere self-involvement and self-interest in one's own prestige and position within a rank-ordered structure.

Worldview in many ways stands as much manipulated, even more in some regards, in open societies like the United States and Great Britain, as has been in the 20^th Century Totalitarian Societies, as in China and in other totalitarian states. This manipulation derives in the free world not from the restriction of the freedom of information itself, as it occurs in Big Brother societies, so much as it is intrinsic to the structure of the distribution of information, and to the interference in the access and availability of what can be considered to be critical or vital information. They are not being lied to and denied, so much as they are not being told the entire truth. People who maintain themselves as deliberately uninformed, because they have no access to the proper information channels, are not just docile and obedient as their counterparts are on the other side of the world, but they become something worse, I believe. They become willing participants in the control processes themselves, willing to edit the information to suit their narrow cultural rationalizations, etc. They become more highly manipulable and gullible by and to such misinformation because they see their main social interest in such a world. Chinese are led by the nose, the Americans by the tail.

A big part of this dilemma in the Western developed world is just the shear mass and complexity of all the information, and the challenges of its organization in a socially useful and timely manner. But this is not the crux of the problem, so much as it is the basis. The crux of the problem rests clearly with the control structures that operate largely behind closed doors rather than in open forums to manipulate the laws and implicit rules of social systems in the promotion of private self-interest. Academia in this context becomes a game to be played, often at any cost, in which knowledge and information is treated as a resource and a commodity to be bought and sold for profit, and people are merely pawns and cogs in a largely impersonal system.

In understanding where we have gotten to in the academic system, we must ask ourselves what might be wrong with what we are doing, and what may be missing from all that we have done or intend to do. Furthermore, it is rooted in our goals, values and our educational priorities as to what is important to transmit to the future and what is conveniently, if not safely, ignored.

One of the things that seems missing in the academic milieu, is a genuine sense of cooperative endeavor for the achievement of common and collective goals that extend beyond the life-world of the individual. Another thing that seems missing is a full inclusion of the individual as an individual, rather than merely as a member or a competitor in a larger marketplace. This implies as well that there is lacking a fundamental level of trust and solidarity in interpersonal academic relations, as well as a fundamental reciprocity of interest and attention that is not prestructured within some hierarchical framework.

Missing also, I believe, is a sense of the play of ideas, or a kind of ideodaedaly that allows the production of new and alternative insights. Connected to this seems to be the lack of forums for such open communications to be cultivated and take place within, as well possibly as the appropriate atmosphere of social relations that entail mutual interest, respect, tolerance and appreciation of alternative points of view.

This kind of critique comes as a paradox to the formal trend towards increase in diversity in the Academia upon all levels. This sense of paradox is only resolved when we realize that diversity is largely a front that is defined in rather spurious and pseudo-scientific terms of race, and it therefore becomes a mechanism for the inculcation of a narrow sense of conformity, rather than as a means for opening the channels of communication between different people and different kinds of people. By opening the competitive base at one end of the academic ladder and in some ways within the larger social system, they have managed to effectively close it on the other end and in other ways.

*****

There is an important sense that runs throughout an anthropological perspective, especially in terms of research, that involves the problem of attempting to relate the immediate, and concrete apprehension of events and relationships one experiences in the here and now of everyday reality, with the largest possible significations that one can bring to bear upon the framing and comprehension of such experience. Through experience, we learn to do it commonly in field research, and we find ourselves sometimes embarrassed when we are still doing it somewhat habitually in the course of the rest of our lives. These significations that we draw from and bring to our everyday, concrete experiences are not of any form or fashion, but are constrained by certain guidelines of selection and definition that are framed within an anthropological idiom and worldview.

I have undertaken this work and previous works (Natural Systems, Metasystems) as a result of a decade and more of involvement in an esoteric field known as the Anthropology of Knowledge, that is akin to the perspectives referred to generally as the sociology of knowledge, except that traditionally the problem of the anthropology of knowledge deals with the anthropological (including, but not exclusively, the social construction of reality) construction of reality. Many questions inform this kind of study, which can be considered the cognitive equivalent of cross-cultural research. We consider issues of natural and cultural classification, the influence of language and culture upon human thought, the general relativity of knowledge, the possibility of cognitive universals, early acquisition, socialization and secondary enculturation of personality, psychological abnormality, especially from a cross-cultural perspective, the problem of symbolism and symbolic behavior, the ethnosemantic and ethnoscientific organization and distribution of across a cultural landscape knowledge, the cultural and ideological constraints of knowledge systems, the worldview problem, the problem of attitudes, emotions and behaviors across cultural boundaries, the problem of common sense, the problem of logical inference, the problem of the influence of literacy and orality upon human noetic patterns, problems such as the rural-urban transition in affecting the way human beings think and respond to their world, as well as a host of other related questions.

In returning from fieldwork abroad, I have sought both a larger, more general definition of the kind of research and study I have done, and I have sought to extend its methodologies operationally to embrace a wider array of applications of knowledge. At the same time, I've sought to elevate the entire problem of the "construction of reality" to a level of theoretical and methodological stature and design that it probably deserves, beyond being the mere critique of western knowledge and its structural articulation in the world. I have sought to extend the theoretical insights and problem solving operations developed within an anthropological perspective, to embrace a wider plethora of the human experience as this is articulated in and by means of formal knowledge systems. This development has gone in several different but convergent directions at the same time. I have been interested in the elaboration of what I refer to as a metasystems approach, which can be said to be based upon something akin to a "metaparadigm" of knowledge.

This entails that we adopt not only a critical or "post-structural" view of knowledge systems as we find them in the world, but that we attempt to define what can be called a metastructure for knowledge systems, whether of our own construction or a claim to more objective status in the world. In other words, I have sought to offer yet another construction in place of all our constructions, but one that is better informed than either the constructions or the critique.

Especially in this regard I have come to focus mainly upon scientific knowledge, and what might be properly referred to as the anthropology of scientific knowledge. It embraces what I call the natural sciences, which includes the physical sciences (physics, chemistry, geology and related subdisciplines); all fields of the biological sciences; and all related fields of the social sciences, (including anthropology itself, which paradoxically is the framework in which this work is defined in the first place). It also has been enlarged to embrace fields of mathematics, philosophy, engineering, education, art and, last but not least, the so-called cognitive computer sciences.

The role of science in the world and scientific knowledge has become of increasing interest in this research for several interrelated reasons: 1. As a knowledge system it has achieved superlative success in the shaping of our world and the received view of our world, both positively and negatively, and nevertheless, it lacks a "total worldview" that can be called its own. 2. Issues of the status and importance of scientific knowledge in the world, its organization and dynamics, has remained as yet unresolved. 3. Science as a general knowledge system informs a great deal of what is done in many different and disparate knowledge systems, though these processes have not been fully described. The sciences as a plethora of varieties of expertise seem to share basic presuppositions in common, and yet exhibit many fundamental differences in approach and style as well. 4. Science offers the potential for achieving a theoretical perspective and system of organization of knowledge upon a level of integration that has not yet been realized. 5. Finally, science as what I consider to be a central problem in reality involves the question of reality in both the most basic and most ideal senses that we can come up with.

One form of anthropological relativity rests upon the interpretive parallax of human language systems, particularly as these are used in the general description and denotation of reality. In such cases, multiple solutions to basic problem sets can be generated, each essentially correct, depending upon how the problem sets were defined in the first place. Each view would be entirely logical and rational, though they may lead to entirely different, and even at times conflicting conclusions. The problems themselves are as often as not defined in terms that lack any sense of clear resolution or that fail to disambiguate the realities supposedly represented. In such situations, we can say that the lack of agreement does not begin in the conclusions, but in the definition of the terms and the presuppositions that we bring to these terms that we employ. This demonstrates at the level of the study of culture and human reality, a certain form of semantic uncertainty about our knowledge, and a kind of complementarity of alternative points of view, each equally or more or less correct, but each limited in the terms that it uses to define the problem and reach its solution. Furthermore, science imposes some kind of objective criteria or set of standards upon such viewpoints, such that it stipulates that for any given problem set in reality, there should ideally be only one correct set of answers or best solution that exists independently of our knowledge parallax that we bring to such "systems" regardless of whether we can clearly identify or define such structures. They are presumed to exist at least a priori to our ability to comprehend them or the fact of our apperception of them.

The complementariness of the structure of knowledge, at whatever level we are addressing, but especially in this case, upon social levels, is inherent to the knowledge and depends upon the primes that we adopt in our definitions and presuppositions about the world. The first inferences we make regarding some problem set about which there is some degree of uncertainty, due to lack of information, will determine the possible outcomes that we arrive at. If we realize that our first definition of the problem may be prestructured in terms of the kinds of inferences we make from it, prestructured by our habits of seeing and defining what we see, by our habits of perception and conception that framews what we see, by unstated feelings and semantic meanings that remain usually below the surface of our awareness, then we can see that the outcomes of our interpretation or investigation may well depend upon our initial states and statements we make. If more than one set of solutions might be forthcoming from this semantic parallax inherent to complex problem sets, then we cannot claim that one solution is better than any other or is to be preferred, except perhaps unless we impose some set of intersubjective standards upon our solution.

This complementarity of knowledge resists the notion of establishing singular or primary causality for event processes or occurrences in the world. There are always more than one cause for complex problem sets, and therefore more than one correct solution in the explanation of such problem sets.

In light of this fundamental consideration of the anthropological relativity of knowledge, I have sought to offer what I feel to be the underlying structural aspects of naturally occurring systems at all levels. We can make the following kinds of statements:

1. All natural systems consist of complex, composite event structures that occur through time and in space, usually in a repetitive and at least in an expectable pattern.

2. All natural systems exhibit event structures that are reducible to series or sequences of cycles defined by two or more discrete events that occur per cycle.

3. All natural systems are informationally describable--their patterns can be linguistically or mathematically defined in terms that permit conclusions to be drawn about similar phenomena, or outcomes of such phenomena, and can be explained and demonstrated in terms of the rules derived logically and statistically from the observation of the patterns.

4. All natural systems are based upon emergent properties that are explainable in terms of the synergistic relationships of component subsystems. Emergent properties characterize the behavior of the systems as a single whole or integrated unity.

5. All natural systems are mechanically ordered and function upon different levels. Such systems can be said to be mechanically articulatory, and the patterns produced by their articulation can be described in terms of discrete cycles or steps.

6. All natural systems exhibit some form of equilibrium of energy between its component parts and as a system as a whole in relation to its surroounding environment.

7. All natural systems have some form of built-in control structures that regulate the articulation of the system.

8. All natural systems perform some kind of work, that can be described, in a larger sense of the term, as anti-entropic in function. In other words, they can be said to occur in patterns that are relatively: 1. nonrandom; 2. semideterministic.

9. All natural systems appear to articulate with other systems in regular ways, leading to the development, through emergent properties, of a higher order system of integration that leads to the development of new natural systems.

10. All natural systems integrate within the natural surroundings of their articulation, and are subject to the same sets of physical properties and laws that govern their physical surroundings.

We can add a few more caveats to our definition of natural systems. All natural systems are both finite and continuous, have start, middle and end states, and tend to be instantaneously unique from any other similar or different system, and yet are however remotely related to any and every other natural system.

A natural system, in other words, can be described in definable terms and can be explained in terms of the mechanisms and state-path patterns such systems exhibit. Furthermore, they are amenable to experimental control and replication in nature, and these facets render the elaboration of such systems to be a fundamental part of scientific method as this is conventionally understood. In other words, we do not have to invoke what can be called supernatural causes to explain the origin and function of natural systems upon any level.

Natural systems therefore are a set of things and/or processes that interact and cohere together to form a functionally integrated unit. The basis for their integration is the rise of what can be called "control" and this "control" forms the basis for the emergence of dependent patterning. Control can be considered to be any measure of feedback that results in resonance patterning, whether this is amplifying, dampening, stabilizing or destabilizing. Control can be simple, or it can constitute a rather complex subsystem of the one it is controlling. Control sets in motion active constraints in the relational interactions possible within a system, and hence serve to regulate and forestall the path toward random decay in order between the subcomponents of the system and the system as a whole.

Control enables the establishment of a dynamic equilibrium of a system in relation to its surroundings, and this equilibrium is tied to the reciprocity of relations within the system and its environment.

Thus, the maintainence of order against the gradient of universal entropy is the basis for undertanding life forms. It confers to a system a distinctive identity in nature, a pattern of order in a sea of disorder, that is frequently demarcated by the maintenance of some boundary mechanism.

There appears to be a fundamental similarity of ordering of natural relationships in the world at any and every level that we may choose to analyze. I have sought to frame within scientific terms, terms that I furthermore seek to qualify from both relativistic and objectivist standpoints, what I have come to call a metaparadigm of natural systems that exhibit a similar structure of patterning upon many different levels.

I would call a "metaparadigm" a framework for understanding that seeks to be comprehensive and encompassing of knowledge of many different forms. The metaparadigm that I seek is a system of knowledge that successfully integrates scientific knowledge, as well as other forms of knowledge, in a comprehensive framework.

What I refer to as a system embodies the notion of the complementarity of knowledge, that we seek to know and understand that with which we are dealing from as many different angles and perspectives as possible. But a system is more than just knowledge--a scientific system attaches itself outside to a world of experience and sensibility and action. It is a system that has a material form of expression and that therefore always involves the energy dynamics that are associated with any material form of objective expression. We call such a system mechanical--it is composed of working parts that make certain events happen, events that always involve the exchange of energy at least.

Thus the system of knowledge in science is purportedly at least based upon the implicit systems of nature that underlie the patterns of things we observe in the material reality. The system of knowledge in science is also based upon another fundamental property that seems inherent and important to the patterning of nature at all levels. It is based upon information that is implicit to the patterning of nature. By information, we are not referring to knowledge, but to the building blocks of knowledge that are derived from the order and repetition and regularity of pattern that we find in nature, as well as upon the changes and differences and chaos found as well.

Natural information is always found embedded in reality in a manner that invites choice and alternatives, variation and fluctuation. We assign meaning to these patterns, as we project by means of our cognitive abilities a symbolic framework upon the world, and we take in these meanings as things of symbolic significance in our lives. In a strictly scientific sense, we delimit this meaning strictly by empirical, etic standards of observation and replicability of results. In this sense, information is a part of a system, a property of a system, and makes no sense outside of the system's framework. In such a case, information can be considered an inherent part or property of the design of the system, or its structural order and function. Natural information can be seen to be directly associated to and dependent upon the problem of energy in the natural world, particularly the problem of the organization of energy to perform some kind of work. Work in general occurs against a natural gradient involving the entropic loss of energy and therefore the inherent randomization and loss of ordered pattern and relationship.

Information is therefore a kind of trick nature plays upon itself--an order of relationship in a world based upon the inevitability of disorder. We derive knowledge from information that is a part of the structure of patterning we observe, and yet the information itself is critically conditioned by the selective perception and or preconceived categories employed in description. This is another fundamental part of anthropological relativity, that it is ulimately impossible to see the world in a fully disengaged or distanciated or objectified way. All such information will be framed not only in terms of the event patterning in which it is manifest, but in the terms that we bring to the experience of reality in order to render such reality meaningful and useful in our lives. If this is not challenging enough by itself, we must also take into account the informational facticity of our own presence and material existence in the world. We are a natural part of the informational framework that we are attempting to describe and define, and this basic truth is often lost sight of in supposedly "objective" interpretations of reality. We are attempting to define and describe information in terms that are ultimately part of the informational system, and that are composed by the same constituent factors that are involved in the production of natural information.

A systems framework provides a means for the organization of scientific knowledge upon an integrated and comprehensive level of its articulation in the world. In other words, it forms the foundation for the development of a metaparadigmatic approach to scientific worldview in a universal and general sense, as well as to scientific praxis in any context in which it can be said to occur.

A common definition that I feel applicable to all scientific knowledge is that it is:

1. Problem solving, in such a manner that solutions to the problems it attempts to solve are empirically substantiatable and replicable, lead to the solution of other problems (i.e. they are productive solutions), and lead as well to new information and knowledge about reality, or else to the progressive improvement and refinement of such knowledge compared to some received standard.

2. Empirically descriptive and classificatory of reality in terms that are objectively realistic and make sense of the events and relations found in reality in some rational order.

3. Theoretically explanatory of the events and relationships found in reality in a manner that works and that can be tested by means of repeat, controlled experimental application.

4. Results in the augmentation of reality by the invention and devising of new systems of information that are alternative and non-natural, but which are based upon the ordered manipulation of natural events and phenomena.

The last point may not be obvious and is developed further at a later point in the text. Suffice it to say in this introduction that

Though it appears that I have adopted a fairly standard and conventional approach to the definition of science, I would qualify such an approach by a number of statements. First, science is what science does, and it appears that sciences is being done differently by many different people. It may seem superficial and perhaps superfluous to impose and arbitrary set of standards or system of problem solving upon all sciences, regardless of their domains, their history and their models and methods of praxis.

Beyond a received view of science, we must address the notion of the culture of science that shares, among other things, a certain consensus or agreement of worldview and understanding, as well as a special set of problems as well as the instruments for the solution of such problems. The culture is not all about sharing and consensus--it is as much about the competition of ideas and conflict of viewpoint as well. Scientific culture is about language dialects that define realities in complex terms, and about the sharing of implicit values and standards that serve to demarcate the boundaries and codes of conduct for this or that kind of scientist. It is about the control and distribution of resources and funding that permits and legitimizes some forms of research, and undermines and destroys the basis for other kinds or directions of research involvement. It is about egos, people and small cliques that become established and vie for position and status within some social organizational framework. It is in other words an inherently plural reality from the standpoint of the distribution of its knowledge among a broad plethora of different domains.

These aspects of the anthropology of scientific knowledge are no less important than the previous approaches toward its objectivity, for they affect the shape and outcome of scientific knowledge, and its ability to serve as either a positive or negative force in the world. But more importantly, they help us to understand the realities of science as something that is lived, as social praxis and process that has its own dynamics and that influences how it articulates with and in the world.

The issue of the socio-cultural construction and praxis of scientific knowledge, a viewpoint which arose clearly in the humanities as a critique of science, has probably been ill-received if at all within the sciences proper. Nevertheless, it does warrant consideration, as it broaches a much deeper issue within the argument of anthropological relativity of all knowledge, and that is the inherent dichotomy between subjective and objective ways of knowing. At all times, knowledge is situated both in and outside of the individual, and knowledge acts as a bridge between the inner and outer world that allows coordination of a sense of self and place within a larger context. We can see in this argument at once a larger symbolic function of scientific knowledge in answer to the question of "why" science. It situates the subjective sense of self within a world that is more certain and more solid because of its sense of certainty. It helps us to make sense of the world, and via this means, to also maintain a sense of balance of the ourself in the world.

The subject-object dichotomy is inherent to all knowledge, and is reflected as well in the social situatedness of such knowledge, as both a sense of objectivity and greater subjectivity is broadened out to embrace a wider range of people. For this wider compass, a scientific worldview and collective representations offer the possibility of a basic sense of unity and a shared foundation for consensus about reality, as well as the possibility of greater realism in action and as expressed in social relation. It has from the beginning been a goal of science that it should involve an improvement of relation between people and the world, and between different people as a part of this world. The basis of scientific standards of measurement and objectivity really rests upon a shared locus of the public availability of scientific knowledge, open to independent test and verification. At the same time, the legitimation of the subject aspects of scientific knowledge also exists essentially within a social locus--one person alone has neither a clear sense of objectivity or one's own subjectivity.

I believe that scientific realism and detail of knowledge would mean little by itself if it is just left in books or journals on library shelves. It is in the act of reading the literature and understanding in a subjective sense that such knowledge achieves its purpose and function in the world, and that serves as the principle motivation, beyond status mongering and ego-centricim. Again, scientific knowledge, without independent social verification, remains essentially solipsistic and useless. Its use and function therefore always has both simultaneously a social and subjective locus.

As the basis for a metasystems approach and to advanced systems science, I propose a general heuristic problem solving methodology that I believe has substantive applicability to a wide range of knowledge systems. The basis for this approach is to construe problem sets, whether natural or of human origin, within a complementary framework of theortical and operational interpretation that permits what can be considered successive or progressive resolution of the problem set by means of some workable solution that can be said to be of optimal value in terms of some received set of standards. There is both a rational and consensual framework for the framing and operationalization of these problem sets, that are rooted in as much common sense and basic experience as they are in open mindedness and exploratory inquisitiveness. There is also an empirical framework for problem definition, description and reference by which the results and outcomes, as well as the terms and terminologies, and the underlying taxonomies of relationship and difference, are consistently applied. At the same time, there are what can be called lateral models and alternative points of view, as well as complementary forms of knowledge and perspective, that may play upon the definition and solution of problem sets.

We stand in the middle of these influences and constraints, and we engage ourselves and one another in a dialectic of inference and practice by which we seek to resolve the sense of complexity and the overwhelming overload of information by some elegant and simplying formula or paradigm that brings these different directions of knowledge together in a common middle-ground.

It is recognized that in any theory construction there must occur a compromise based upon a whole series of trade-offs between competing points of view.

The heuristic methodology I have espoused herein is one derived from anthropological research and is one that has general applicability in a large number of areas. Part of the issue here is the problem of the linguistic entanglement of meanings and words in the definition and explanation of scientific reality--language remains the primary basis for the communication of scientific information and ideas. Math as the abstract language of science is valid in an abstract sense as implied in the Noumenal realities of Aristotle and Plato, but its application to the description of actual natural realities is usually limited to measurement upon some scale, be it that of distance, time, temperature, weight, pressure, or count, be it percentage, proportion, sampling or some other derivative statistical measure. Even intrinsically, the applied use of mathematics to the problems of scientific description and explanation remain for the most part abstractly oversimplifying and limited in application. Hence, such language is usually severely limited in the actual process of defining and explaining event structures and state-path trajectories in nature. We therefore invoke standard language to come to our rescue, but then we are confronted with its semantic constraints and its inherent imprecision to describe faithfully the details as well as the conceptual rules lying behind the details.

The general heuristic proposed herein has efficacy to the extent that language problems represent duality of patterning in relation to the problems that they attempt to solve. If problems are empirically definable with finite and correct solutions available, then the challenge becomes to both disambiguate the terms used in the logical definition of the problem, as well as to push the problem in the general direction of the solution by ever closer approximations. The problem we deal with here, even for applied mathematical descriptions and statistic, are the logical inference structures that we apply to the understanding of the implicit rule structures and relationships that we find in our data--this problem is by no means a trivial one, nor can it be simply and safely overlooked just because it remains largely an invisible issue. Furthermore, we are limited in the semantics of our language to a definitional view of reality, and to a referential semantics that implies also some sense of taxonomic hierarchy, often embedded in the language itself, that implies underlying theories about the things being thus described. We would like to invoke a simplifying sense of common sense, or at least to basic categories, but we are hardpressed to find a common sense in the world that is not underscored by ethnocentrism or ego-centricity of judgement, nor are we likely to find a patent definition for what are "basic" or "natural" sets in the world.

No one who has a slightest interest in the modern reality of the world can avoid ultimately the question and problem presented by knowledge and information, its engineering, structure and dynamics, as well as its political-economy in the world. All research and scholarship that aims at the preservation, extension and promotion of knowledge, especially of new knowledge, can be thought of as a form of knowledge engineering.

Definitions abound in science, and definitions of science also abound. There are as many definitions of science as there are people practicing it and textbooks teaching it. Definition appears to be a key operator in science--definition refers in a strict sense to the kind of careful philological analysis and stratigraphic excoriation of the received meanings of words that are found in good dictionaries. In a looser sense it refers to the establishment of the broader skeletal outlines of a subject or topic, possibly with highlights to the main features of the topic.

Science is about the definition of reality, and this work is first about the definition of science. It is precisely in the dictionary terms stated above that science achieves its clearest vision of reality--definition as a formal process in scientific thought and communication remains a key aspect of its articulation in everyday life. The problem of definition points up the language-problem of science and the role of a kind of formal semiotics and semantics in the understanding of reality. Agreement in theory and practice in any scientific field depends upon sharing and agreement between practitioners of its basic terms and jargon, and the definition in a careful, if not completely precise manner, of the reality it represents. The semantics of science involve the use of terms with clear- cut denotative meanings, implying as often as not a one-to-one correspondence with things in reality and the terms that represent those things linguistically. It implies as well a certain realistic kind of logic that, if it doesn't always follow strict logical rules of inference, it at least implies a practical and historically oriented kind of informal logic involving basic statements of determinism and causality.

Scientific reference works are usually clearly denotative in their language and leave little to the imagination. Perhaps boring to the lay reader and to the humanist alike, they are careful and concise in their parsing of reality in a linguistic manner, tending towards exact or precise definition of terms and their correct usage in contextual settings involving scientific problem understanding, analysis and solution. Scientific reference works written in "plain" language often blend into mathematical formulae and texts that is heralded as a true language of science. It is an important consideration to note that next to mathematical formulation of problem sets and their solutions, clear preference in normal scientific discourse is given to restrictive denotative use of terms and terminologies within fairly rigid conceptual frameworks. This rigor of natural language in the sciences is necessary not only to achieve a maximum of signal efficacy of communication, but it is necessary intrinsically for the clear and concise elucidation and linguistic parsing of reality, in a manner that is conceptually clear-cut and subject to reason and critical judgement without the suspension of reality testing or credibility challenging analysis.

Many basic theories in science are indeed formulated in clear propositional terms, and refer to conceptual sets and complex phenomenal patterns that inherently defy our capacity to mathematically model. Propositional thinking, done in a way that precludes value judgement or conclusive statements, forms the basis for scientific theoretization and hypothesis formulation and revision. The formal use of language in scientific definition of reality depends upon the careful training of the individual scientist, and the accumulation through research and experimentation of a standard and received terminology upon which there is implicit agreement. It is in precisely those areas where there is little agreement and where uncertainty is high that the propositional use of language breaks down, and instead there is the competition between language models to achieve goodness of fit to the problem sets they define. Language models seldom offer in such contexts little clear-cut semantic understanding of the problem sets they attempt to define and reconcile. Full reconciliation of a problem set that is attendant upon full understanding entails the development of a coherent propositional view of the reality it represents in terms that are precise and coordinate.

Until this happens, scientific inquiry remains as much a problem of language to define reality clearly as it is a problem of observation or experiential perception to "see" the problem clearly, or of conceptual understanding about the problem. "Seeing" a problem clearly is tantamount and synonymous with "defining" the problem in clear and no-uncertain terms. Conceptual understanding is critically tied to language function and use--we cannot derive a clear sense of understanding of complex problems in reality without a fundamental dependency upon language, or what can be called a basic linguisticality of our thought and ideas. Language is not deterministic of such understanding, but it is in the semantic function and application of language in the parsing and definition of reality, perceptually as well as conceptually, that such understanding becomes possible and expressed in a communicable form.

The linguistic definition of reality, which constitutes the basis for sound science, brings us to the symbolic function of human cognition and mental behavior, and to the gestalt pattern recognition of complex phenomenal event patterns, that is the basis for scientific recognition and understanding. Language parses reality for us, and serves to semantically and iconographically reinforce those divisions or distinctions of reality that occur "naturally" for us in the first place. If terms are unavailable to describe an aspect or feature of reality, then either a new term must be invented or a different term borrowed to fill in the "hole" in our representation of reality. Language facilitates normal pattern and process recognition aspects of our mental functioning and perception, and furthermore extends our capacity for pattern recognition beyond the realm of the purely perceptual to the general realm of conceptual models and relations.

Propositional definition of pattern sets in reality are the basis for theory building and general understanding in the sciences, and it derives from the ability to draw conclusions about basic operating rules that underlie and at least partially determine the relationships between different sets of phenomena that we observe in reality. Such propositions specify in precise terms the deterministic or predictable order of occurrence in relationships, or failing this, at least describes the complementary patterning of inherently indeterminate relationships in a sufficient manner. Propositional construction requires extensive use of critical reality testing mechanisms that permit us to refine and possibly to contradict our propositions by the use of counterexamples or non-predictive outcomes. They represent a natural logical extension of the basic definition of terms, to an application of entire terminologies in a manner that is consistent in every case and sufficient in every example.

A greater part of such rule-definition in our propositional construction of reality is in accounting for, discovering and explaining countless exceptions to rules that we formulate. Too many exceptions to our rules implies that we must either expand our propositions with a wide belt until it can take in all anomalies, or else abandoning the proposition for a new set of propositions that better reconcile the contradictions that are known. This is known as a normal process in scientific inquiry and development of theory. Theories become time-tested with the accumulation of a body of post-hoc evidence which may or may not conform to the predictive inferences of the theory in the first place.

Scientific definition of reality is guided in certain ways by the natural features and distinctions that are readily observable, identifiable and thus nameable. Much of the language of science stems from common sense definitions rooted in perception and in the naturalistic description of things or events in reality. Naturalistic description precedes and comes before scientific definition that leads into propositional testing and paradigm formulation. The basis of naturalistic description is the particularistic identification of the distinctive features of a unique "thing" or event in reality, and then its at least implicit comparison to other "things" that are either similar or different. Such description, if done consistently and extensively, will lead to the development of identificational terminologies of description, on one hand, and relational taxonomies of things being described, on the other. Terminologies consist of nomenclature that names things in particular orders or sets, along with the type-traits associated or used in the definition of these things. Taxonomies arrange things in particular orders showing relationship and difference between different sets, and the basis for the distinguishing between these sets.

All sciences are based upon the parsing of a certain topography or landscape of the natural world, and involves first the development of topically specific terminologies and taxonomies through naturalistic description of the phenomena that form the substantive basis for the discipline. Part of the necessary inculcation of a member into a particular scientific community is the mastery through extensive and intensive study of the basic terminologies and taxonomies that are most closely associated with that particular field of inquiry. The greater part of preparatory training in all the sciences is dedicated to just such learning of the basic nomenclature and relational structures occurring in a field, and the common problem sets that are associated with that field. All fields are furthermore based upon a strong foundation in terminology and taxonomy governing a knowledge system relating to a particular area.

The standard definition for expertise, in whatever field we wish to apply this term, is in the detailed understanding of the specific aspects to any possible problem set within the field, and a command of the specific knowledge or information relating to such a problem set. In general, an expert's taxonomic and nomenclatural knowledge within the field will extend to far greater depth and detail than the average knowledge of a non-expert. It can be expected that among a community of experts, there will be much greater communicative efficacy of technical terms, and a greater shared ground or consensus of knowledge and understanding relating to specific topic areas of the field compared to any collection of non-experts. This consensus defines the basis for the development of a scientific culture that is tied to the consistent and reliable expertise concerning a certain realm of knowledge in reality.

Thus scientific definition is not formal or abstract in the manner that we see pure mathematics. It is applied continuously to real world problem sets, and it tends to follow the natural topography and stratigraphy that is found in reality. In fact, it is important that scientific definition must follow the natural order of things, and must always in the final analysis, refer back to the naturalistic description of things in reality, if it is to remain a science.

Scientific explanation is the propositional definition of problem sets in reality that follows and refers back to the naturalistic description of things and events in that reality in consistent and non-contradictory ways.

We may state a second generalization that is broadly applicable to the definition of science: Scientific definition, following natural lines of description, tends always towards isolating specificity, or particularity, and thus tends always towards complication rather than simplification. The central role of propositional explanation, therefore, is the simplification of realities that always tend toward increasing descriptive complexity. This forms a natural based dialectical tension in scientific knowledge between over-complication on one hand that is tied to descriptive realism, and oversimplification on the other, that is tied to explanative parsimony and logical coherence at the expense of descriptive accuracy. Another way of saying this is that there is in scientific knowledge always a trade-off between empirical consistency on one hand and rational coherence and non-contradiction on the other, but seldom can we have it both ways at the same time. Yet another way of rephrasing this problem linguistically is to say that in our description of reality, we can opt for increasing communicative efficacy, or functional reliability, but at the cost only of communicative efficiency or formal signal coherence. The basis for this trade-off refers to the inherent semantic parallax of human language used in the representation of reality, and in the fundamental informational uncertainty in our linguisticality. It is not just that different people may mean fundamentally different things within the same language terms, but the language terms themselves, when pushed to their limits, remain definitionally imprecise and uncertain. The symbolic flexibility that is inherent to human language and is the basis for its adaptability in reality, making it wonderful for scientific application, contains an inherent flaw or imperfection that is tied to a proposition about the inherent and ultimate entropy of knowledge in the world.

1. No communication can be 100% certain or completely without noise or ambiguity.

2. Communicative inefficiency in language has both intrinsic and extrinsic sources.

3. The greater the inherent uncertainty of a domain of knowledge or understanding, the greater will be the ambiguity attached to its signal patterning and transmission.

4. In general, there is a human tendency under highly uncertain conditions, to reduce the signal to noise ratio by increasing the strength of the signal, even at the cost of the fidelity of the signal over the noise.

In other words, in highly uncertain situations, internal coherence of received signals will be overemphasized even to the point of exclusion of incoming signals that result in loss of coherence. In terms of gestalt pattern recognition processes, this results in a tendency to superimposed preconceived models or pattern structures upon phenomenal fields or stimuli, even to the point of misrepresenting the stimuli. We can understand this clearly in regard to the paradigmatics in scientific revolution and the observed tendency, more apparent in recent periods, for scientific communities to close their ranks to new ideas or to new definitions of reality that are based upon the resolution of an accumulation of exceptionable and unaccountable information.

This points up a fundamental and inherent limitation of human language to serve as the primary vehicle for scientific thought and communication. If language were completely rigid and its semantic parsing capacity over-determined by the linguistic codification, then science would be essentially impossible and unproductive. The price we pay for maintaining the semantic parallax of language in the sciences, by which we achieve alternation of insight and productivity of theory, is our susceptibility to error and misrepresentation of reality in false or incorrect ways.

Scientific definition stems from the denotative function of making explicit in language what normally remains implicit and intuitive to the background of meaning. Thus definitions are in cognitive function symbolic framing devices that serve to delimit the meaning of a specific term within a specific or general context, by the emphasis of distinctive features and the contextuality of the term within a larger frame of reference, either by both its parent/child relations in a hierarchy, by distinguishing synonyms and antonyms, and by excoriation of the general levels of meaning of the term. Definition and meaning of words in a language normally remains out of consciousness and unconscious to the construction of meaning. Familiarity and experience with the significance of terms is probably traceable to root neural memory associations that are elicited by the term and which neural pattern stands symbolically in place of the term in an automatic or reflexive manner. Consciousness is freed from the task of excavating discrete significances in order to give full attention to the ongoing significance of the term within its naturally occurring sentential context, whether this context is fully elaborated as with written texts or remains to some degree contextually embedded as with a great deal of oral discourse. The sentential frame of reference within which a word is used on the fly remains as much as possible an explicit contextual framework--it is a propositional definition that implies a specific action or inference about reality that then requires testing for fulfillment. Thus by situating a word within a specific sentential framework, the word becomes applicable to reality and real situations such that its inferential value is testable or available for validation.

Scientific definition, which is a normal part of scientific knowledge, serves to make explicit the background context those basic elements of any text or discourse that would remain normally only implicit. By doing so it sets these terms as subjects of other sentential frames serving to make their significance testable in either a general or a specific sense. Ultimately, definition of a term is an entirely relative affair, referring to the definitions and meanings of other terms. Linguistic relativity really unfolds on the issue of the semantic parallax of words, and the linguisticality of all meaning that gains verbal expression. In other words, definitions of terms can only refer to other terms, which terms are situated in their own sentential or propositional frames making them available for testing in a general sense. Thus semantic denotation and definition in an explicit sense refers only to relational values within language itself, in terms of other words within other propositional frames of reference. Unlike mathematics, which validation is inherent to the logical structure of the language, and is abstractly independent of actual experience, natural language about natural events lacks any inherent structures of signification. They are symbolic structures which can only point indexically in some fashion or other to external meanings and experience gained from the natural order of patterning in the real world. Ultimately, the only source of validation for terms are therefore by means of the trace memory and experiential associations that such terms fundamentally or ultimately elicit. And these mental patterns are built up from real perceptual and behavioral experience.

Words only gain significance in their application to real situations or reference to things in reality. The capacity for creating fictionalized accounts attests to both the power and essential weakness of language--many accounts are beyond our ability to test them if they are beyond our experience or capacity for validation. We can choose to accept or reject such propositions, but we have no way of independently confirming or disconfirming their validity or credibility. Again, in highly uncertain situations or environments, there is a tendency to accept certain propositions on the basis of blind faith alone, suspending any critical judgement or objective reality testing through experience. In such a case there is a predisposition to impose frameworks of knowledge and meaning upon behavioral experience that is inconsistent or contradictory to this experience, and at time to even force-fit or conform behavior to meet the expectations imposed by our own frames of reference.

It can be said that science serves through its methodology to render explicit and systematic in our behavioral experiences and observations, in our language and our definitions, what otherwise remains normal and implicit to everyday cognitive processing and reality testing.

It is often the case that a theory may be perfectly logical and acceptable in the treatment and definition of some kinds of problems, or certain major aspects of a problem, on one hand, and yet remain ill fit and insufficient for the explanation of other aspects of a problem that are attached. Such theories are generally revised as partial or intermediate range theories, known as "covering law models." We do not throw out Maxwell's wave-field theories that are perfectly suitable for the description of electromagnetic properties and fields, because they are found not to be applicable in a direct or necessary way to a general relativistic accounting of physical reality. We assume that Einstein's theory of general relativity is more basic and general and encompasses a broader range of phenomena that Maxwell's earlier equations cannot fully or sufficient explain. At the same time, we accept the limited truth value of Maxwell's equations in the precise definition of certain kinds of phenomena occurring in reality.

We may say in general that all scientific theoretization tends towards over-generalization, or what can be referred to as over-extension of reference, and in the process, all theories, to the extent that they are correct, tend in the long run towards specialized compartmentalization, or a strict determination of reference within a context that becomes bounded by more general statements about reality.

Propositional thinking is therefore the foundation for the formation of paradigms in scientific communities, and for the process of paradigmatic dynamics affecting the acceptance and rejection of alternate theories. Propositions that should permit some degree of reality testing through experience, (in scientific terms, controlled experimentation), by posing explicit inferences within sentential frameworks that are available by means of their communication to independent validation and signification. At the same time, propositions can foster a framework of understanding that invites a sense of security about our knowledge structures that require subsequent reinforcement to maintain. A paradigm can be said to be a body of propositional theory that is built up around an agreed upon terminology that defines reality in a given subject area in certain precise ways.

It is apparent from this digression about scientific definition that science is not just about the saying, but also about the doing, and the dialectic between thought and action in the development and history of scientific research and theoretization is clearly evident in every case of its practice. Science sets about to systematically discover through exploration, or to demonstrate through controlled experientiation, or rather experimentation, the validity of propositional statements made by scientists regarding the phenomenal patterning of reality at whatever level this may be analyzed upon. The doing of science situates the meaning structures of scientific definition within an organic and experiential frame of reference--furthermore this frame of reference has certain standards and measures attached to it that it renders this experience fairly reliable in terms of its replicability and its representation of reality, and makes it a fundamental part of the common stock of knowledge. There is perhaps no other field of endeavor outside of science where thoughts and actions, words and deeds, are so closely interlocked and are so studied and carefully coordinated.

Again, though, the behavior of a scientist in terms of research is not fundamentally different from the behavior of an average person who is attempting to learn something not previously known. We test our propositional structures of meaning in reality, especially in a subjective sense, everyday through our conversation with other people and through our interactions with the world as well as through our reading and perception of media. We have an inherent motivation and need to test our propositional inferences, and to construct these propositions about reality. These needs are critically tied to our capacity to learn from and adapt to dynamic environments and settings where change is continuous and most often unexpected. Again, the critical difference between scientific practice and normal human behavior is a matter of degree and studied refinement that allows the same basic processes of symbolic reality testing and propositional construction to proceed in a much more explicit and controlled manner than otherwise possible--in a manner that puts a premium upon objective communicability of meaning and upon its testability through independent experience. The constructive semantic and inferential function of language in science is the same function it serves in everyday experience--albeit in a more strictly denotative manner. The consequences in terms of the mapping of reality, of the construction of some sense of worldview that mirrors or models complex realities in the wider world, permitting a symbolic coordination of behavior of a person from day to day and year to year, and between different people over both space and time, are the same with science as they are with everyday common sense. The intuitive functions of embedded meaning are the same for the languages of science as they are for everyday language, except that the former tends to be defined denotatively while the latter remains mostly connotative and defined through use and application.

There is little room for emotional reaction or impulse in scientific work, though we can say that a scientist is a passionate person in the pursuit of new knowledge and understanding, or in the invention of a new device that permits the expansion of reality by some increment. A scientists thus normally sacrifices subjective indulgence of experience for the objective coordination and control of experience by careful and planned ratiocination. When a scientists acts in the field, there is usually a clear accounting for why the scientist acted in terms that are logically tied to some propositional framework. Thus it requires a tremendous discipline to become a scientist--a discipline to control and channel one's emotions and impulsive drives and aggression towards deferred ends.

Understanding the linguistic role of semantic definition in scientific thought and its constraints upon action in scientific method, points up the relationship of scientific thought and activity to normal human thought and activity in everyday settings. The same basic mechanisms of symbolic framing are employed in both sets of activities--human cognitive functions serve the same interests and function in the same manner in both instances. The critical difference between the two are the degree of elaboration and rigor that is brought to the former and the degree of intuitive contextuality and generality of function that characterizes the latter.

Science can be seen therefore as an esoteric form of symbolic exercise that is more differentiated and specialized in function that normal human symbolic behavior. It is systematically and deliberately controlled to yield consistent results in a regular way, or else to discover exceptional patterns in an unusual manner.

Science as a form of systems theory and operational methodology, whatever form this may take in knowledge domains, is based upon this requirement of scientific knowledge that it is more rigorous and elaborated in the form of expertise than is general or normal knowledge practices. A scientific approach may be systematically applied to any field of endeavor or knowledge--requirements are in its systematicity and, more importantly, in its heuristic success in being able to solve central problems that characterize a field of inquiry.

The basis of scientific research is question asking, and posing a question is a way of drawing a symbolic frame that contains or expresses one or more unfinished inference structures, inviting some solution to this structure. A question is a kind of unfinished proposition, in which the reality testing function implied in all propositional statements is emphasized and made explicit by marking in the question framework. A normal proposition poses an answer to be verified or not on an implicit level--a question posing proposition demands an answer to be given on an explicit level.

The question posing and answer seeking nature of science as a heuristic problem solving system has not been fully addressed in the literature. We abound with questions, but we seldom question our own question asking ability. Questions invite or provoke some kind of complementary response. In science, we do not normally ask questions of one another, but rather we ask questions of our data, and of the reality that lies behind the data and from which the data emerged in the first place. Questions are tied to an innate human proclivity to explore the environment. We have an inherent preoccupation with our life-world upon a basic level. Our existential sense of security rests upon the perception of a world that is ordered and "safe." Our curiosity is a function of our intelligence, and our ability to pose questions, even behaviorally, about our environment is a function of the symbolic structure of this intelligence. The capacity to ask questions, I believe, rests in the ability to transfer meaning from one symbolic frame to another, remote frame, that has no direction connection or immediate, mechanical relation. The capacity to shift frames from one context to another creates on one hand a tendency towards closed-minded superimposition of preconceived stereotypes upon our field of awareness. On the other hand, if this pre-conceptioning can be suspended, however temporarily, then it is possible to experience reality with a kind of intuitive naivete and unbiased involvement upon basic levels of perception and cognition--under such conditions questions arise almost naturally if we seek to make sense of our experiences.

A question in a technical sense is an inference frame that does not answer itself or does not put forward an inferential proposition about reality. In a sense it is an incomplete proposition, lacking a referential subject or object. Questions are usually marked by some form or word, such as the "wh" words in English. English and probably most Indo-European langauges have some version of the who, what, where, when, why and how questions. On the other hand, the semantic implications of these kinds of questions may vary considerably between languages and cultures. Some cultures may not ask why questions in the same way as we might expect, and if such a type of question were put forward, we might be surprised to receive an answre indicating a what or even a who, where, when kind of frame. This is not surprising if we understand that what may be obvious to us may not appear so obvious to others, and vice versa.

Science is restrictive in a fundamental sense of question asking ability--science does not normally ask or seek to answer "why" kinds of questions. An answer to a why question would be framed in a "how" manner. Answering how something happened speaks to a form of efficient and mechanical causality or determinism that does not provide a full "why" explanation. Ultimately, "why" type questions lead to unanswerable speculation upon another level. I believe it can be demonstrated ultimately and categorically that science is not operationally capable of dealing with why kinds of questions except in a most local and limited way. Instead, a how kind of answer provides a kind of explanation to a problem for which there appears to be some kind of solution. Why kinds of questions again invite a form of rationalization about reality that entails the substitution of some form of symbolic construction or framework for an answer that is more directly rooted in the experiential foundation of reality. In this we may see a simple way for describing the difference between religious leaders, whatever the religion or faith, on one hand, and working scientists on the other.

Two aspects of the normal affairs of science are not given great attention or credence, but are nevertheless normal and critical processes in scientific method. The first is the emphasis upon individual speculation as a productive means of conducting scientific inquiry; the second is the use of interpretation in the analysis and synthesis of empirical information. These statements will be challenged because they seem to contradict a received view of science as rigorous, studied and systematic in every way. Such words like speculation and interpretation become taboo in science because they admit processes that lack the discipline of science and that make scientific inquiry soft and related to other forms of humanistic inquiry.

Scientific speculation can be said to be a kind of informed hypothesis formulation in the fact of uncertain or unknown facts. We are all naturally given to speculative reasoning in situations in which we are unsure of events or outcomes. Such speculation provides us with a means for filling in the gaps of worldview and our cognitive maps when such uncertainty or a lack of knowledge arises. Speculation is really a way of proposing alternative hypothetical constructs, or possible scenarios or frames, within which we can test known realities for best fit. The problem with speculation seems to be that such a method provides no direct means of proof or demonstrative testing of reality. Speculation begins with known facts, and then can grow wilder and wilder with the hypostatization of unknown realities. Speculation can therefore be said to be a form of counterfactual hypothesis generalization that deal with conditional realities.

Interpretation is related to speculation in a manner that deduction is related to inductive inference, and this is more than just an analogy. Interpreting data in the face of possibly unknown facts allows us to think about the data in different frameworks, and provides increased understanding about the data within the structure of various frameworks. The interpretation of evidence follows an attempt to make facts fit when all the pieces of the puzzle are not available or are missing. It allows us to try to guess the image of the puzzle even if it is only completed by a small percent.

It is found in pattern recognition tasks that speculation and interpretation are basic and natural responses to the presentation of relatively unpatterned or highly ambiguous figure ground relationships. Speculation and interpretation are in these tasks complemented by the superimposition of mental imagery and forms derived from the imagination. Speculation usually involves the entire frame of reference, while interpretation usually at least initially tends to focus upon minor details within the larger framework. Much of this speculation and interpretation appears in the initial stages to be erroneous and purely imaginative, but it tends to lead to a "priming" of the mind to be able to recognize and piece-together slight cues or clues so that, in the case that an image can become even partially more resolved, a more realistic solution becomes available as a result of such studied speculation and interpretation. Only in cases where the superimposition of preconceived forms upon the data, and the perseveration of these forms in spite of the increasing resolution of the image, does such speculation lead to total failure to perceive or conceive of the true form embodied in such ambiguous backgrounds. This is attributable to a kind of neurotic frame dependency that cannot tolerate or play with ambiguity.

There has been much in the development of a meta-systemic perspective in natural systems theory that has originated in speculation and interpretation. The process has been repeated and gradually refined around central points, and has led the way to investigation in certain directions that has opened the door to new insights and understanding of such systems at different levels. Speculation in the initial stages at least permits almost a total free play of ideas without constraint or consideration of plausibility or probabilities. The only constraints to such speculation, from a scientific standpoint, is that the plausibility structures of normal reality are not context or strained too far, to the point that we are engaged in the production of science fiction and fantasy, rather than being involved in a critical dialog with reality and facts.

Speculation and interpretation are to be expected in a new and nascent field of inquiry such as natural systems theory. This perspective is in fact relatively new, though it has been built upon the accomplishments of the sciences. It follows that the early stage of the development of natural systems theory should see a tremendous amount of speculative and interpretive activity that would be, if not completely wild, at least not yet fully domesticated.

The basis of informed speculation and studied interpretation is the development of frames of reference and back-grounding of the subject being undertaken. It entails the construction of alternative plausibility structures that permit inferences to be drawn in directions not otherwise permitted. If such and such is true, then this that and the other thing become plausible as well. The construction of such plausbility structures are guided as systematically as possible by the application of sound reasoning or rather a form of possibilistic logic and a kind of mathematical ratiocination.

Informed speculation requires several preliminary conditions. It requires a certain basic expertise and informed knowledge of the facts and field within which speculation is applied. It requires the capacity to temporarily suspend the sense of credibility of certain basic propositions, or the capacity to at least call these basic propositions into critical question. I believe as well that informed speculation requires a kind of intuitive understanding of both the data and of how the data may fit together in previously unseen or untried ways.

Like speculation, accurate interpretation also requires a degree of preparation and preposturing of background knowledge to permit the correct relationships to be drawn from and to whatever limited data base may exist regarding a particular subject. It is a kind of detective work that requires both detailed observation and long-range deduction and the construction of alternative frameworks or scenarios by which to fit the available facts. Parsimony applied to interpretive frameworks would entail the inclusion of as few extra bits or plausible counterfactuals to the interpretation of the evidence as possible--in other words, though the evidence may be incomplete and insufficient, it must be regarded as complete as possible, and the best interpretation would be the one that sufficiently explains the available evidence without the demand for more evidence being made or met by hypotheticals. In other words, the data in such situations should, as much as possible, be self-explanatory. Short of this, the next best arrangement is that the data can be organized in a meaningful manner that allows us to frame new questions and that permits us to conduct explorations or experiments that leads to the acquisition of new data, the discovery of new pieces that fit the puzzle.

We can see that while speculation is allowed to roam rather freely over hypothetical terrain that is bounded only by structures of plausible inference, interpretation is more closely constrained by the available evidence and the fit of the facts to the natural framework in which they occur. Of course, interpretation and speculation can be seen to be mutually and dialectically constraining of one another--speculation is based and defined by the interpretations we give to events and evidence, while interpretation is permitted some degree of freedom by means of a speculative mode of hypothetical construction. It follows that we should not attempt the one without performing the other in the development of new insights or new fields of understanding.

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There is a kind of problem solving that I would call creative or innovative, that leads to new insights. This is a kind of problem solving that seems to me rarely taught in schools, perhaps because, given our cultural conventions, it is thought of as being something hard to teach. Most often we ascribe certain people with a knack or a natural gift or talent if they appear to be especially good creative problem solvers. There is a tendency in creative problem solving, somewhat like dreams, to apply alien or foreign forms to the solution of a problem. I believe this kind of problem solving was characteristic of Leonardo da Vinci, for example, as exemplified by his play with ideas and doodles in his note-books. There is a experimental imagination to try new things and to look at old things in new ways. That this may frequently lead to new insights, even as a matter of chance, should be in itself unremarkable.

The qualities that we find in creative problem solving are intuition, or what I would call a non-verbal form of thought and analysis that we bring to the understanding of the world, imagination, including the ability to create alternative constructs and to "mix metaphors" in a manner that would result in creative insight or alternative constructs. Also, I believe, freedom of thought and action, including free play of ideas, seems to me to be critical to the cultivation of creative problem solving, and this is a quality which is perhaps rarest and hardest to find, given the common tendency in society to restrict freedom and even frustrate its expression. I would add a fourth quality to the cultivation of creative problem-solving, and this is a certain inherent sense of interest including responsibility and seriousness that is brought to the problem situation in the first place, and that is necessary to carry the problem through to successful solution in spite of perhaps an endless round of frustration. Creative problem solving may demand a certain kind of freedom from constraints, but it does not mean that it is merely play and anti-structure. It entails a kind of deliberate effort and work, what I would call a focused concentration upon the problem set, that provides the necessary energy to achieve its resolution.

To a great extent, the successful development of metasystems theory depends upon the cultivation of these qualities associated with creative problem solving, and creative problem solving as a general and legitimate methodology is given more credence in this approach compared to the conventional sciences that stress directive thinking and analytical problem solving.

Einstein, in his autobiographical piece, clearly highlights the importance of some of these qualities to the challenge of intellectual problem solving. Mastery of a field of expertise does not preclude interest in other, often related fields of inquiry, and must be accompanied by the capacity to think beyond the constructs and models that inform such a field in a critical and open manner.

These same qualities are those that I have found manifest in the development of metasystems theory, almost without exception, and I believe most of my life has been characterized by this kind of creative problem solving applied to one area of activity or another.

We must inquire a little further into the nature of intellectual constraint. In general I would say that it is a form of limitation that is brought to our thinking, perhaps for a variety of reasons. Belief, superstition, false consciousness, ideology, all present forms of intellectual constraint to our thinking, and I can imagine other forms of symbolic dependency as well. We can speak of various forms of fetishes that we may have, as well as what might be termed obsessive or compulsive fixations. Distraction is a great frustrater of intellectual freedom, and that is why real thinkers almost invariably seek solitude and silence in order to think without disturbance or noise. If people live with behavioral limitations, structurally or socially reinforced in their own lives, then this will translate into some form of intellectual constraint as well. Francis Bacon spoke well of these kinds of constraints when he referred to the different kinds of idols of the human understanding--idols of the tribe, of the den, of the market and of the theater. We must be capable of detaching ourselves from a strong sense commitment to any particular mode or object of interest, and at the same time, of fully and unreservedly involving ourselves upon some focal problem set without a sense of reservation or distraction. This may be harder to accomplish than we think or wish, and we may in the process find ourselves our own worst enemies of intellectual freedom. For the repression we find and place in other people, are those that come from within ourselves, often in an unconscious manner.

True intellectual freedom entails, I believe, a general non-attachment to material things or circumstances. At the same time, it entails a certain release from concern with petty or day-to-day matters, and thus also some optimal level of material comfort. It is difficult to think clearly if one is shivering from the cold or burning and sweating from the sun's heat. Intellectual freedom entails a detachment from social roles, identities and often even social relations, and thus entails some sense of general withdrawal from the parade and vanities of human affairs. Thus intellectual freedom entails the nurturance of a certain simplicity and, I believe, humility of lifestyle that precludes self-aggrandizement or preoccupation with petty ego-oriented attachments. At the same time, it is equally true that if creative work is to move ahead, the contexts, materials and tools must be available and of ample amount for such creativity to gain full expression.

I also believe that at some level intellectual freedom entails its communication within a larger community that will be minimally tolerant if not supportive of such freedom. That freedom may depend upon communication comes as somewhat of a paradox, as it would seem that communication can be the principle vehicle for the shackling of freedom and its restriction. Thus communication must essentially be open and reciprocally given and received. The communicative aspect of such freedom locates a sense and reality of such freedom in a social landscape, as a social process, in the articulation and advancement of knowledge especially.

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Observational inferences and the result of structured research has led me to conclude that underlying knowledge cultures are cognitive substrates of meaning and order that regulate behavior and belief structures within these fields. These cognitive foundations of knowledge vary considerably between different disciplinary fields, and lead to different kinds of consequences and outcomes. Generally, I conclude that there may be two different forms of problem solving that are based upon the cognitive patterning of the brain that can be utilized in different knowledge systems, and some knowledge systems tend to emphasize one form of problem-solving activity, especially in terms of formal training, than the other. I believe that these fundamental differences may constitute the basis for the stratification of knowledge between C. P. Snow's "Two Cultures" of the sciences and the humanities. To a great extent, these two cognitive orientations can be said to be mutually exclusive, at least in the sense that the success of one kind of problem solving tends to come at the cost of success in terms of the other. This does not mean that people can normally and frequently function in both modes in tandem or simultaneously, but I believe that the inter-functioning of both systems together may result in increased levels of cognitive dissonance that would interfere with the effectiveness of either system.

I would define the two sets of problem solving that characterize and underlie the Two Cultures of academia as being primarily the differences between holistic and analytic approaches to knowledge organization, as well as between different levels and degrees of restriction and constraint of the symbolic encoding of the language that is applied to different domains of phenomena. The former, holistic problem solving can be seen as expansive and elaborative, leading to the contextualization and interpretation of information, while the latter form of analytic problem solving can be said to include a systematic restriction and reduction of information to a narrow range. The former can be said to seek resolutions and identification of contradiction and dilemma found in natural patterning, the latter form of problem solving takes the characterization that Thomas Kuhn applied to it, that of puzzle-solving that has a finite, specific solution to a delimited problem set. Differences between the two kinds of knowledge systems can be said to be recognizable in relation to both the organization of knowledge, its disposition and function, and to the application of knowledge to the problem of the unknown and uncertainty in reality.

I have come to recognition of this in terms of my own personal life experiences in attempting to develop natural systems theory and apply various aspects of this work across disciplinary boundaries. It forces me to attempt some kind of formal reconciliation of the two sides of this model in terms of providing a means for both approaches to interfunction effectively and at least interference to one another over time. I am not sure if this is possible in situations where one or the other mode of problem solving has been hyper-developed, whether in psychological terms of an individual's habitual cognitive functioning, or socially in contexts where one kind of problem solving or another is expected and constrained in the social patterning. In the best of possible worlds, opening up one or the other form of problem solving to make room for the occurrence and development of the other would be desirable, at least in theory.

It is said that we use only a portion of our brains. I do not know how true a statement like this really is, or if it can be truly proven or disproved. It is possible that we are normally using most of our brains most of the time. If we are to get at the mystery of Einstein's problem solving intelligence, what many consider to be his genius, then I doubt we will find it in the formaldehyde of his pickled dead brain a half century after his demise. We may not even accomplish this if we attached electrodes to the brain during his lifetime.

What seems apparent to me is that we use our brains in a habitual manner on a normal basis, because such habitual patterns are the simplest and most cost efficient patterns for the brain to follow. It strikes me too that in such a case, neural patterns would be laid down or rewired in a manner to reflect as much as possible this habitual pattern, or any alternation from it that may occur as the result of learning or change of circumstances and experience. We fill up our brains with knowledge like so much information on a floppy disk. We must at some point in our lives, perhaps in our middle age when brain cells quite growing so rapidly and begin dying more quickly, reach a stage of cognitive equilibrium of brain function such that our experiences in life and our noetic patterns are fairly stable. Any perturbation of such patterning would be expected to result in compensatory mechanisms serving to reestablish an equilibrium. If we pile more junk information in on some level, then a corresponding amount of old outdated junk information must be recycled back out again. One anachronistic brain pattern must yield to a new and more important brain pattern. Dreaming may have something to do with this, as well as with other cognitive housekeeping functions such as integration and rehabilitation and symbolic evaluation.

The life and inferred existence of the unconscious psyche seems equally important to me in this consideration. Much learning of new information and its embedding into the cognitive substrate of meaning in our existence must occur on a fundamentally unconscious level, and much of this unconscious processing and direction occurs without our own explicit awareness of its happening. I do not know how much we are slaves of our own unconscious psyche. It is clear to me that one manner we have of being duped and manipulated by our psyche is in terms of our self-illusion of our own rational control and intention. It must be wondered how such rationalization of purpose and intentionality in our lives is nothing but an ego-defense mechanism serving to mask our real unconscious intentions, which would be presumably more crass and base in desire than we would want others to know or deal with. I do not know if this kind of internal control mechanism can ever be proven or disproved in any clear empirical manner, but it does make for meaty psychoanalytic interpretation.

Another way of putting this is to state that the brain may have multiple control mechanisms that may function frequently only in an indirect and non-obvious manner. These mechanisms would serve to organize, order and define brain processes and cognitive function in certain basic ways. Furthermore, these mechanisms may be competing for control in the brain over the life of the mind and its subjective and behavioral consequences upon the body. It is perhaps easier to see such control mechanisms in the brains of non-human mammals and other animals than it is to find it in our selves, so fraught are we with the illusion of our own exceptionality in the natural order of things. Instinctual patterns, obviously brain based, leading to fixed action patterns and predictable response systems, are an example of this kind of control mechanism or system in, lets say, a dogs brain. The fact that most dogs behave in similar circumstances in a similar, often predictable manner, entails that dogs must share similar structures of cognitive control over their behavior, and these control mechanisms are not only to be seen in a Pavlovian manner of stimulus-response conditioning. The fact that dogs do not always behave in a predictable manner tells us as well that control centers in dogs may not be that predeterminative or fully determining at all times as it might be for, say, a rattle snake. Even snakes with relatively small and primitive brains can be seen to behave in case studies in ways that do not preclude some kind of arbitrary self-control in certain situations. It appears under certain circumstances that they may be capable of deciding whether to strike or not, depending upon the assessment of the situation and the response patterning of their intended victim, and even possibly how much venom to release when they do strike.

Humans do of course have self-control, and problem solving demands that this self-control be coordinate to and active in relation to a range of cognitive processes relating to the determination of a solution to a problem. Our own autonomous self-control seems itself to be an emergent property of our overall sense of self as a unique and independent organism in life. In other words, it appears to emanate in our consciousness as a result of our overall organismic integration and self-awareness. An interest case in this regard is the not uncommon possibility of our rendering our sense of self control to the external social control of another or to a social situation in which we are involved and that we find to be compulsive behaviorally regardless of our psychological reactions to it. Hypnotism and crowd response are examples of this. Self conscious control mechanism, that appear to repress certain feelings or impulses in a normal manner, may be obviated or temporarily suspended in relation to external stimuli or circumstances. There is a sense that field-dependency and neurotic attachment to external stimuli may be related to this process. In any such context, it appears that sense of self as a independent, whole organisms breaks down or becomes lost in relation to a situation or particular behavioral setting.

On the other side of the coin are the obvious instances when self controls are defeated by libidinal impulses or aggressive tendencies that appear to arise internally within an individual, but which are externally referenced and made relevant to external stimuli and response patterns. Conscience, which may involve a sense of responsibility, of respect, of normative valuation, of psychological restraint or repression, of shame or guilt, and possibly also of empathy and concern for others, seems to me to be a basic overall self-control mechanism that some might claim represents a societies internalization into the psyche of social sanctions and proprieties. I believe that Freud termed this the superego, though I believe the term superego has other idealized connotations of an exaggerated sense of self that may or may not be a control mechanism over the psychological integration of the individual.

I suspect that other kinds of internalized control mechanisms may occur as well, which serve to govern many aspects of our noetic response patterning. Thus the content, quantity and quality of what we think and how we think may effectively be managed in some as yet unknown manner. These may influence both conscious awareness and response as well as unconscious patterning. Control mechanisms may occur in focal areas of the brain, or may be distributed and implicit to the organization of brain function and pattern itself, such as the morphological partitioning of brain function between the hemispheres, intermediated by the corpus calustrum and other nervous subsystems. The brain achieves partitioning of function in a complex manner. It appears that this partitioning is somewhat variable between individuals, and yet also probably genotypically based.

It is beyond the scope of this preface to go into further details of this aspect of human knowledge and its functioning. Implicit to the concept of the two cultures in this regard is the idea that knowledge systems are situated within, and are intrinsic aspects of, larger cultural realities that are rooted in behavior and cognitive patterning that is both shared and interactive. Culture can be defined in this regard as something that exists, at least for the time being, within the brain of the informant, as an organization and summarization of life experience within some social framework. It is not so much a mental concatenation or concoction, so much as it would be the mental machinery for such concatenation and formulation of meaning. To be effective, culture must be active and adaptive, on-going and current, such that there is continuous feedback and reinforcement of the mental patterning, almost on a daily basis.

We can understand therefore the syndrome of culture shock, adaptive response disorders, and other kinds of similar mental dysfunction, as the result of mental-environmental displacement that leads to dissonance and discord between the internalized apparatus of the brain and the external world in which the brain is situated. This occurs even on very basic perceptual and cognitive levels of brain function, must less on more abstract or evaluative levels. It is obvious in terms of second-language acquisition and the capacity to recognize and response effectively to new sets of meanings occurring in new kinds of signals.

These are important and vital considerations when it comes to understanding the ontological and epistemological status of knowledge in the world in a manner that can be said to be anthropologically significant and realistic. The concept of mind implies knowledge and the meanings that knowledge encompasses. It does not exist outside of the brain or independently of it, except in the alienated and objectified sense of its social construction and distribution in society. Thus, whether we are interested in the particulars of microbiological research in one place or other or not, we can go to practically any microbiology department in the country and find very similar knowledge models and patterns being articulated in the same basic terms. And these knowledge will not be identical to the kinds of knowledge articulated in relation to any other aspect of biological sciences. To argue for brain based organization of human consciousness, its control mechanisms and its articulation and expression in a larger world, is to impose a certain condition of anthropological relativity upon all such knowledge systems. They are an intrinsic part of the definition of a culture, and they are culturally embedded and embodied in the life-world of the individual culture-bearer. They guide behavioral response patterning and social interaction and process.

The rough relationship therefore between the brain and the mind can be characterized by a digital analogy to the relationship between the hardware and architecture of a computer and its software, or the programming language that is used to encode and organize the functioning of a computer. We can see that a computer does not function without both sets of components, and that a brain without a mind is as if a dead organ. In a similar way, the software of the brains mind can be said to be socially and culturally encoded in such a manner as to allow there to be an effective interface and communication between different minds. Just like computer software, the mind is written in the script of a definite language with its own syntactic rules of ordering and articulation. These scripts are culturally defined.