Carlson

Carlson-Sabelli, L, Sabelli, H., Patel, M, Sugerman, A and L. Kauffman. Process method: II. From process thinking to the empirical study of coexisting opposites. Systems thinking, globalization of knowledge, and communitarian ethics. Proc. International Systems Society, Seoul, Korea, 1997, pp 976-988

Process method: II. From process thinking

to the empirical study of coexisting opposites

L. Carlson-Sabelli, H. Sabelli, M. Patel and AS. Sugerman

Chicago Center for Creative Development,

Rush University and University of Illinois at Chicago.

2400 Lake View Avenue, Chicago, Illinois 60614, U.S.A.

Abstract

The process method systematically measures the 4 features of processes postulated as universal by process theory: (0) Flux is measured as statistical entropy. (1) Action is measured as rate and as asymmetry. (2) Information is measured as the coexistence of complementary opposites, attraction and repulsion, acceleration and deceleration. (3) Organization is measured by the duration, dimensionality, and pattern of complexes of recurrences --transient, multidimensional and sparsely recurrent patterns generated by complex interactions, as contrasted to stable, low dimensional and recurrent attractors. In Part I we illustrated the application of some process methods to the analysis of time series. Here we discuss process thinking as the foundation for these and to-be-developed methodologies, and focus on techniques to study the coexistence of opposites, that the theory views as the most fundamental feature of both objective and subjective processes.

Key words: asymmetry, cardiac physiology, co-creating, complementary opposition, complexes, entropy, information, process theory, sociometry.

Process thinking is often intended but not practiced: Science, mimicking social ideology, has been dominated by the celebration of permanence and order, and the denial of ongoing creation. A Platonic view imparts permanence with import, and identifies change with chaos and lack of consequence. Current scientific methodology portrays complex and evolving processes as mechanical or accidental. Life and its evolution are explained as the result of fortuitous accidents, because processes, according to standard thermodynamics, spontaneously decay towards equilibrium and disorder ("entropy"). Classical, statistical, relativistic, quantum mechanics allow for time reversal, and imply either strict determinism or probabilistic contingency. Human behavior still is largely explained as determined by human "nature", or as a free choice. From physics to psychology, analysis is identified with method, theory focuses on invariance, order, determination, and the conservation of energy, when in fact the simplest entity, the Planck constant, has the dimensions of action (action = energy x time), implying change. A physics of cosmological evolution has developed only in recent decades, one hundred years after biological evolution was demonstrated, and assumes a linear rate of expansion at odds with the non-linearity of complex processes. Even system theory and the new science of dynamical systems, popularly known as chaos theory focus on stability and its maintenance (homeostasis, homeokinesis); attempts are made to reduce novel and complex physiological processes to low-dimensional and stable attractors, and failures are attributed to the inadequacy of the data rather than of the model. There is a failure to understand how widely used methods imply assumptions that actually prevent the detection of creative change.

Process thinking

It is currently fashionable to take newer for better, but adopting a process perspective, let us examine science as a historical process. Science originated with a process perspective, viewing matter as alive, energetic and creative. This was Greek physiology, i.e. natural science. The correlation between the length of chords and musical harmony was the first, and for a long time the only, numerical law of science. It illustrates a manner of thinking that combines empirical data, mathematical analysis and theoretical formulation, and that attends to physical and psychological issues, without giving primacy to any one of them.

Born with a process perspective, science, in a significant alternation of opposites, developed through the separation of the physics of "inert" matter from biology and psychology, and the adoption of static, mechanical, and idealized models. "Physiology" became confined to biology. Although mechanism dominated scientific discourse (and supernaturalism dominated public one), process thinking reappeared at crucial times in history: during the Renaissance (Bruno, Pico, Nicholas Cusano) and in nineteenth century with biological evolutionism (Lamarck, Darwin) and dialectic philosophy (Hegel, Marx, Engels), although both Darwinism and Marxism stressed struggle rather than the coexistence of cooperation and conflict. Process perspectives are gaining primacy in the twentieth century. The complementarity of opposites has been formulated within the context of quantum mechanics (Bohr), psychology (Freud, Jung, Riegel), and systems science.

To operationalize process thinking into a practical method, it is necessary to ground it on empirical research, and to formulate its principles clearly, and, whenever possible, mathematically. In the last decade, such a formulation of process thinking has emerged within the system community. Process theory operationalizes process thinking through the methods and concepts of mathematical, biological, social, and psychological dynamics. We refer the reader to companion articles in this volume that present the theory in a non-technical form [Sabelli et al, This Volume] as well as a mathematical equation [Kauffman and Sabelli, This Volume]. [Sabelli et al, This Volume] as well as a mathematical equation [Kauffman and Sabelli, This Volume]. The theory provides specific methods that have been applied in medicine [Sabelli et al, 1994], psychology [Sabelli and Carlson-Sabelli, 1991], and sociology [Sabelli and Carlson-Sabelli, 1995].

From process thinking to Process method

The process world view is much more complex than simply stating that things change, or that they are in "dynamic equilibrium". From its inception with Greek physiology, process thinkers have postulated 4 universal patterns -flux, flow, opposition, and creation. Methodologically, this implies to analyze data as to reveal a minimum of one (temporal change), two (opposition) and three (structure) dimensions, never assuming a linear model.

(0) Energy flux: Everything spontaneously changes. Change is not only uninterrupted; it is also self-propelled. Matter is alive. Everything is "fire". In contrast, mechanics regards matter as inert, changed only by external action.

(1) Time: processes evolve in one direction, "as a river" (Heraclitus), in contrast to the reversibility of time postulated by classical, statistical, relativistic, and quantum mechanics -- irreversibility has been incorporated by Prigogine in far from equilibrium thermodynamics.

(2) Opposition: Opposites coexist, as illustrated by matter and anti-matter, positive and negative electrical charge, feminine and masculine, and attraction and repulsion from physics to psychology. Harmony arises from the tension of opposites, "as in the bow and the lyre" (Heraclitus). The union of opposites is excluded by traditional and mathematical logic, while process philosophers (Whitehead, Seldon, Rescher) largely ignore it. Mechanics postulates the mutual neutralization of opposites. Organicism views systems as integrated whole, denying the coexistence of cooperation and conflict. Relativism and deconstructionism deny objective oppositions, and misconstrue opposition as a conceptual construction.

(3) Creative evolution: the interaction of simple processes creates novelty, complexity, and diversity. The simplest creations are co-creations generated by the separation of opposites (bifurcations, such as catastrophes) or their combination (system formation). Creation is an ongoing process. In contrast, equilibrium, circular, random and chaotic models have dominated scientific discourse. Classical and relativistic mechanics imply strict determinism, while statistical and quantum mechanics imply probabilistic contingency. Determinism denies ongoing creation, while contingency trivializes it, without really offering any explanation for novelty or complexity.

Process Method

The process method aims at the systematic measurement of these four patterns, by using, modifying, and integrating dynamic techniques ranging from mathematical dynamics to psychodynamics. Our current methodology is based on the assumption that one can gain some insight into the nature of simple and complex components of variation by studying processes in frameworks of 0, 1, 2 3, ... many dimensions. Process theory postulates two universal features of process, action (defined as in physics, as the product of energy x time) and information (defined as complementary opposition). Action is asymmetric (temporal order) and thus constitutes the simplest case of Pasteur's cosmic asymmetry, which we take as the most fundamental law of nature. Information is a difference, and thus includes the symmetry of opposition. Action and information co-create organization of greater stability and dimension, starting with the tridimensional structure of matter, and higher dimensional, less stable forms of organization, such as brains. The evolution and development of organization depend on past evolution and create novelty. Actions (1) combine into lattice-shaped processes of bifurcations and recombination; (2) are paired with a complementary opposite (inverse); and (3) have a topological form, meaning that they can adopt a wide range of geometries without discontinuity, and experience discontinuous change as result of a continuous change in some quantity. Thus every process has one dimension of action (because energy and time are inseparable, as illustrated by the Planck constant), two dimensions of information (because complementary opposites determine a two orthogonal axes), and three or more dimensions of organization. Thus an irreducible framework of six dimensions is a universal form that repeats in multiple ways in all respects and at all levels of organization (homology). Such a cosmic form serves as both the origin and the attractor of evolution. These are not philosophical speculations. They are scientific hypotheses because they are experimentally testable (as required by Popper), empirically grounded on observation, clearly formulated (in fact, mathematically), and practically applicable.

Flux and Flow

0 dimension: statistical measures of flux: Variation is equally or more important than order. The process method studies statistical variation as a measure of flux. The process method aims to describe the form of variation, not just to measure for the sole purpose of determining what differences between groups are statistically significant. Histograms are sufficient to differentiate most chaotic series from random distributions, and cardiac data from both of them. In contrast, biotic patterns generated by the process equation generate histograms similar to those observed with cardiac data. In contrast, static thinking employs statistics to reveal repeatable order by reducing variability, which is viewed as experimental error and/or as random and meaningless.

1 dimension: time series of action: To study processes it is necessary to obtain longitudinal recordings, instead of snapshots. Observations at one point in time, no matter how sophisticated the measurements, cannot portray processes. Processes are flows of energy in time, i.e. actions. Action is defined in physics, as the product of energy and time. Process theory attempts to extend this definition to all levels of integration. What an action should be for any particular case must be determined by some kind of trial and error even in physics. In mechanics, action A is the kinetic energy KE minus the potential energy PE integrated over time: A = ò (KE - PE) dt. It is not always possible to measure both the energy and the time dimensions of action. The actual measurement of action is facilitated by the fact that at every level of organization there are units of action, such as cardiac contractions, neuronal action potentials, individual organisms, etc. If action units can be considered as roughly equal in energy, then their rate provides a coarse measure of energy consumption. This is in fact roughly true for cardiac rate and energy consumption.

Another motivation to study, whenever possible, time series of action units, is that rate measures the local time. Every process is its own timer. In physics, time is relative to the frame of reference. Expanding on this idea, we consider that time is local in biological, social and psychological processes. For instance, we take cardiac beats as the timing of the personal clock of the individual.

Two dimensions: Opposition as Information

One dimensional recordings portray action; two dimensional portraits provide a picture of acceleration and deceleration. This is information as defined by Bateson [1979], i.e. news of a difference. In many cases, however, information is the recognition of a repetition. In particular, repetition in the mist of change is news. Both recurrence and novelty can be informative. Difference and repetition are opposite cases of pairing. Likewise an enzyme recognizes its substrate through pairing. We thus define information as complementation or opposition.

Linear scales and categorical distinctions force linearity, and thus constrain us to consider that attraction and repulsion neutralize each other. In reality opposite forces can grow together. For instance, cost and benefit often vary in parallel, but exert opposite influences on our decision to buy. Likewise love and conflict grow together with intimacy, and decrease together with distance. Harmony and conflict coexist in intrapsychic and interpersonal processes: methods that assume a categorical distinction, or an inverse linear relation between them, cannot be valid or even fruitful; they prevent the recognition of ambivalence, contradiction, ambiguity and conflict, and thus they conceal, rather than reveal, why and how change is engendered or prevented. Linear scales necessarily produce distorted data. To study coexisting opposites one needs to plot the data in a two-dimensional Cartesian scale. We thus plot attraction and repulsion as orthogonal vectors rather than as linear opposites. In this manner we can plot in one axis, let us say the vertical, how these actions are synergic, and in the other (horizontal) axis how they oppose each other. The many uses and implications of such representation of opposites are presented in figure 1. We apologize for the complexity of the figure, and ask you to toil with it, because it illustrates a novel and useful technique. It is the core of the process method. Combining the phase plane of non-linear dynamics and the concept of the union of opposites, it offers a practical method to study empirically and numerically contradictory processes.

Diamond of opposites: Whenever possible, we measure opposites separately, thereby allowing for an empirical evaluation as to whether they neutralize each other or grow together. The two axes of the coordinate plane are linear scales representing the intensity of each opposite force. When multiple observations are made, one can examine how the interaction of opposite forces shapes the trajectory of processes. Consider for instance attraction and repulsion between two persons (or two particles). The four quadrants within the plane correspond to a category describing the relationship of the opposites. The left and right quadrants represent cases in which one opposite clearly dominates over the other, either attraction or repulsion. The bottom quadrant signifies that both forces are of low intensity (neutrality), while the top quadrant is occupied when opposites are both of high intensity (contradiction). Using the diamond of opposites to study interpersonal relations (sociodynamic test [Carlson-Sabelli et al, 1992, 1994], we find that attraction and repulsion are not inversely related, but often correlated positively with each other. The diamond of opposites allows one to differentiate ambivalence and contradiction from neutrality and indifference, that linear scales lump together. High energy contradictory processes, either intrapsychic or interpersonal, a great potential for creativity and destructiveness, and are easily influenced by small interventions (butterfly effect). The capability to identify contradictions is thus useful to target issues that are most amenable to therapeutic intervention at a given time.

The diamond of opposites has also been used to study longitudinally the interpersonal relations of patients [Carlson-Sabelli et al, 1992, 1994] and the emotions of individual subjects [Sabelli et al, 1990]. Opposite emotions such as anger, anxiety and depression, wax and wane together. Plots of interpersonal relations indicate that more than a third of persons report over 30 % of their close relationships as contradictory. This is predictive of catastrophic switches between opposites, where one's choice easily becomes a rejection, and vice versa. This was in fact observed when the subjects were retested at a later time. It is noteworthy that the neutral quadrant was much emptier than the contradictory quadrant in all plots, indicating that coexisting opposites create ambivalent bonds, not neutrality.

Interpersonal profiles plotted in two dimensions reveal personally unique patterns. For some persons, their important relationships are unambiguous: as harmony and attraction grow, conflict and repulsion diminish. Their interpersonal plots show a linear sequence from positive to negative. Such linear personality may reflect a simple, low energy psychological make-up, or a neurotic an inability to recognize and/or tolerate ambiguity. In contrast, there are high energy persons who consistently have and seek high energy relationships, that may not be readily tolerated by others. This may lead to interpersonal conflicts. They are bifurcating personalities, who make friends and enemies, and who are simultaneously attractive and repelling for many others. This is the pattern expected from a bipolar personality, but it is also present in highly creative persons.

Phase plane of opposites: The diamond of opposites can also be used to interpret two-dimensional plots of time series such as phase portraits and return maps commonly used to study non-linear processes. According to qualitative dynamics, patterns in complex processes can be found by plotting its trajectory on a phase space defined by a few variables. Process theory suggest that the most revealing plots will be obtained by choosing pairs of complementary and opposite forces as the axes of the phase space. The three diagrams at the bottom of figure 1 illustrate how changes in instantaneous heart rate (the inverse of cardiac beat intervals) result from the opposing actions of the sympathetic accelerating nerve that releases norepinephrine (NE) and the decelerating parasympathetic nerve that releases acetylcholine (Ach). Heart rate is approximately 90 beats per minute when neither input is activated, as it is observed in the denervated heart --a condition clinically found in some neuropathies. Cardiac timing usually varies from resting states of acetylcholine predominance (low rate, high variability) to active states of norepinephrine predominance (fast rate, lower variability). The heart may, however, be in any one of the four quadrants. Simultaneous activation of acetylcholine and norepinephrine systems occur in situations of crisis.

Iterated negation -the diamond of opposites in logic: The diamond of opposites can also be used in logic (upper left) as an alternative to Venn diagrams. It allows to represent coexisting opposites (e.g. an electron is a wave and a particle). All concepts and propositions are in part true and in part false; this coexistence of contradictory values can be formulated as an expansion of two-valued logic by iteration, as shown in the table inset [Sabelli, 1989, 1996].

Tridimensional plots portray catastrophes and co-creations. Consider for instance an important interpersonal relation. It often includes multiple links which may elicit contradictory feelings and motivations. When two of them are strong opposites, and neither one can be eliminated, the "equilibrium" of opposites creates complex organization, including relatively stable structures to chronic conflicts that arise when an individual has no choice. When a choice between opposite behaviors is made, high levels of ambivalence or contradiction lead to sudden changes in behavior, that oscillates between choice and rejection in a manner that corresponds to the notion of catastrophe. The distribution of interpersonal choices as a function of the underlying feelings of attraction and repulsion follow a folded surface. This folded surface can be modelled as a catastrophe. A fold catastrophe is governed by two parameters, the bifurcating and the asymmetric control parameters. As illustrated in figure 1, the asymmetric parameter of the simplest catastrophe is a function of the difference between opposite motivations, while the bifurcating parameter is a function of their sum. Intuitively, both opposing forces contribute energy to the process, while their difference provides information regarding the direction of the outcome, either choice and rejection.

The relation between opposites embodies two primary physical dimensions, action (energy x time) and information. Energy and information may estimated from the diamond of opposites as the sum and differences of opposites, and more properly by using trigonometric functions (figure 1, upper right). We may take the sum of the sines of the vectors representing opposite forces as a measure of their synergy, and the sum of their cosines as a measure of their antagonism.

Entropy measures provide a way to quantify action and information. Again we use a two-dimensional portrait, plotting the entropy of units of action, such as cardiac beat intervals, versus the entropy of accelerations (differences between consecutive members of the time series, as described in Part I), as illustrated in figure 2. Using such a two dimensional measure of entropy, Kanters and co-workers [1994] measure parasympathetic activity in their studies of heart rate variation.

In a time series, organization is embodied as pattern of accelerations and decelerations, just as in a structure is embodied as form. The computation of patterns successive differences between successive members of a time series is a method to measure strong, definite, simple patterns (Part I, figure 4) that make themselves apparent in short sequences of data. The construction of long vectors of N-successive members, and their quantification by the method of recurrences allows one to detect complex patterns. Recurrence graphs reveal multidimensional, time-limited patterns (complexes) in biological data as contrasted to the stationary, low dimensional patterns of periodic and chaotic attractors. Organization can be measured by the duration, dimensionality, and pattern of such complexes. Eckmann et [1987] introduced recurrence plots as portraits of processes of any type. Webber and Zbilut [1994] provided methods for their quantification. A process perspective focuses on the ability of the method to study non-stationary processes, and adds:

(a) Construction of time graphs to reveal transient patterns (complexes), quantify their duration, and the frequency of interruptions of pattern (net accelerations).

(b) Use of high embeddings: Postulating that biological processes reflect the complexity of the neuropsychological processes that regulate them, leads us to study high dimensions of embedding; in contrast, a focus on attractors leads to the investigation of time series in low dimensional frameworks.

(c) Empirical measurement of novelty: Postulating that processes generate novelty and are not determined, we interpret a paucity of recurrence below that observed with random distributions with the same statistical variance (constructed by shuffling the time series) as a measure of development. Biological data have a low rate of recurrences, indicating novelty, and a high rate of sequential recurrences. We thus interpret the rate of sequential recurrences as a measure of pattern, rather than of "determinism" as labelled by Webber and Zbilut.

As shown in Part I, entropy measures reflect the degree of symmetry and diversity of a time series at a given dimension. The measurement of entropy at various levels of complexity thus provides a measure of organization. Given the ambiguities associated with the term entropy, we have coined the expression biostatistical entropy [Patel et al, 1998] to refer to the quantification to entropy at increasingly higher dimensionality. Thermodynamic entropy is measured at 0 dimensions in the sense that temporal order is ignored. In most cases it is not possible to measure simultaneously thermodynamic entropy and temporal features. However the mean frequency of the series provides an estimate of the intensity of energy flow --for instance heart rate is related to the intensity of physical exercise and of emotional exertion. Dynamic entropy is the entropy of intervals between action units (one dimension, time). The dynamic entropy of static distributions does not depend on the length of the series; the entropy of time series of cardiac beats changes with the duration of sampling, time of the day, subject's activity, etc. Thus entropy is a function of change, not of temporal order.

The entropies of interval differences (two dimensions) and of differences of differences (3, 4,.. few dimensions) measure accelerations and decelerations that result from interactions or communications; we thus label them together as informational entropy. The entropy of longer sequences of consecutive members of a time series, measured by the recurrence method, provides an estimate of the entropy of complexes --complex entropy.

The fundamental tenet of physiological thinking is that both physical and mental phenomena are processes of different complexity, not two different substances. In contrast, dominant ideologies adopted dualistic views that separate physical and mental processes as different substances. Levels of organization of different complexity interact in two opposite hierarchical manners, that we call priority and supremacy. We take the levels of organization of biological organisms as a model for the relation between levels of organization in nature. Respiration, circulation, nutrition have priority, while nervous control has supremacy. In the central nervous system, spinal cord reflexes have evolutionary, developmental, and functional priority, but brain cortex has supremacy of control (Pavlov). Likewise in nature, simple processes have temporal priority and finality, greater energy, greater extension, and greater duration; they determine universal patterns that are reproduced at higher levels (homology). Complex levels are more efficient, and determine the form of the simple levels that encode them (isomorphism), and thus acquire local supremacy. These ideas generate methodological guidelines:

(a) Priority of the objective and supremacy of the subjective: The objective reality of the external world has priority in learning, but the biases introduced by social culture and personal psychology give supremacy to the subjective in what we regard as truth [Carlson-Sabelli and Sabelli, 1984]. Thus, in scientific research, empirical data has priority, but method and interpretation have supremacy.

(b) Physical priority and psychological supremacy: Physical actions have greater temporal and spacial extension, but within a complex system, they are controlled by higher levels of organization. Complex processes are encoded in physical actions, so the two necessarily are isomorphic. One can thus study complex processes by examining their stamp upon simpler ones. This is the rational for seeking in cardiac recordings a portrait for emotions, pioneered by the work of Redington and Reidbord (1992).

The concept of biological priority and psychological supremacy has other applications in medicine [Sabelli and Carlson-Sabelli, 1989, Sabelli et al, 1994] and in sociology [Sabelli and Carlson-Sabelli, 1995]. The idea that psychological energy is embodied in a material structure has led to the search for neurohormonal deficits in the causation of depression. Animal and clinical data has led us to postulate that 2-phenylethylamine (PEA) is the neurohormone of psychological energy [Sabelli and Javaid, 1995], to diagnose certain types of depression by PEA deficit, and to treat depression physiologically with PEA replacement --just as diabetes is treated with insulin replacement. This approach is successful in 60 % of cases [Sabelli et al, 1994, 1996].

(c) Mathematical priority and ideological supremacy: Mathematics provides methods for measurement and a clear formulation of hypotheses, while psychological analysis allows for critical consideration of underlying assumptions. For instance, creative change and interactions cannot be studied with assumptions, definitions and methods that exclude them, such as independent, isolated events, equilibrium states, static order and randomness the entire range of alternatives, linear scales that imply the mutual exclusion of opposites; systems separated by boundaries rather than connected by interphase.

Following these notions, we are developing the process method by combining mathematical measurement with simultaneous recording of behavior and emotions to analyze the electrocardiogram. We hope in this manner to learn not only something medically and psychologically useful, but also something about the universe we inhabit. This is the physiological approach to the study of nature, as contrasted to reductionism. Disregarding the common nature of all processes, reductionism makes physics a "theory of everything", dreams of particle physics as "a final theory", and dismisses biology and psychology as "soft science". Actually, Pythagoras' discovery of the first law of science on a psychobiological phenomenon, musical harmony, the discovery of the golden ratio as an aesthetic parameter long before it was found to define botanical and anatomical relations, Lamarck-Darwin's discovery of biological evolution a century before physics developed its own evolutionary theory, and Pasteur's discovery of cosmic asymmetry long before it has begun to emerge in physics, indicates that complex psychobiological patterns can reveal fundamental features of physical processes not evident in simpler phenomena. Such inference from the complex to the simple ("complexity inference", Sabelli, 1989) complements reduction, which has been the only operative scientific strategy throughout the centuries. In this manner one can operationalize the systems approach as a method.

We may illustrate this approach by contrasting the concept of biostatistical entropy with the standard view of entropy as disorder. Analyzing time series, we observe that entropy is equally high in random distributions (rectangular, Gaussian, Poisson) and in ordered series of the same diversity, indicating it does not measure order. Shuffling ordered data to create a randomly-ordered time series with the same statistical distribution as the original periodic or chaotic ordered time series does not change their entropy. Further, maximal entropy is said to correspond to greatest probability, yet absolute randomness (such as pure white noise) never obtains in reality. In reality, maximal entropy has the lowest probability of realization. On the other hand we note an empirical correlation between the value of entropy and the symmetry and diversity of the time series. This conclusion illustrates the empirical interpretation of concepts, in this case the meaning of entropy, by examining normative models (random, harmonic, and chaotic, series) and experimental data, rather than defining them conventional and a priori.

The development of the process method is still in progress. Many and diverse data must be considered before defining patterns as characteristic of biological processes. Many other techniques may be more useful to measure novelty and entropy in creative processes. Some of the techniques adopted here seem particularly questionable. Using a high number of embeddings undoubtedly such procedure distorts the data, "crushing", so to speak, its patterns, but then one must remember that particle physics, mass spectroscopy, and biochemical analysis likewise depend on destroying the objects they study. Every measurement is a transformation of facts into data, and contains inseparable objective and a perceptive aspects. The use of multiple frameworks of increasing dimensions seems justified by the findings of patterns at many of them.

Demonstrating asymmetry, opposition, and novelty in natural processes supports the hypothesis that they are fundamental cosmic forms [Sabelli et al, This Volume]. Such agreement is no proof, because methods as a rule confirm the theories that originate them. The same reason indicates the need to use process methods. To study creative processes calls for techniques to measure novelty, complexity, and the two-way interaction of multiple levels of organization.

A theory is most valuable when it generates methods that refute it. Thus Russell refuted his own logic with a counterexample it generated, Eccless demonstrated chemical synaptic transmission with methods designed to refute it, and now chaos theory has generated methods that demonstrate the need to go beyond deterministic, recurrent, low dimensional, and symmetric attractors. Undoubtedly process theory will be refuted, but its methodology is still too underdeveloped to reach this goal.

Acknowledgements: This work was supported by the Society for the Advancement of Clinical Philosophy. The authors are deeply indebted to Drs. C. Webber and J. Zbilut for the use of their programs.

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