A key topic in the work of Burghard Rieger is the notion of meaning. To explore this notion, he and his collaborators developed a most sophisticated approach combining theoretical ideas and concepts of semiotics with empirical and numerical tools of computational linguistics (see [31] for a most recent comprehensive account). In the present contribution, relations of Rieger’s achievements to some issues of interest in the physics and philosophy of complex systems will be addressed.

Some theorists who emphasize the complexity of biological and cognitive systems and who advocate the employment of the tools of dynamical systems theory in explaining them construe complexity and reduction as exclusive alternatives. This paper argues that reduction, an approach to explanation that decomposes complex activities and localizes the components within the complex system, is not only compatible with an emphasis on complexity, but provides the foundation for dynamical analysis. Explanation via decomposition and localization is nonetheless extremely challenging, and an (...) analysis of recent cognitive neuroscience research on memory is used to illustrate what is involved. Memory researchers split between advocating memory systems and advocating memory processes, and I argue that it is the latter approach that provides the critical sort of decomposition and localization for explaining memory. The challenges of linking distinguishable functions with brain processes is illustrated by two examples: competing hypotheses about the contribution of the hippocampus and competing attempts to link areas in frontal cortex with memory processing. (shrink)

This article illustrates the important scientific role that a systems approach might play within the social sciences and humanities, above all through its contribution to a common language, shared conceptualizations, and theoretical integration in the face of the extreme (and growing) fragmentation among the social sciences (and between the social sciences and the natural sciences). The article outlines a systems theoretic approach, actor-system-dynamics (ASD), whose authors have strived to re-establish systems theorizing in the social sciences (after a period of marginalization (...) since the late 1960s). This is done, in part, by showing how key social science concepts are readily incorporated and applied in social system analysis. (shrink)

Complexity and Postmodernism explores the notion of complexity in the light of contemporary perspectives from philosophy and science. The book integrates insights from complexity and computational theory with the philosophical position of thinkers including Derrida and Lyotard. Paul Cilliers takes a critical stance towards the use of the analytical method as a tool to cope with complexity, and he rejects Searle's superficial contribution to the debate.

The subject of this chapter is the identity of individual dynamical objects and properties. Two problems have dominated the literature: transtemporal identity and the relation between composition and identity. Most traditional approaches to identity rely on some version of classification via essential or typical properties, whether nominal or real. Nominal properties have the disadvantage of producing unnatural classifications, and have several other problems. Real properties, however, are often inaccessible or hard to define (strict definition would make them nominal). I suggest (...) that classification should be in terms of dynamical properties of systems, starting with individual systems rather than classes, and working up by abstractions that fit causal generalities. The advantage of this approach is that individuality is testable and revisable as we come to know more about systems. Another advantage is that if anything is real, then it is the dynamical. Once I have presented this approach in general, I will show that the central concept of dynamical cohesion (the "dividing glue") is amenable to giving a principled account of individuation as a process, at the same time explaining the origin of diversity. Some other advantages of this approach are presented, including how it can be used as a basis for testable classifications. (shrink)

Complex systems are dynamic and may show high levels of variability in both space and time. It is often difficult to decide on what constitutes a given complex system, i.e., where system boundaries should be set, and what amounts to substantial change within the system. We discuss two central themes: the nature of system definitions and their ability to cope with change, and the importance of system definitions for the mental metamodels that we use to describe and order ideas about (...) system change. Systems can only be considered as single study units if they retain their identity. Previous system definitions have largely ignored the need for both spatial and temporal continuity as essential attributes of identity. After considering the philosophical issues surrounding identity and system definitions, we examine their application to modeling studies. We outline a set of five alternative metamodels that capture a range of the basic dynamics of complex systems. Although Holling’s adaptive cycle is a compelling and widely applicable metamodel that fits many complex systems, there are systems that do not necessarily follow the adaptive cycle. We propose that more careful consideration of system definitions and alternative metamodels for complex systems will lead to greater conceptual clarity in the field and, ultimately, to more rigorous research. (shrink)

bruce@edmonds.name http://bruce.edmonds.name Abstract. Two kinds of problem are distinguished: the first of finding processes which produce complex outcomes from the interaction of simple parts, and the second of finding which process resulted in an observed complex outcome. The former I call the easy complexity problem and the later the hard complexity problem. It is often assumed that progress with the easy problem will aid process with the hard problem. However this assumes that the “reverse engineering” problem, of determining the process (...) from the outcomes is feasible. Taking a couple of simple models of reverse engineering, I show that this task is infeasible in the general case. Hence it cannot be assumed that reverse engineering is possible, and hence that most of the time progress on the easy problem will not help with the hard problem unless there are special properties of a particular set of processes that make it feasible. Assuming that complexity science is not merely an academic “game” and given the analysis of this paper, some criteria for the kinds of paper that have a reasonable chance of being eventually useful for understanding observed complex systems are outlined. Many complexity papers do not fare well against these critieria. (shrink)

Owing to intensive development of the theory of self-organization of complex systems called also synergetics, profound changes in our notions of time occur. Whereas at the beginning of the 20th century, natural sciences, by picking up the general spirit of Einstein's theory of relativity, consider a geometrization as an ideal, i.e. try to represent time and force interactions through space and the changes of its properties, nowadays, at the beginning of the 21st century, time turns to be in the focus (...) of attention. It turns to be possible to represent space through time, because synergetics shows that historical and evolutionary stages of development of a complex structure can be found now, in its present spatial configuration. A whole series of paradoxical notions, such as “the influence of the future upon the present”, a “possibility of touching of a rather remote future today”, “availability of the past and the future now, in praesenti”, “irreversibility and elements of reversibility in the course of evolutionary processes in time”, “discrete unites, quanta of time”, appear in synergetics. (shrink)

Change is an inborn trait of all organisms at every level of existence. This article proposes that the evolution of all life follows a course as if bound by a guiding principle or template. Overcoming disorder and entropy through diversity, this template has the properties of a spiral force, which acts to maintain continuity during change and transitions, and operates at all levels, from the simplest of forms to the most complex. Drawing from Chaos Theory, biology, depth psychology, and Buddhism, (...) the spiral template is presented as a new vision of reality guiding scientific and spiritual perspectives toward evolutionary wholeness. (shrink)

The complex and dynamic nature of systems pose a particular challenge to researchers and require the use of a research methodology designed to deal with such systems. The properties of fit, relevance, understandability, generality, control, workability, generalizability, and modifiability make Glaserian grounded theory and grounded action particularly well suited for studying systems. These methods are innovative, systemic, and sophisticated enough to reveal the underlying complexities of systems and plan actions that address their complex, dynamic nature while remaining grounded in what (...) is occurring within the systems as they change over time. (shrink)

Ecologist Richard Levins argues population biologists must trade‐off the generality, realism, and precision of their models since biological systems are complex and our limitations are severe. Steven Orzack and Elliott Sober argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins's thesis that there is a necessary trade‐off between generality, precision, and realism in mathematical models in biology is false. I argue that Orzack and Sober's arguments fail since (...) Levins's thesis concerns the pragmatic features of model building not just the formal properties of models. (shrink)

Ecologist Richard Levins (1966, 1968) argues population biologists must trade-off the generality, realism and precision of their models since biological systems are complex and our limitations are severe. Elliott Sober and Steven Orzack (1993) argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins` thesis that there is a necessary trade-off between generality, precision, and realism in mathematical models in biology is false. I argue that Sober and Orzack`s (...) arguments fail since Levins` thesis concerns the pragmatic features of model building not just the formal properties of models. (shrink)

This is a review article of Paul Cillier's 1999 book _Complexity and Postmodernism_. The review article is generally encouraging and constructive, although isolates a number of areas in need of clarification or development in Cillier's work. The volume of the _South African Journal of Philosophy_ in which the review article appeared also printed a response by Cilliers.

Systems involving many interacting variables are at the heart of the natural and social sciences. Causal language is pervasive in the analysis of such systems, especially when insight into their behavior is translated into policy decisions. This is exemplified by economics, but to an increasing extent also by biology, due to the advent of sophisticated tools to identify the genetic basis of many diseases. It is argued here that a regularity notion of causality can only be meaningfully defined for systems (...) with linear interactions among their variables. For the vastly more important class of nonlinear systems, no such notion is likely to exist. This thesis is developed with examples of dynamical systems taken mostly from mathematical biology. It is discussed with particular reference to the problem of causal inference in complex genetic systems, systems for which often only statistical characterizations exist. (shrink)

Willard van Orman Quine once said that he had a preference for a desert ontology. This was in an earlier day when concerns with logical structure and ontological simplicity reigned supreme. Ontological genocide was practiced upon whole classes of upper-level or "derivative" entities in the name of elegance, and we were secure in the belief that one strayed irremediably into the realm of conceptual confusion and possible error the further one got from ontic fundamentalism. In those days, one paid more (...) attention to generic worries about possible errors (motivated by our common training in philosophical scepticism) than to actual errors derived from distancing oneself too far from the nitty-gritty details of actual theory, actual inferences from actual data, the actual conditions under which we posited and detected entities, calibrated and "burned in" instruments, identified and rejected artifacts, debugged programs and procedures, explained the mechanisms behind regularities, judged correlations to be spurious, and in general, the real complexities and richness of actual scientific practice. The belief that logic and philosophy were prior to any possible science has had a number of distorting effects on philosophy of science. One of these was that for ontology, we seemed never to be able to reject the null hypothesis: "Don't multiply entities beyond necessity.". (shrink)

Complex systems can be characterized by classes of equivalency of their elements defined according to system specific rules. We propose a generalized preferential attachment model to describe the class size distribution. The model postulates preferential growth of the existing classes and the steady influx of new classes. According to the model, the distribution changes from a pure exponential form for zero influx of new classes to a power law with an exponential cut-off form when the influx of new classes is (...) substantial. Predictions of the model are tested through the analysis of a unique industrial database, which covers both elementary units (products) and classes (markets, firms) in a given industry (pharmaceuticals), covering the entire size distribution. The model's predictions are in good agreement with the data. The paper sheds light on the emergence of the exponent tau approximately 2 observed as a universal feature of many biological, social and economic problems. (shrink)

Cosmology has undergone a revolution in recent years. The exciting interplay between astronomy and fundamental physics has led to dramatic revelations, including the existence of the dark matter and the dark energy that appear to dominate our cosmos. But these discoveries only reveal themselves through small effects in noisy experimental data. Dealing with such observations requires the careful application of probability and statistics. But it is not only in the arcane world of fundamental physics that probability theory plays such an (...) important role. It has an impact in many aspects of our everyday life, from the law courts to the lottery. Why then do so few people understand probability? And why do so few people understand why it is so important for science? Why do so many people think that science is about absolute certainty when, at its core, it is actually dominated by uncertainty? This book attempts to explain the basics of probability theory, and illustrate their application across the entire spectrum of science. (shrink)

Behaviors of chaotic systems are unpredictable. Chaotic systems are deterministic, their evolutions being governed by dynamical equations. Are the two statements contradictory? They are not, because the theory of chaos encompasses two levels of description. On a higher level, unpredictability appears as an emergent property of systems that are predictable on a lower level. In this talk, we examine the structure of dynamical theories to see how they employ multiple descriptive levels to explain chaos, bifurcation, and other complexities of nonlinear (...) systems.. (shrink)

For Merleau-Ponty,consciousness in skillful coping is a matter of prereflective ‘I can’and not explicit ‘I think that.’The body unifies many domain-specific capacities. There exists a direct link between the perceived possibilities for action in the situation (‘affordances’) and the organism’s capacities. From Merleau-Ponty’s descriptions it is clear that in a flow of skillful actions, the leading ‘I can’ may change from moment to moment without explicit deliberation. How these transitions occur, however, is less clear. Given that Merleau-Ponty suggested that a (...) better understanding of the self-organization of brain and behavior is important, I will re-read his descriptions of skillful coping in the light of recent ideas on neurodynamics. Affective processes play a crucial role in evaluating the motivational signif- icance of objects and contribute to the individual’s prereflective responsive- ness to relevant affordances. (shrink)

Three principles of dialectical analysis are examined in terms of nonlinear dynamics models. The three principles are the transformation of quantity into quality, the interpenetration of opposites, and the negation of the negation. The first two of these especially are interpreted within the frameworks of catastrophe, chaos, and emergent dynamics complexity theoretic models, with the concept of bifurcation playing a central role. Problems with this viewpoint are also discussed.

Much empirical analysis and econometric work recognizes that there are nonlinearities, regime shifts or structural breaks, asymmetric adjustment costs, irreversibilities and lagged dependencies. Hence, empirical work has already transcended neoclassical economics. Some progress has also been made in modeling endogenously generated cyclical growth and fluctuations. All this is inconsistent with neoclassical general equilibrium. Hence there is growing evidence of Kuhnian anomalies. It therefore follows that there is a Kuhnian crisis in economics and further research in nonlinear dynamics and complexity can (...) only increase the Kuhnian anomalies. This crisis can only deepen. However, there is an ideological commitment to general equilibrium that justifies “free enterprise” with only minimal state intervention that may still sustain neoclassical economics despite the growing evidence of Kuhnian anomalies. Thus, orthodox textbook theory continues to ignore this fact and static neoclassical theory remains a dogma with no apparent reformulation to replace it. (shrink)

Philosophers like Duhem and Cartwright have argued that there is a tension between laws' abilities to explain and to represent. Abstract laws exemplify the first quality, phenomenological laws the second. This view has both metaphysical and methodological aspects: the world is too complex to be represented by simple theories; supplementing simple theories to make them represent reality blocks their confirmation. We argue that both aspects are incompatible with recent developments in nonlinear dynamics. Confirmation procedures and modelling strategies in nonlinear dynamics (...) show that there are simple, abstract theories that can be confirmed without encountering the problems pointed to by Cartwright. (shrink)

Husserl is well known for his critique of the “mathematizing tendencies” of modern science, and is particularly emphatic that mathematics and phenomenology are distinct and in some sense incompatible. But Husserl himself uses mathematical methods in phenomenology. In the first half of the paper I give a detailed analysis of this tension, showing how those Husserlian doctrines which seem to speak against application of mathematics to phenomenology do not in fact do so. In the second half of the paper I (...) focus on a particular example of Husserl’s “mathematized phenomenology”: his use of concepts from what is today called dynamical systems theory. (shrink)

Millers Living Systems Theory (LST) is known to be very comprehensive. It comprises eight nested hierarchical levels. It also includes twenty critical subsystems. While Millers approach has been analyzed and applied in great detail, some problematic features remain, requiring further explication. One of these is the relationship between reduction and emergence in LST. There are at least four relevant possibilities. One is that LST exhibits neither clear reductionism nor emergence, but is essentially neutral in this regard. Another is that the (...) apparent comprehensiveness of LST is illusory, as the approach remains vulnerable to reduction that could ultimately reduce it to a shadow of its present self. The charge of reductionism has been made by critics leading Miller to defend this theory vehemently as nonreductionist in nature. A third possibility is that LST is not reductionist, but is in fact an emergent theory. Miller makes this claim quite strongly. A fourth possibility, and in some ways the most analytically problematic, is that LST exhibits evidence of both reductionism and emergence simultaneously. Some critics might see this fourth situation as evidence of a troubling paradox or anomaly that must be resolved before further progress can be made in the explication and application of LST. The purpose of the paper is to remove this apparent anomaly. The paper removes this anomaly by differentiating between new-variable emergence and transformational emergence. No concrete evidence is found to contradict Milers claim of emergence in LST, and thus no true anomaly exists. (shrink)

Bridging between psychological and neurobiological systems requires that the system components are closely specified at both the psychological and brain levels of analysis. We argue that in developing his dynamic systems theory framework, Lewis has sidestepped the notion of a psychological level systems model altogether, and has taken a partisan approach to his exposition of a brain-level systems model.

Part I [sections 2–4] draws out the conceptual links between modern conceptions of teleology and their Aristotelian predecessor, briefly outlines the mode of functional analysis employed to explicate teleology, and develops the notion of cybernetic organisation in order to distinguish teleonomic and teleomatic systems. Part II is concerned with arriving at a coherent notion of intentional control. Section 5 argues that intentionality is to be understood in terms of the representational properties of cybernetic systems. Following from this, section 6 argues (...) that intentional control needs to be seen as a particular type of relationship between the system and its environment. (shrink)

Intentional systems theory is in the first place an analysis of the meanings of such everyday ‘mentalistic’ terms as ‘believe,’ ‘desire,’ ‘expect,’ ‘decide,’ and ‘intend,’ the terms of ‘folk psychology’ (Dennett 1971) that we use to interpret, explain, and predict the behavior of other human beings, animals, some artifacts such as robots and computers, and indeed ourselves. In traditional parlance, we seem to be attributing minds to the things we thus interpret, and this raises a host of questions about the (...) conditions under which a thing can be truly said to have a mind, or to have beliefs, desires and other ‘mental’ states. According to intentional systems theory, these questions can best be answered by analyzing the logical presuppositions and methods of our attribution practices, when we adopt the intentional stance toward something. Anything that is usefully and voluminously predictable from the intentional stance is, by definition, an intentional system. The intentional stance is the strategy of interpreting the behavior of an entity (person, animal, artifact, whatever) by treating it as if it were a rational agent who governed its ‘choice’ of ‘action’ by a ‘consideration’ of its ‘beliefs’ and ‘desires.’ The scare-quotes around all these terms draw attention to the fact that some of their standard connotations may be set aside in the interests of exploiting their central features: their role in practical reasoning, and hence in the prediction of the behavior of practical reasoners. (shrink)

Social systems theory has been dominated in recent years by the work of Niklas Luhmann, but there is another strand of systems thinking, which is receiving increasing attention in sociology: emergentism. For emergentism, the core problems of systems thinking are concerned with causation and reductionism; for Luhmann, they are questions of meaning and self-reference. Arguing from an emergentist perspective, the article finds that emergentism addresses its own core problem successfully, while Luhmann's approach is incapable of resolving questions of causation and (...) reductionism. On the other hand, neither paradigm yet has a convincing response to the challenges of meaning and self-reference. Key Words: social systems • emergence • paradigms • autopoiesis • critical realism. (shrink)

Dynamic systems theory is a way of describing the patterns that emerge from relationships in the universe. In the study of interpersonal relationships, within and between species, the scientist is an active and engaged participant in those relationships. Separation between self and other, scientist and subject, runs counter to systems thinking and creates an unnecessary divide between humans and animals.

On an influential account, chaos is explained in terms of random behaviour; and random behaviour in turn is explained in terms of having positive Kolmogorov-Sinai entropy (KSE). Though intuitively plausible, the association of the KSE with random behaviour needs justification since the definition of the KSE does not make reference to any notion that is connected to randomness. I provide this justification for the case of Hamiltonian systems by proving that the KSE is equivalent to a generalized version of Shannon's (...) communication-theoretic entropy under certain plausible assumptions. I then discuss consequences of this equivalence for randomness in chaotic dynamical systems. Introduction Elements of dynamical systems theory Entropy in communication theory Entropy in dynamical systems theory Comparison with other accounts Product versus process randomness. (shrink)

Developmental systems theory (DST) is a general theoretical perspective on development, heredity and evolution. It is intended to facilitate the study of interactions between the many factors that influence development without reviving `dichotomous' debates over nature or nurture, gene or environment, biology or culture. Several recent papers have addressed the relationship between DST and the thriving new discipline of evolutionary developmental biology (EDB). The contributions to this literature by evolutionary developmental biologists contain three important misunderstandings of DST.

The Sense of Space brings together space and body to show that space is a plastic environment, charged with meaning, that reflects the distinctive character of human embodiment in the full range of its moving, perceptual, emotional, expressive, developmental, and social capacities. Drawing on the philosophies of Merleau-Ponty and Bergson, as well as contemporary psychology to develop a renewed account of the moving, perceiving body, the book suggests that our sense of space ultimately reflects our ethical relations to other people (...) and to the places we inhabit. (shrink)

A study of shifts in scientific strategies for measuring the living body, especially in dynamic systems theory: (1) sheds light on Hegel's concept of measure in The Science of Logic, and the dialectical transition from categories of being to categories of essence; (2) shows how Hegel's speculative logic anticipates and analyzes key tensions in scientific attempts to measure and conceive the dynamic agency of the body. The study's analysis of the body as having an essentially dynamic identity irreducible to measurement (...) aims to contribute to reconceiving the body, in a way that may be helpful to overcoming dualism. (shrink)

Although we applaud the interactivist approach to language and communication taken in the target article, we notice that Shanker & King (S&K) give little attention to the theoretical frameworks developed by dynamical system theorists. We point out how the dynamical idea of causality, viewed as multidirectional across multiple scales of organization, could further strengthen the position taken in the target article.

Does systems theory need rethinking? Most social scientists would probably say no. It had its run, was debated critically, and found wanting. If at all, it should be treated historically. Why then might systems theory need rethinking, as the title of this symposium claims? The reason is that, unlike in the natural and biosocial sciences, any conception of system in the social sciences has remained suspect in the wake of problematic Parsonian and cybernetic systems theories. The premise of this special (...) issue is that abandoning conceptions of systems has imposed a high price on the social sciences: a lack of ontologies and methodologies that are both philosophically profound and scientifically defensible. It has left social scientists who choose to ignore ontology in their theoretical and empirical work defenseless against enterprising settlers from a variety of humanities and social science disciplines who attack mainstream work with—often simplistic and naïve, but nevertheless fundamental—philosophical arguments, whether anti-scientific postmodernists or pseudo-scientific rational choice theorists. The goal of this special issue is to showcase new and original work that contributes to a rethinking of systems theory by taking the conception of systems seriously. This introduction offers a programmatic statement of a systemic ontology and methodology as well as a brief general outline and examples of what a systems-based approach in the social sciences entails. Key Words: systems theory • systemism • systemic approach • complexity theory • self-organization • emergentism • paradigms • social mechanisms • Mario Bunge. (shrink)

I propose a semi-eliminative reduction of Fodors concept of module to the concept of attractor basin which is used in Cognitive Dynamic Systems Theory (DST). I show how attractor basins perform the same explanatory function as modules in several DST based research program. Attractor basins in some organic dynamic systems have even been able to perform cognitive functions which are equivalent to the If/Then/Else loop in the computer language LISP. I suggest directions for future research programs which could find similar (...) equivalencies between organic dynamic systems and other cognitive functions. This type of research could help us discover how (and/or if) it is possible to use Dynamic Systems Theory to more accurately model the cognitive functions that are now being modeled by subroutines in Symbolic AI computer models. If such a reduction of subroutines to basins of attraction is possible, it could free AI from the limitations that prompted Fodor to say that it was impossible to model certain higher level cognitive functions. (shrink)

Academic social scientists and professional practitioners could increase the effectiveness of their undertakings to advance positive change toward solving social and organizational problems by more effectively combining their efforts. Historically, both realms have used reductionist techniques and methodologies that are unsuited for understanding and solving problems in social and organizational systems. Their efforts could be significantly enhanced by using a grounded theory/grounded action approach. Grounded theory/grounded action is designed to generate explanations directly from data that provide a theoretical foothold for (...) effecting optimal and sustainable change in social and organizational systems. (shrink)

The research methodologies of grounded theory and grounded action are framed by a systems perspective, from which they contribute their own unique properties and processes to the evolution of systems thinking. The author provides definitions for systems, theory, grounded theory, grounded action, and systems thinking, and explores the relationships between theory, grounded theory/grounded action, and systems thinking with regard to purpose, context, and usefulness for the resolution of social concerns and systemic change.

The concepts and powerful mathematical tools of Dynamical Systems Theory (DST) yield illuminating methods of studying cognitive processes, and are even claimed by some to enable us to bridge the notorious explanatory gap separating mind and matter. This article includes an analysis of some of the conceptual and empirical progress Dynamical Systems Theory is claimed to accomodate. While sympathetic to the dynamicist program in principle, this article will attempt to formulate a series of problems the proponents of the approach in (...) question will need to face if they wish to prolong their optimism. The main points to be addressed involve the reductive tendencies inherent in Dynamical Systems Theory, its somewhat muddled position relative to connectionism, the metaphorical nature DST-C exhibits which hinders its explanatory potential, and DST-C's problematic account of causality. Brief discussions of the mathematical and philosophical backgrounds of DST, seminal experimental work and possible adaptations of the theory or alternative suggestions (dynamicist connectionism, neurophenomenology, R&D theory) are included. (shrink)

By advocating an enlightened method of theorizing committed to thinking in terms of a system of differences, Luhmann has contributed to the development of sociology in a manner that cannot be praised enough. Nonetheless, he does not succeed in giving an account of his own position that satisfies the very logical preconditions that he himself has formulated for it. Instead, his systems theory paradigm of sociology is based on metaphysical premises characteristic of the identity-logical thought of "Old Europe." In fact, (...) the only way to make Luh mann's approach truly comprehensible is to reconstruct it as a new version of Hegel's dialectic. (shrink)