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A REVIEW OF SYSTEMS: NEW PARADIGMS FOR THE HUMAN SCIENCES

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This essay is a selective review of Systems: New Paradigms for the Human Sciences, edited by Gabriel Altmann and Walter A. Koch (Berlin: Walter de Gryter, 1998). It is selective because it is impossible to engage such a varied collection of systems-theoretic essays in a review of reasonable length. To invoke a relevant dialectical idea: the characteristic strength of any system is often also its characteristic weakness. One strength and weakness of the systems field is its great diversity, and this diversity is reflected in this volume by the range of subjects addressed in its 27 articles. I will not attempt what the editors themselves have declined to undertake, namely an integrating overview, nor will I offer brief remarks on many articles. Instead, I want to comment in detail on just three articles which bear on my own interests. I do not mean to suggest that these articles are more valuable or central to systems theory than the others.
International Journal of General Systems (2001) In press.
A REVIEW OF SYSTEMS: NEW PARADIGMS FOR THE HUMAN SCIENCES
Martin Zwick
Systems Science Ph.D. Program, Portland State University, Portland OR 97207
zwickm@pdx.edu
http://www.sysc.pdx.edu/faculty/Zwick
This essay is a selective review of Systems: New Paradigms for the Human Sciences,
edited by Gabriel Altmann and Walter A. Koch (Berlin: Walter de Gryter, 1998). It is
selective because it is impossible to engage such a varied collection of systems-theoretic
essays in a review of reasonable length. To invoke a relevant dialectical idea: the
characteristic strength of any system is often also its characteristic weakness. One
strength and weakness of the systems field is its great diversity, and this diversity is
reflected in this volume by the range of subjects addressed in its 27 articles. I will not
attempt what the editors themselves have declined to undertake, namely an integrating
overview, nor will I offer brief remarks on many articles. Instead, I want to comment in
detail on just three articles which bear on my own interests. I do not mean to suggest that
these articles are more valuable or central to systems theory than the others.
After discussing the three articles, I will conclude by adding a few general remarks and
by listing the authors and titles of the essays in the book, so that readers might be alerted
to items of potential interest. From my study of the three articles I discuss and from my
skimming of several other articles, I strongly recommend this book to systems
researchers, especially researchers interested in the human sciences.
George Klir, “From Crisp Systems to Fuzzy Systems” (pp. 79-103)
Klir argues that science is shifting towards the acceptance of “uncertainty” as an attribute
of our knowledge of the physical world and towards the development of methods by
which this uncertainty can be rigorously examined. Uncertainty offers a necessary
counterbalance to the traditional emphasis in science on lawfulness -- and predictability,
which until the discovery of chaos was assumed to follow from determinism. As Klir
points out, uncertainty is unavoidable in descriptions of “organized complexity”
(Weaver, 1948) a domain intermediate between “organized simplicity,” where analytic
methods suffice, and “disorganized complexity,” where statistical methods suffice. In
this intermediate domain neither analytic nor statistical methods are effective, and
problems of computational complexity are encountered.
Klir’s next proposition is the critical one: set theory and probability theory are inadequate
frameworks to capture the full scope of the concept of “uncertainty.” Uncertainty in set
theory means nonspecificity; in probability theory it derives from conflicting likelihood
claims. Generalizations of set and probability theories, for example, fuzzy set theory and
fuzzy measure theory, expand the concept of uncertainty while encompassing these
standard connotations; they are thus potentially of great value for science. Klir briefly
presents the main ideas of these generalizing theories, noting where they extend the more
familiar set theory and probability theory. For example, while the probability of the
union of disjoint sets is additive (equal to the sum of the probabilities of the separate
sets), fuzzy measures can be either superadditive or subadditive.
Review of Systems: New Paradigms 5/4/01 2
Klir goes on to discuss the general framework of systems modeling, which he and his
colleagues have developed, known as GSPS, the “general systems problem solver.” The
main categories of this epistemological hierarchy of system types are quickly reviewed in
the article; for further detail on this deep and comprehensive epistemological framework,
one must consult Klir’s major work in this area (1985). Fuzzy set theory and fuzzy
measure theory enlarge the categories of this framework, and Klir illustrates by
discussing the fuzzy set approach to linguistic variables defined in terms of continuous
base variables. Klir notes that even nominal variables can be fuzzified; there are, for
example, finite-state fuzzy automata. This is an important point, because nominal
variables are the most general kind of variable possible, though most explanations of
fuzzy set theory rarely discuss such variables.
The demonstration that fuzzy mathematics generalizes set theory and probability theory
is presented in a comprehensible and convincing way. From my own perspective,
however, I wonder if these developments represent, as Klir argues, a paradigm shift in
science per se, as opposed to an expansion of the modeling methods used in science.
One could view fuzzy set theory as a high level modeling language which bridges the
precision of mathematics and the flexibility of natural language. One might characterize
the emergence of such a new modeling language as a paradigm shift. Or, one might
instead insist that a new paradigm in science should impact not only methodology, but
also ontology. Can fuzzy mathematics be interpreted as a different view of what exists in
the world? Here I raise a controversial issue about which people have different
perspectives. Constructivists focus on methodology and epistemology and typically
abstain from speaking about ontology. To the extent that fuzzy mathematics emphasizes
issues of “belief,” “degrees of plausibility,” “degrees of evidence,” and the like, it reflects
this particular orientation. I prefer a more realist position: models link observers to
realities, and should be capable of being regarded either as epistemological (or
methodological) statements or as ontological ones. Klir’s presentation reflects the
constructivist position, but he also offers an interesting quote from Smuts (1926), which
seems to envisage fuzzy scientific models which can be viewed in both ways. Smuts
notes that in nineteenth century science, “Vagueness, indefinite and blurred outlines ...
was abhorrent ... This logical precision immediately had the effect of making it
impossible to understand ... actual causation ... We have to return to the fluidity and
plasticity of nature and experience in order to find concepts of reality.”
To make the point concretely: until recently most applications of fuzzy mathematics have
been in engineering, particularly in the design of control systems, and not in scientific
theory itself. This might be contrasted, for example, with the mathematics of non-linear
dynamics. While models of chaos are used both in design and to describe phenomena in
natural and social systems, the mathematics of fuzziness has so far been applied mainly
to design. Of course, designed (e.g., fuzzy control) systems are important objects of
scientific study if their behavior is not fully explicit in their specifications. Still, I would
argue that one can speak of a paradigm shift in science centered in concepts of fuzziness
only if scientific -- as distinct from engineering -- uses of fuzzy mathematics become
extensive. Some promising uses of this sort are apparently occurring (Klir, 2000), and if
Review of Systems: New Paradigms 5/4/01 3
notions of uncertainty from fuzzy set theory, fuzzy measure theory, and related
formalisms, do become as central to new scientific theories as probabilistically-defined
uncertainty is to quantum theory and nonlinear dynamics, then this would indeed
constitute a dramatic development. It is too early to tell whether or to what extent this
will occur. The mathematics of fuzziness has encountered strong opposition, and Klir
provides references for and a brief overview of the controversy.
The characterization, above, of fuzzy theories as high level tools for modeling does not
actually do justice to their value as links between mathematics and natural language.
These links may have deeper significance for the systems project, which, following
Bunge (1973), might be described as an attempt to construct an “exact and scientific
metaphysics.” “Metaphysics” here does not refer to questions of God, free will, and the
like, but to the study of general features of the world, such as order and disorder, system-
environment interactions, self-organization and self-maintenance, information
processing, regulation and control, morphogenesis, adaptation, learning, competition and
cooperation, etc. A metaphysics is “scientific” if it draws from and contributes to the
sciences and is thus both fertile and (indirectly) open to empirical test. A metaphysics is
“exact” if it is expressed mathematically, if not now, then as a future goal. (Bunge
actually includes exactness within a notion of a “scientific metaphysics,” but I find it
useful to separate it out as a third factor.) By being scientific and exact, a metaphysics
might satisfy both correspondence and coherence criteria for truth. To borrow a term
from Nicolescu’s article in this volume, the dual requirement of being scientific and exact
constitute necessary resistances for a metaphysics; they ground it and keep it honest.
A metaphysics is necessarily expressed in natural language. This allows it to be the
common heritage of humanity and not restricted to technical specialists, and enables it to
serve as a bridge to other aspects of philosophy, to religion, and to the arts and
humanities. So the linkage of natural language and exact mathematics is important to the
systems project. Fuzzy mathematics is one way of establishing such a linkage. Fuzzy
notions bear directly on distinguishing between system and environment, between one
element within the system and another, and between different attributes of the various
elements. Fuzzy notions address the fundamental issue of the ontological status of the
discrete versus the continuous. (This is treated, for example, by the use of linguistic
variables in fuzzy set theory and by “granulation” -- fuzzy membership functions --as an
alternative to “discretization.”) One finds recognition of the importance of this issue in
Smuts or, earlier, in Hegel’s dialectics, which also raised the issue of fuzziness. For
many centuries, in the notion of the “Great Chain of Being” which dominated western
philosophical thought, the continuity -- and by implication fuzziness -- of all types of
being was a central premise (Lovejoy, 1936).
The notions of fuzziness thus bear on systems in general. They also bear on the
particular class of systems of special interest to us, namely that class of beings, generated
by evolution, with developed faculties for modeling their environments, themselves, the
interaction between the two, and, self-referentially, these very “modeling subsystems”
themselves. The highest forms of these faculties for modeling and for communication
emerged with the development of natural language. From this perspective, mathematics
Review of Systems: New Paradigms 5/4/01 4
was only a later enhancement and specialization of language, applicable only to limited
aspects of reality and usable only by a small sub-population. While we have had the
idea, since Pythagoras, that the laws of the universe are mathematical, and feel awe and
puzzlement, as Wigner put it (1960), about the “unreasonable effectiveness of
mathematics” in the natural sciences, the optimum human means for describing the world
in its full richness continues to be natural language.
The bridge offered by fuzzy theories between mathematics and natural language thus
cannot be dismissed as a mere “higher level computer language.” How much interaction
this bridge promotes between natural language and mathematics is, however, another
issue. Whether the mathematics of fuzziness will afford deep insights into reality and
thus constitute a paradigm shift in science remains uncertain. Still, it is plain that this
mathematics is important to Systems Science. Klir’s presentation, in its compactness,
rigor, and clarity, distills the essence of this development.
Solomon Marcus, “No system can be improved in all respects” (pp. 143-164)
The essay of Solomon Marcus, “No system can be improved in all respects,” reflects an
orientation I have also articulated (Zwick, 1984). The article mainly addresses the
“conflictual pairs” which characterize many mental representations, and his discussion of
these pairs is subtle and illuminating. The notion of a conflictual pair is introduced using
Gödel’s findings about the conflict between consistency and completeness. Marcus
identifies the unexpectedness, the a posteriori character, of the {consistency,
completeness} conflict as a distinctive and defining characteristic of these pairs. A
similar non-a priori “conflict” characterizes the complementarity in quantum mechanics
between knowledge of position and of momentum. It does not, however, characterize the
[particle, wave] pair, in which the separate terms are inherently and explicitly opposed.
(Note: Marcus uses ordinary parentheses for all of his pairs, but I will use curly brackets
for conflictual pairs and ordinary brackets for explicit oppositions.)
Explicit and a priori oppositions are relatively straightforward, the terms being related
essentially through negation. Conflictual pairs, where oppositions are implicit and a
posteriori, are intrinsically more interesting. Marcus offers a number of conflictual pairs
in this paper, some of which bear a family resemblance to one another, but he does not
actually seek to identify an underlying commonality between all these pairs or between
very different pairs, other than the non-obvious nature of the conflict between the terms.
Since some of these pairs arise in mathematical domains, one might conceivably hope to
identify some similarity in the origins or character of the conflicts within different
formalisms (e.g., one might try to identify some relation between the property of a
conjugate pair of variables in quantum theory and the property of consistency and
completeness in formal mathematical systems).
A related philosophical remark and some questions. It seems possible to view some pairs
as “dyads” which arise from a distinction made within some “monad.” For example, the
dyad, {position, momentum}, differentiates the monad, {state}. A monad, {quantum
object}, might be considered to unite -- or be the source of -- the pair, [particle, wave].
One might inquire: Can a monad be identified for all or only some conflictual pairs?
Review of Systems: New Paradigms 5/4/01 5
What is the difference in the monad-to-dyad transformation for conflictual versus
explicitly-opposing pairs?
{Precision, truth} is another conflictual pair. If a claim is made that some variable has a
very precise value, the claim is unlikely to be true. This is partially the motivation for
fuzzy mathematics (see the quotation of Smuts cited by Klir, mentioned above). A
similar pair might be seen in {exactness, truth}, especially in the aesthetic realm, where
exaggeration is often a vehicle for conveying artistic truth not achievable by exact
representation. Related to this is {certainty, reality}, where the second term refers to
some empirical reality. Here again we encounter a justification for fuzzy logic, and
fuzziness is now offered as ontology. Similar also is {rigor, meaning} and its correlate
{syntax, semantics}, where rigor is syntactic success and meaning is semantic success.
(One might ask about the 3rd -- the pragmatic -- dimension of communication.)
With respect to the last of these pairs, Marcus notes that syntactics is often seen as
“dominating” semantics, but in Gödel’s proof semantics dominates syntactics in that “any
statement that can be proved is true, but the converse is not valid.” This recalls the post-
modernist position (from Derrida) that in every polarity, one term is “marked,” i.e.,
favored. Yet by “translating” a dyad into an alternative but nearly equivalent
terminology, the other term of the dyad may come to dominate. For example, in the dyad
of [order, disorder] as understood in physics order is marked. (This is not a conflictual
pair because the opposition is explicit and a priori.) But if [order, disorder] is translated
into [constraint, variety], it is variety which becomes the favored term. As Ashby (1976)
notes, variety is not inherently different from noise (disorder). So marked has the term
“chaos” become in contemporary scientific culture despite its disfavored past, that
Kauffman was induced (1991) to call order “anti-chaos”!
As noted, many pairs resemble other pairs. Marcus mentions Hjelmslev’s {coherence,
exhaustiveness} which resembles Gödel’s {consistency, completeness}. A quote cited
from Braque suggests {artistic relevance, clarity}, which resembles {reality, certainty}
and also {meaning, rigor}. Marcus also offers conflictual pairs from mathematics (from
numerical approximations, algorithmic complexity, formal systems, etc.), including pairs
related to randomness and negligible sets and to local vs. global properties. For example,
while it can be demonstrated that most strings are random, it is impossible to prove that a
specifically given string is random.
Towards the end of the article, conflictual sets of more than two terms are introduced.
For example, a conflictual triad based on the Arrow Impossibility Theorem is given.
(Blair and Pollak (1983) offer a more accessible formulation of Arrow’s result: no voting
system which aggregates ordinal preferences among three or more alternatives can be
rational, decisive, and egalitarian.) Marcus suggests possibilities of conflictual sets
containing more than three terms, and there seems to be no reason to preclude conflictual
sets of still higher ordinality.
It may be possible to gain insight and a more unified understanding of conflictual pairs
by “clustering” similar oppositions, trying to understand the commonalities within
Review of Systems: New Paradigms 5/4/01 6
clusters, and then trying to relate clusters to one another. Marcus presents these
conflictual sets as applying to representations, e.g., models (abstractions) of empirical
phenomena or purely conceptual (e.g., mathematical) systems. However, to return to an
earlier theme, from a different point of view some of these conflictual sets might be
regarded as being ontological in character. One might view the {position, momentum}
pair of quantum theory as reflecting not a limitation in our current representation, but an
opposition inherent in reality, which no alternative representation can ever remedy.
Similarly, the Arrow result has actual implications for democratic decision-making and is
not merely about representations of decision procedures. Corresponding to Gödel’s
result is the Halting Problem in automata theory, and while Gödel’s proof may seem to
concern only formal mathematical systems, the relevance of undecidability to automata,
dynamics, games, etc., suggests that more than mental representations may be involved.
But this debate should not distract us from the finding convincingly argued by Marcus:
the mysterious ubiquity and inter-relatedness of these conflictual pairs.
Basarab Nicolescu, “Gödelian aspects of nature and knowledge” (pp. 385-401)
It is refreshing to read in Basarab Nicolescu’s essay the plain assertion that “Reality is
not only [italics added] a social construction, the consensus of a collectivity, or some
intersubjective agreement. It also has a trans-subjective dimension, to the extent that one
simple experimental fact can ruin the most beautiful scientific theory.” This, to be sure,
is an idealization of the scientific enterprise, but Nicolescu offers an important insight
when he designates “reality” as “that which resists our expectations, experiences,
representations, descriptions, images or mathematical formalization.” If sociologists and
philosophers of science who advocate the strong constructivist position (that “reality” is
social constructed) did laboratory experiments or computer simulations, the personal
experience of such resistance might lead them to appreciate better the argument for
realism. Nicolescu also regards simple chaotic equations which generate infinities of
images as exemplifying such resistance; “resistance” thus is tied to inexhaustible
fecundity, a linkage which merits further elaboration.
A central thesis of Nicolescu’s article is that apparent contradictions, such as the wave-
particle duality, which are associated with one particular “level of reality,” may be
resolved via a third term at another level of reality where levels of reality, as distinct
from levels of mere organization, are characterized by discontinuities in fundamental
laws. Nicolescu argues that the classical and quantum domains constitutes two such
levels of reality. It is true that interpretations of quantum phenomena in terms of waves
and particles are contradictory from a classical perspective, and are united without
contradiction in quantum formalism, but more justification is needed for asserting that
classical and quantum domains are utterly discontinuous and radically different from one
another. There is today in fact extensive research on the interface between the classical
(especially the chaotic) and the quantum domains, and older links exist in physics and
chemistry between classical and quantum explanations. Nicolescu’s article is short, so he
can give only limited space to his assertion of the utter discontinuity between classical
and quantum mechanics, but since much in his article rests on this assertion, it needs a
more detailed argument. One related and minor terminological point: the quantum-
classical distinction should not be characterized as a microscopic-macroscopic
Review of Systems: New Paradigms 5/4/01 7
distinction, as quantum phenomena can occur at macroscopic scales as in superfluidity
and superconductivity.
Nicolescu implies that science supports the postulation of other levels beyond the
classical and quantum. Unfortunately no examples are given (except a passing reference
to Husserl’s phenomenology, a philosophical project outside of science), so it is hard to
grasp what Nicolescu is actually advocating. One does not need to multiply realities or
kinds of “materiality” to indicate differences other than merely compositional; one can
speak about function and its different levels.
Nicolescu’s assertion that the classical-quantum distinction “can lead us to reconsider our
individual and social life” is intriguing but left undeveloped. It is not obvious that
quantum theory is relevant to more than physics and the adjacent field of chemistry, or,
more specifically (in the context of this particular book) that it carries any implications
for systems theory, which a priori is concerned with descriptions of reality common to
more than one scientific discipline. Since Nicolescu does not offer any examples of
different levels of “reality” (or “materiality”) other than the quantum-classical
distinction, the importance he sees in quantum theory seems to favor a reductionist
viewpoint (i.e., the usual hierarchy of chemistry reducing to physics, biology reducing to
chemistry, and so on). This is hardly the systems position, and it contradicts the author’s
later denial that any level of reality should be taken as privileged.
Quantum mechanics is important for Nicolescu beyond its implications concerning levels
of reality. Nicolescu advocates a “logic of included middles,” specifically the 3-valued
logic of Lupasco (1987), and illustrates his position by pointing to the wave-particle
duality, in which a contradiction at a classical level is reconciled at the quantum level. If
A is a wave and non-A a particle, then the [A, non-A] contradiction at the classical
(lower) level is resolved by T, the system at the quantum (higher) level. Nicolescu
argues that this logical structure is open-ended, that new contradictions emerge at the
upper level which can be resolved by a still higher level. This implies the existence of a
“level of reality” higher than quantum theory, but no suggestion is given about what this
higher level might be. Contradictory pairs abound in quantum theory, but examples from
domains other than physics are unfortunately not offered.
For systems theorists, the view that classical 2-valued logic may not be adequate to
describe reality needs no justification from quantum theory, as it is well-articulated in the
systems -- especially the fuzzy -- literature, though this is not mentioned in the essay.
Nicolescu credits Lupasco with being the first to formalize a logic of the included
middle. It would have been helpful if he had explained the place of Lupasco’s work in
the literature of multivalued logic, which goes back at least to Lukasiewicz (1930) and
includes the systems-oriented non-Aristotelian logic of Varela (1975, 1979). There are
many non-classical logics, and the unique importance of Lupasco’s logic is not
explained. For a discussion of some of these issues, which also shows how Varela’s
work can be used to axiomatize a 3-valued logic proposed earlier by S.C. Kleene, see
Schwartz (1981).
Review of Systems: New Paradigms 5/4/01 8
In Marcus’ terms, Nicolescu is addressing explicit oppositions. It would be interesting if
Nicolescu would take up also the implicit oppositions which Marcus writes about. There
are many kinds of oppositions and the resolution of oppositions is a big subject.
Resolution at a higher level is one conceivable approach, but there are oppositions
resolved at the same or even at a lower level.
For Nicolescu, quantum theory has significance beyond physics by virtue of a connection
to Gödel’s proof, which applies to all formal systems of sufficient complexity. The
proposal is a radical one. Although the connection between a Gödelian level/meta-level
distinction and a classical/quantum distinction is not actually explained, the distinction
between levels in the mathematical instance does indeed have the quality of sharpness
which Nicolescu asserts for “levels of reality.” One might argue that classical
description, especially Bohr’s view of the necessity of a macroscopic description, relates
to quantum description as meta-number theory relates to number theory. This cannot
serve as an example for Nicolescu, however, because he wants quantum, not classical,
reality to constitute the higher level.
The temptation to link the quantum revolution in physics to Gödel’s revolution in
mathematics is understandable. (I have made a similar attempt (Zwick, 1978).) These
were profound discoveries, and if they can be rigorously connected, the significance of
the linkage would be considerable. The issue is the relevance of Gödelian undecidability
to science. It is unlikely that the specific formula that Gödel constructed to be
undecidable is important for science, and simply to say that science uses arithmetic which
is incomplete is also not a compelling answer to this question. One wants to know if
significant assertions about the world are undecidable. Nicolescu mentions Pauli and
Laurikainen but does not himself discuss this question or the relevant literature (e.g., in
dynamic systems theory, automata theory, algorithmic information theory) that addresses
the broader significance of undecidability.
It is not obvious how Gödel’s results involve a logic of included middle or how the level
distinction between number theory and meta-number theory in Gödel’s proof have the
form of an [A, non-A] contradiction resolved by T at a higher level. It is hard to see a 3-
valued logic in operation here because the base (number theory) level is not actually
afflicted by contradiction, only by incompleteness. There is also the issue of self-
reference. It is not apparent if Nicolescu views self-reference as involved in the
quantum-classical dichotomy. Self-reference is certainly critical to Gödel’s construction
and use of a level/meta-level mapping. It is also not clear from Nicolescu’s account if
self-reference is involved in Lupasco’s logic. Even if one interprets a 3-valued logic
(Lupasco’s or Varela’s) as encompassing a kind of self-reference, I wonder if it is a self-
reference as rich as the kind of self-reference found in Gödel’s work, which involves only
classical 2-valued logic.
Nicolescu’s attempt to connect the classical-quantum dichotomy, multivalued logic, and
undecidability is only sketched in the article, and may be more developed in his other
publications. This conceptualization is then the foundation for a wide-ranging discourse
on philosophical topics, which Nicolescu calls “the transdisciplinary approach.” I find
Review of Systems: New Paradigms 5/4/01 9
much of his discussion on this obscure (it needs some grounding resistance), but it does
offer interesting insights. For example, Nicolescu rightly observes that we need but no
longer have a coherent and rich sense of Nature. “Nature is dead, but complexity
remains.” This is a perceptive, pithy, and ironic assessment of why the “sciences of
complexity” have captured public attention. But still, I think his nearly exclusive focus
on physics has caused Nicolescu to miss the cultural potential of these sciences, which
constitute a renaissance of the systems research program. In my opinion, it is from the
systems theory/complex systems project, which addresses systems of every conceivable
type, rather than from theories in physics, that a new philosophy of nature can -- and will
-- ultimately be constructed.
More about this volume
Table 1 provides a list of the articles in this book. The diversity of topics covered is
actually not as extreme as it might be. Beyond the articles classified as “general,” the
primary topic areas in this book focus on knowledge, language, and communication, as
opposed to the subject matter of anthropology, sociology, political science, and
economics. Perhaps this is implied in the use of the phrase “human sciences” as opposed
to “social sciences” in the title. But there is also considerable material drawing upon and
relevant to the social sciences in this volume. This book has many riches which can be
mined by readers, and I anticipate returning to it to explore articles I have not yet studied.
Table 1. Table of contents
General
Peter Allen Evolving complexity in social science
Johannes Gordesch Evolutionary modeling
Hermann Haken Can we apply synergentics to the human sciences
George J. Klir From crisp systems to fuzzy systems
Erwin Laszlo Systems and societies: The logic of sociocultural evolution
Vladimir Majernik Systems-theoretic approach to the concept of organization
Solomon Marcus No system can be improved on in all respects
Helmut Schwegler The plurality of systems, and the unity of the world
Jouko Seppanen Systems ideology in human and social sciences
Rudolf Stichweh Systems theory and the evolution of science
Franz M. Wuketits Emerging systems
Semiotics
Mario Bunge Semiotic systems
Udo L. Figge Inquiries into semiotic principle and systems
Harald Schweizer Constructive contradictions
Knowledge and Cognition
Basarab Nicolescu Gödelian aspects of nature and knowledge
Gert Rickheit &Hans
Strohner Cognitive systems theory
Culture
Michael Fleischer Concept of the ‘Second Reality’ from the perspective of an
empirical systems theory on the basis of radical
Review of Systems: New Paradigms 5/4/01 10
constructivism
Adam Nobis Self-organization of culture
Music
Moisei Boroda Systemic organization and the development of the
European musical language
Reinhard Kohler & Zuzana
Martinakova-Rendekova A systems theoretical approach to language and music
Language
Hans Goebl On the nature of tension in dialectal networks
Ludek Hrebicek Hurst’s indicators and text
Helmut Schnelle A note on language competences as dynamic systems
Wolfgang Wildgen Chaos, fractals, and dissipative structures in language
Literature
Floyd Merrell Fractopoi, chaosmos, or merely simplexity-complicity?
Siegfreid J. Schmidt A systems-oriented approach to literary studies
In lieu of an EPILOGUE
Walter A. Koch Systems and the human sciences
To reiterate a point made at the outset of this review, such a wealth of material calls for a
coherent framework which might organize it. It is unfortunate that although one of the
prime motivations of the systems movement is the integration of knowledge from a
variety of disciplines, the field itself desperately lacks integration of its own ideas and
methods. Collections such as this volume are valuable resources, but in addition to such
collections and expositions reflecting the viewpoints of particular researchers, we need
synthetic works, better yet, textbooks, aimed at the development of a systems science
canon.
Acknowledgement
I thank Wayne Wakeland for helpful comments on this manuscript.
References
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Blair, D. H. and Pollak, R. A. (1983). “Rational Collective Choice.” Scientific American,
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Bunge, M. (1973). Model, Model, and Matter. Boston: D. Reidel.
Kauffman, S. (1991). “Anti-chaos and Adaptation” Scientific American, Aug., pp. 78-84.
Klir, G. J. (1985). Architecture of Systems Problem Solving. New York: Plenum Press.
Klir, G. J.(2000). Personal communication.
Lovejoy, A. (1936). The Great Chain of Being. Cambridge: Harvard University Press.
Review of Systems: New Paradigms 5/4/01 11
Lukasiewicz, J. (1930). Philosophical remarks on many-valued systems of propositional
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Book
1. Introduction: On Method in the Philosophy of Science.- I: Scientific Method.- 2. Testability Today.- 3. Is Biology Methodologically Unique?.- 4. The Axiomatic Method in Physics.- II: Conceptual Models.- 5. Concepts of Model.- 6. Analogy, Simulation, Representation.- 7. Mathematical Modeling in Social Science.- III: Metaphysics.- 8. Is Scientific Metaphysics Possible?.- 9. The Metaphysics, Epistemology, and Methodology of Levels.- 10. How do Realism, Materialism and Dialectics Fare in Contemporary Science?.- Name Index.
Article
There is a story about two friends, who were classmates in high school, talking about their jobs. One of them became a statistician and was working on population trends. He showed a reprint to his former classmate. The reprint started, as usual, with the Gaussian distribution and the statistician explained to his former classmate the meaning of the symbols for the actual population, for the average population, and so on. His classmate was a bit incredulous and was not quite sure whether the statistician was pulling his leg. “How can you know that?” was his query. “And what is this symbol here?” “Oh,” said the statistician, “this is π.” “What is that?” “The ratio of the circumference of the circle to its diameter.” “Well, now you are pushing your joke too far,” said the classmate, “surely the population has nothing to do with the circumference of the circle.”