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| Scale (Scaling Law):
The level at which a system is observed. For example, one can observe the coast of England from a satellite or from a jet liner or from a low flying plane, or from walking along the coast, or from peering down into the sand and rock of a cove beach you are standing on. Each of these perspectives is of a different scale of the actual coast of England. Fractals are geometric patterns that are self-similar on different scales. See: Fractal; Power Law Bibliography: Kaye (1989) A term referring to the internal models of a complex, adaptive system. The idea of a schema is related to how the term is used in Cognitive Psychology to refer to a way information is organized and thought about. Our perceptions are determined by a combination of external stimuli and internal schema. See: Internal Models; Mental Models Bibliography: Gell-mann (1994); Holland (1995); Stacey (1996) In a social system, a self-fulfilling prophecy is a vicious circle that takes place when an expectation (prophecy, belief, mental model) leads to actions culminating in results that serve to confirm the validity of the original expectation. An example is when a bank collapses because depositors expect (or prophecize ) that the bank will fail leading to the behavior of a large scale withdrawal of funds, and thereby, the fostering of the eventual failure of the bank. Self-fulfilling prophecies serve to keep out information that is contradictory to the original expectations operating on the system. The circular feedback between expectation, actions, and results can serve to keep organizations locked in particular constrained types of behavior. Far-from-equilibrium conditions can be used to disrupt the status quo effect of self-fulfilling prophecies. See: Difference Questioning; Equilibrium; Far-from Equilibrium; Purpose Contrasting Bibliography: Goldstein (1994) A process in a complex system whereby new emergent structures, patterns, and properties arise without being externally imposed on the system. Not controlled by a centralized, hierarchical "command and control" center, self-organization is usually distributed throughout a system. Self-organization requires a complex, nonlinear system under appropriate conditions, variously described as "far-from-equilibrium," critical values of control parameters leading to "bifurcation," or the "edge of chaos." First studied in physical systems by Ilya Prigogine and his followers, as well as the Synergetics School founded by Hermann Haken, self-organization is now studied primarily through computer simulations such as cellular automata, boolean networks, and other phenomena of Artificial Life. However, self-organization is now recognized as a crucial way of understanding emergent, collective behavior in a large variety of systems including: the economy; the brain and nervous system; the immune system; ecosystems; and the modern large corporation or institution. The build-up of system order via self-organization is now conceived as a primary tendency of complex systems in contrast to the past emphasis on the degrading of order in association with the principle of entropy (Second Law of Thermodynamics). However, rather than denying entropy, self-organization can be understood as a way that entropy increases in complex, nonlinear systems. See: Coherence; Dissipative Structures; Emergence; Far-from-equilibrium Bibliography: Eoyang (1997); Goldstein (1994); Nicolis (1989) Self-organized Criticality (SOC): Formulated by the physicist Per Bak, a phenomena of sudden change in physical systems in which they evolve naturally to a critical state at which abrupt changes can occur. That is, when these systems are not in a critical state, i.e., they are characterized by instability, output follows from input in a linear fashion, but when in the critical state, systems characterized by self-organized criticality act like nonlinear amplifiers, similar to but not as extreme as the exponential increase in chaos due to sensitive dependence on initial conditions. That is, the nonlinear amplification in a self-organized, critical system follows a power law instead of an exponential law. SOC systems are self-organized in the sense that they reach a critical state on their own. Examples of such systems include avalanches, plate tectonics leading to earthquakes or stock market systems leading to crashes. Because SOC systems follow power laws, and because fractals also show a similar mathematical pattern then it may be the case that many naturally occurring fractals, such as tree growth, the structure of the lungs, and so on, may be generated by some form of self-organized criticality. See: Bifurcation; Catastrophe; Instability; Power Law; Self-organization Bibliography: Bak (1996); Peak & Frame (1994): Waldrop (1992) Sensitive Dependence on Initial Conditions (SIC): The property of chaotic systems in which a small change in initial conditions can have a hugely disproportionate effect on outcome. SIC is popularly captured by the image of the Butterfly Effect. SIC makes chaotic systems largely unpredictable because measurements at initial conditions always will contain some amount of error, and SIC exponentially increases this error. See: The Butterfly Effect Bibliography: Goldstein (article on Planning in this volume); Lorenz (1993); Peak and Frame (1994) The management/ complexity theorist Ralph Stacey’s term for the set of informal relationships or networks among people in an organization which exists in tandem with the official and "legitimate" network or hierarchy. The shadow organization is not focussed on the same stabilizing objective as the official organization, so it is a ripe ground for the instability required for self-organization and the emergence of more adaptable organizational structures and processes. Effective leaders take into consideration both the mainstream and the shadow systems, even capitalizing, according to Stacey on the potential friction between them. See: Edge of Chaos; Far-from-equilibrium Bibliography: Stacey (1996) The opposite of "instability," therefore, the property of a system which stays pretty much the same after being disturbed by internal or external forces or events. For example, the deeper the keel of a sailboat, the more stable it is regarding the wind and currents. A running gyroscope is stable with respect to changes affecting its centrifugally determined level plane. Sometimes used as synonymous with equilibrium or with the state of a system trapped within a particular attractor regime. See: Equilibrium; Far-from-Equilibrium; Instability Bibliography: Nicolis (1989); Prigogine and Stengers (1984) Two terms coined by the editor of Wired Magazine Kevin Kelly for two antithetical management processes. "Clockware" are rational, standardized, controlled, measured processes; whereas "swarmware" are processes including experimentation, trial and error, risk-taking, autonomy of agents. Clockware processes are seen in linear systems whereas swarmware is what happens in complex systems undergoing self-organization as a result of the nonlinear interaction among components. See: Cellular Automata; Complex, Adaptive System; Self-organization Bibliography: Kelly (1994) |
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