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Complex Systems of Meaning

Page history last edited by Mark 9 years, 11 months ago

Complex Systems of Meaning

 

Cilliers (2005) provides a concise, but useful, summary of complex systems framed in the context of their applicability to organizations. Complex systems are comprised of a large number of elemental components, any (or all) of which may be simple. These elements exchange information via interactions, the effects of which propagate throughout the system. Because complex systems – and in particular, systems that are interconnected via a network – contain many direct and indirect feedback loops, interactions are nonlinear with non-proportional effects. This means that seemingly small interactions may have quite substantial effects throughout the system, and what appear to be substantial interactions may have quite insignificant system-wide effects. Complex systems are open with respect to their environment, which means that there are continuous information exchange processes among the system, its components, and their mutual environment.

 

Complex systems also possess memory – a history of interactions, exchanges and effects – that is distributed throughout the system, and influences the behaviour of the system. This memory is significant: the behaviour of the system is determined by the nature (effects) of the interactions, not by the content of the components. Hence, the overall system’s behaviour is unpredictable based on an understanding of the components’ individual behaviours alone. The resultant patterns of system behaviour are called emergence, and refute models predicated exclusively on deterministic causality. Finally, complex systems are adaptive, and can reorganize their internal structure based on information exchange, as opposed to the action of an external agent (Cilliers, 2005, p. 8-9).

 

Weick (2001) cites Gergen’s (1982) three principles of constructivism that I recount here, with particular points of comparison with complex systems emphasized: (a) as events occur, they change the emerging current context from which both earlier and subsequent events have meaning; (b) the reference against which the interpretation of any event is contextualized is itself the product of a network of interdependent events and interpretations, often mutually and collectively negotiated among a network of people; (c) as a consequence of the previous two principles, the meaning of any given event is interpreted differently by different people, with collectively agreed meaning being achieved through processes of consensus, or the exercise of power (Weick, 2001, p. 10).

 

Complex systems are often described in mathematical terms using Henri Poincaré’s topological approach. In mathematics, and particularly in topology, solutions to sets of nonlinear equations are often depicted as sets of curves drawn through an n-dimensional phase space, where n represents the number of variables in the equations. A point that “travels” along one of these curves defines the state of the system at any time; its movement over time is called its trajectory[1]. The trajectory of the point is called an attractor, with three topologically distinct forms: point (a system that eventually reaches stable equilibrium, representing the end of change and growth; i.e., death), periodic, meaning a system that has regular oscillations between two states, and strange that applies to chaotic systems such as those characterized by Cilliers as exhibiting properties of complexity.

 

Strange attractors tend to create distinct patterns of trajectories for a given system, although the precise location of a point in phase space at a particular time cannot be accurately determined. This means that the system is non-deterministic – its future state cannot be accurately predicted from its past state(s). Substantial changes in the type, shape, or existence of an attractor, corresponding to substantive changes in the nature of the defining parameters (e.g., contextual ground of the system), is called a bifurcation point, and marks a state of instability from which a new order of greater complexity can emerge (Capra, 1996).

 

Now, consider a system of meaning, such as that typically described as emerging from empirical observations analyzed according to a particular research paradigm. Constructivism holds that people confer meaning onto their lived experiences by virtue of a complex intermingling of individual and collective past experiences that provide context – in other words, the system’s history – to current perceptions of events. A (contingently) stable meaning or interpretation can be considered to be an emergent property of that system of lived experiences. In complexity terms, that stable meaning can be described as one point along a trajectory of meaning that travels through a phase space defined by a set of parameters that might include individual history and memory, group history or collective memory, consensus processes, cultural influences, normative behaviours of one or more social networks, and other similar factors, forces and causes[2].

 

A person’s constructed reality, that is, the trajectory of meaning through the phase space of lived and interpreted experiences, can become disrupted when one or more of the parameters of that phase space significantly change. Although an individual may attempt to hold onto familiar, “privileged” (Weick, 2001) interpretations, the time during which the formerly stable meaning becomes disrupted is chaotic, and hence, often confusing for the individuals and groups concerned. At the bifurcation point, sufficient interpretive energy must be injected into the meaning system to enable emergence: the creation of a new stable state of higher order than before. In other words, the creation of new meaning and interpretation of events that is significantly different from the person’s prior understanding informs future sense- and meaning-making. This complexity understanding of meaning-making not only informs the current research process; it will also provide a useful framework through which I will later contextualize processes of organizational change.

 

Because the research seeks to discover what is expected to be a radical shift in organizational perception – from BAH to UCaPP – the specific methodology employed must be a sufficiently sensitive instrument to be able to recognize and report on any potential bifurcation that might occur during the time scope of the research, or laterally among the participating individuals and organizations. The methodology most appropriate to this undertaking is constructivist grounded theory, as characterized by Kathy Charmaz (2000).

 

 

Read on: Regrounding Grounded Theory

 


[1] This concept is most easily imagined as a point moving through physical space relative to reference axes of length, width, and breadth. At any time, the “state” of the physical system can be defined in terms of the point’s position; its path through space is the trajectory. Similarly, in a complex system, there would be more dimensions, each dimension, or variable, referring to a parameter that uniquely defines an aspect of the system being described.

[2] Used in the Aristotelian sense of formal, material, efficient, and final causes, as opposed to linear, deterministic causality.

 

 

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