Theoretical Applications in Sociology: Critical Theory vs. Systems Theory
Exciting advances are being made in the development and application of sociological theories to social work practices. Two of the foremost theories are systems theory -- currently undergoing an architectural evolution due to the implications of the chaos and complexity disciplines -- and critical theory, which seeks to change the current systematical frameworks of society for the better. For the purposes of this paper, I will compare and contrast the two theories, highlighting the similarities between them as well as the segments of departure and their practical implications. I will then apply both theories to a single case study in order to show the strengths and weaknesses of each theory in practice.
In "New Directions in Systems Theory: Chaos and Complexity," authors Warren, Franklin and Streeter examine how advances in the chaos and complexity disciplines are instigating an evolution of traditional systems theory. While in the past, systems theorists have typically argued that systems are rational, orderly, and essentially stable as governed by "boundaries, homeostasis, and equilibrium" chaos and complexity theorists argue that the system only becomes rational and orderly after a preceding stage of chaos, and that the most complex systems -- such the human family -- exist "on the edge of chaos and order" as opposed to a completely chaotic or completely orderly sphere (Warren, Franklin & Streeter, 1998). The chaos and complexity disciplines arose from the need to understand changes in systems that don't necessarily adhere to linear cause and effect models, i.e. nonlinear dynamics. Rather than A leading to a proportional B. As is the case in a linear cause and effect model, nonlinear dynamics refers to cases in which A and B. are disproportional and essentially unpredictable. Warren et al. put forth the example of a mounting argument between a child and parent. While in a linear system, the child's rise in pitch would result in a proportional rise in pitch in the parent's voice, in a nonlinear system, the child's rise in pitch could result in silence, no change in the parent's voice, or a disproportionally high rise in the pitch of the parents voice. The argument here is that the tiniest difference in pitch as perceived by the parent could result in any number of reactions, hence the erratic and unpredictable nature of nonlinear systems. Put in more general terms, the smallest change or modification of A -- the cause -- can result in a number of possible altercations of B -- the effect -- from the truly proportional to the outlandishly disproportional.
Another example of the often disproportional relationship of cause and effect was the introduction of VHS vs. Beta videotape players in the 1980s. As Warren et al. explain, while VHS and Betas was introduced to the consumer market at around the same time and sales were initially proportional between them, at some point VHS sales slightly exceeded Beta player sales, resulting in more people buying VHS videotapes for their new VHS players, which in turn resulted in video stores stocking more VHS tapes than Beta tapes, which in turn led to more people buying VHS players in order to watch the VHS tapes now available at their local video stores. In the end, the Beta videotape and videotape player disappeared from the market altogether, and the VHS prevailed as the predominant format of home movie viewing. This is an example how the slightest change in a cause can inevitably snowball, resulting in a dramatic and disproportional change in its effect (Warren et al., 1998).
In more human terms, Warren et al. cite the human learning process as an example of a change in a cause snowballing to a disproportional effect. According to child psychologist Jean Paiget, as the mind of a child develops it continually integrates new knowledge as received from its environment with existing knowledge, resulting in the practiced ability to acquire knowledge more easily, with in turn results in the ability to perform higher thought processes, further enhancing the ability to learn. In other words, the more you learn, the easier it is to learn, which in turns allows you learn more. This is an example of chaos and complexity theorists call "nonlinear growth" (Warren et al., 1998)
The process of nonlinear growth does not continue forever. Rather, after continuing on in this chaotic and predictable fashion for a certain time, the system with eventually attempt to stabilize and reorganize itself, resulting in a growth plateau. For example, a person goes on a diet and loses three to six pounds a week for the first four weeks, only to lose no weight in the fifth week. This is an example of the system -- the person's body -- attempting to stabilize itself in resistance to nonlinear change. Yet even this resistance is chaotic and unpredictable, as a weight loss "plateau" could last for a week, three days, two weeks or five years, depending on the many potential actions of the system's agent, in this case the person. If the person responds to the plateau by further decreasing her calories and/or increasing her level of activity, the weight loss plateau could last no more than a few days. On the other hand, if the person becomes discourages by the plateau and gives up, she might either maintain her weight for several months or years, or possibly even gain weight. In this way, systems theory as perceived in the chaos and complexity frameworks is necessarily empowering of the individual agent, as the actions of the agent are essentially a cause that can result in any number of effects.
The systems theory of "structural determinism" purports that a "living system [is] an expression of its structural connections, which in turn determine all its operations" (Warren et al., 1998). The system is therefore autonomous and "self-organizing" and any changes in the system is a result of the system "pushing itself" to attain higher and higher levels of organization (Warren et al., 1998). In this initial push, the system uses resources made available by its exterior environment, termed "positive feedback"; when these resources are depleted -- "negative feedback" -- a plateau in growth occurs. The duration of the plateau is dependent on how quickly the system is able to replenish the resources it needs to support and sustain growth, at which time another "growth spurt" may occur (Warren et al., 1998). In this way, the system's evolution is continuous and never complete, as growth continually leads to plateaus and plateaus are continually broken in an infinite cycle of change. An example of this continual cycle, as put forth by Warren et al., is the continual development of a person's sense of self:
According to cognitive therapists such as Guidano (1991) and Mahoney (1991), a person's development of a sense of self goes through a process similar to the one described earlier. A person adapts new knowledge from his or her environment to match his or her personal meanings. All pushes for personal changes in self from the environment are subsumed under the person's core constructs or present experiential order. Life experiences and subsequent pushes from the environment, however, result in the "discontinuous emergence of more inclusive knowledge of self and of the world" (Guidano, 1991, p. 9). This also means that as a person adapts to the environment he or she also changes the environment, which in turn is influencing them. Thus, a recusive feedback loop is established. (Warren et al., 1998)
The development of a sense of self is also an example of a highly complex system -- the human mind -- at work in creating itself, which in turn has a creative effect on the system's environment. According to complexity theorists, "the local interactions of individual [systems] give rise to a global system," and the focus of complexity theory is on "the ways in which those local interactions act to maintain and increase the complexity of the system" (Warren et al., 1998). In terms of people, a person's creation of self is a contributing cause of the effect of the creation of the environment, and even the slightest change in a person's perception of self can have a dramatic impact on the global system as a whole.
The notion of a human being as a self-organizing system autonomously determinant of its own evolution leads to the corresponding of notion of what complexity theorists call "path dependence" (Warren et al., 2008). Essentially, path dependence purports that two systems can begin in the same place and end in two completely different places, depending on the actions of the autonomous systems in question. For example, two brothers are born and raised in the same inner-city slum. One brother chooses to neglect his studies, drop out of school and join a local gang, while the other brother studies hard, graduates high school and goes on to college. Though they both began in the same place -- even within the same household -- they're opposing decisions led…