Chaos theory or complexity theory distinguishes the presence of social disorder from order within social disorder. The notion of patterned regularities operating deep within the apparent randomness of dynamic systems (including the behavior of society as a macro/micro system) challenges the assumptions informing correctional, psychiatric, and/or legal practice.

Many pundits invoke chaos theory to complain about frustrations with daily life, which is a disservice to the task of highlighting the important insights of chaos theory. According to complexity theory, there is a hidden order to the behavior of complex systems, as in a national economy, an ecosystem, an organization, or a production line. Research on complexity theory originates from the Sante Fe Institute in New Mexico, a mecca for those studying complexity theory. Scientists at the Sante Fe Institute Institute claim that through the study of complexity theory, one can see not only the laws of chaos, but also those of order.

Chaos Theory is the popular term used to describe a novel, quite revolutionary
approach to a wide range of mathematical, pure science, and applied science fields.
Instead of** **the term chaos theory many people prefer the terms
"complexity theory" or "dynamic systems theory." Chaos theory is a new
paradigm, that transcends the limitations of conventional
science. The fundamental lesson of chaos theory is that the
behavior of a wide range of dynamic systems is extremely sensitive to minute fluxes in initial conditions, thus making it virtually
impossible to obtain accurate medium-term and long-term predictions.

People who have heard of Chaos theory associate it with the idea that tiny disturbances can cause enormous long-term differences. In the movie Jurassic Park, the actor Jeff Goldblum speaks about the 'butterfly effect', that a butterfly flapping its wings could set in motion a sequence of self-reinforcing events that would ultimately result in a hurricane on the other side of the world. While within the realm of possibility, this image has reduced Chaos theory as conceived by most people into a generic cliche that the world's just a unpredictable mess.

The purpose of the Society for Chaos Theory in Psychology and Life Sciences is to provide a forum for scholars and practitioners who share an interest in the application of nonlinear dynamical systems models in psychology, social sciences and life sciences. Members of SCTPLS share an interest in a wide range of nonlinear dynamical phenomena, such as chaos theory, catastrophe theory, fractal geometry, and far-from-equilibrium systems, and they appreciate the wide range of possibilities for application in such areas as clinical and organizational psychology, neurobehavioral science, medicine, economy, biology and education. - Society for chaos theory.

**Chaos Theory and Its Implications for Social
Science Research** - Hal Gregersen, Lee Sailer.

Based on theoretical and mathematical principles of chaos theory, we argue that
the customary social science goals of "prediction" and "control" of systems
behavior are sometimes, if not usually, unobtainable. Specifically, chaos theory
shows how it is possible for nearly identical entities embedded in identical
environments to exhibit radically different behaviors, even when the underlying
systems are extremely simple, principally determinism,
which is contrasted with free will.

Furthermore, chaos theory arguments are general enough to apply to any type of entity, including individuals, groups, and organizations, and therefore they are relevant to a large domain of social science problems. As a result, this paper concludes with six familiar claims about the study of social phenomena for which chaos theory provides new theoretical arguments.

**Social Structures and Chaos Theory** - Smith, R. D. (1998),
Sociological Research Online, vol. 3, no. 1.

Abstract: Up to this point many of the social-scientific discussions of the impact of
Chaos theory have dealt with using chaos concepts to refine matters of prediction and
control. Chaos theory, however, has far more fundamental consequences which must also be
considered.

This paper attempts to show that such social and structural concepts as class, race, gender and ethnicity produce analytic difficulties so serious that the concept of structuralism itself must be reconceptualised to make it adequate to the demands of Chaos theory. The most compelling mode of doing this is through the use of Connectionism.

The
paper will also attempt to show this effectively means the successful inclusion of Chaos
theory into social sciences represents both a new paradigm and a new epistemology and not
just a refinement to the existing structuralist
approach
models. Research using structuralist assumptions may require reconciliation with the new
paradigm.

**Chaos Theory and the Social Sciences**

In this paper, I examine three ways researchers in the social sciences have used chaos
theory. These examinations are part of an ongoing project to understand what chaos theory
means and what it does not mean, as a way to investigate the general question of how
research in the physical sciences is and ought to be translated across
disciplines. The first type of use of chaos theory is the application of mathematical
techniques. In the physical sciences, a typical experimental situation will yield a long
series of measurements, from which a "strange attractor" can be sought in
reconstructed phase space. Under what circumstances can the mathematical
techniques of nonlinear dynamics and chaos theory be applied to social systems?

**CHAOS: The Geometrization Of Thought** - (Talk given to the Chaos in
Psychology Association) F. David Peat.

Introduction: As a result of the popular books and magazine articles that have appeared
over the last few years the topic of chaos theory has become familiar to many people. For
example, the image of "butterfly effect" is often applied to systems so
extraordinary sensitive that a perturbation as small as the flapping of a butterfly's
wings produces a large scale change of behavior. While chaos theory holds that such
systems remain strictly deterministic they are so enormously complex that the exact
details of their behavior are, in practice, unpredictable even with the aid of the largest
computers.