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Chaos theory emerged in the physical sciences as an explanatory framework for processes that appeared disorderly, such as turbulence or weather patterns, but which had complex mathematical models behind their seeming randomness. However, theories which are predictive chemistry or physics fall short of explanation for the diverse phenomena and larger standard error margins of human behavior. The apparent promise of chaos or complexity theories for sociology is their tolerance for ambiguity, uncertainty or unpredictability, and their assertion that apparent disorder in human behavior may in fact be orderly at a higher level than we are measuring.
Few sociological studies have been published that successfully apply chaos or complexity mathematics to empirical social research results. Journal articles use concepts and models of chaos or complexity as metaphors, and they may fail to distinguish between the two theories.
Promising sociological research directions may be found in the incorporation of fuzzy set theory to social science research methods. ”Fuzzification,” according to its originator Lotfi Zadeh (1965), is a methodology used to generalize a specific theory from a crisp (discrete) to a continuous (fuzzy) form. Members of a fuzzy set may or may not have full membership in the discrete sense, but are assigned a value indicating their degree of possible membership.
Bibliography:
- Kiel, L. D. & Elliott, E. W. (eds.) (1997) Chaos Theory in the Social Sciences: Foundations and Applications. University of Michigan Press, Ann Arbor, MI.
- Zadeh, L. (1965) Fuzzy sets. Information and Control 8: 338-53.
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