The statistical relations between a great number of seemingly not causally ordered elements.
According to I. BLAUBERG, V. SADOVSKY and E. YUDIN: "(Classical science) was chiefly concerned with solving two-variables problems, establishing the causal relations between two phenomena, determining linear causal chains for a relatively small number of objects" (1977, p.200).
As noted by these authors, this was basically deductive science, and could not cope with "… the problem of discovering the diversity of links and relations existing inside the analyzed object and its interactions with other objects" (p.201).
The closest approach to this type of problems was classical statistics, whose laws are basically quantitative and allow merely to tally, classify and extrapolate or interpolate (without much security), i.e. look for some hidden order within "a great number of seemingly not causally ordered elements", as for example in composite systems.
The expression "Unorganized complexity" was coined by W. WEAVER in 1948, and commented by him as referred to problems "… in which the number of variables is very large, and in which each of the many variables has a behavior which is individually erratic, or perhaps totally unknown. However,… the system as a whole possesses certain orderly and anaIyzable average properties".(1948, p.536).
In G. WEINBERG's words such systems being "… sufficiently random in their behavior… are sufficiently regular to be studied statistically" (1975, p.16).
WEAVER observed however that in this way, the enormous domain of systems with more than two, but less than an astronomical number of variables was still left untouched (Ibid). Chaos theory is now progressively covering this ground. (See G. BROEKSTRA, 1994, p.1099).
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Bertalanffy Center for the Study of Systems Science (2020). Title of the entry. In Charles François (Ed.), International Encyclopedia of Systems and Cybernetics (2). Retrieved from www.systemspedia.org/[full/url]
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