The epistemological predicament associated with purposive quantitative analysis

Abstract

This paper discusses the epistemological predicament associated with the formal modeling of the behavior of complex adaptive systems. This is a class of systems which: (i) express functions and structures on multiple levels and scales; and (ii) become “something different” in time, because of evolution. The paper addresses four points. (#1) The pre-analytical definition of “what is observed and how” is essential in determining any quantitative output of mathematical models. Scientists have to learn how to acknowledge and to deal better with the fact that the observer always affects what is observed when defining the descriptive domain. This influence of the observer occurs even before there is interaction with the observed in the process of gathering empirical data. (#2) The peculiar human ability to share a commensurate experience involves the concept of semiotic identity. The generation of knowledge is possible only because of the co-existence of a semiotic reality and physical systems. (#3) The special organization of living systems depends on their ability to establish and maintain a semiotic coupling between functional and structural types. This coupling is associated with the concept of holon and explains why it is impossible to formalize in substantive terms organizations recognized as holons. Holons can only be handled in semiotic terms. (#4) A strong semiotic identity entails an uncontested selection of an appropriate sampling procedure for validating the choice of the formal identity used in the model. On the contrary, a weak semiotic identity entails a tautology in the modeling relation. The formal identity used to represent the semiotic identity in the model has also to be used to decide about the relative sampling used for validation. The distinction between strong and weak semiotic identities places a limit on the power of modeling. A sound modeling relation requires strong semiotic identities, whereas the typical issues associated with science for governance imply perceptions and representations based on weak semiotic identities.