RIGOR AND RELEVANCE IN SYSTEMS WORK

Conceptual models which, in simplifi ed and therefore comprehensible form, try to represent certain aspects of reality, are basic in any attempt at theory; whether we apply the Newtonian model in mechanics, the model of corpuscle or wave in atomic physics, use simplifi ed models to describe the growth of a population, or the model of a game to describe political decisions. The advantages and dangers of models are well known. The advantage is in the fact that this is the way to create a theory – i.e., the model permits deductions from premises, explanation and prediction, with often unexpected results.

The danger is oversimplifi cation: to make it conceptually controllable, we have
to reduce reality to a conceptual skeleton – the question remaining whether, in doing so, we have not cut out vital parts of the anatomy. The danger of oversimplifi cation is the greater, the more multifarious and complex the phenomenon is. This applies not only to “grand theories” of culture
and history but to models we fi nd in any psychological or sociological journal (p. 200) Rigorous methods and tools for observation and experimentation, combined with mathematical calculations, led to astounding discoveries in astronomy and physics. These allowed for discoveries in chemistry, biology, and the many expanding fi elds of science, along with applications in medicine, engineering, technology, and other areas. Did this progression imply a natural hierarchy, though? Was physics the basis for all science (the reductionist point of view) or were there boundaries between different realms, to which different principles applied?