Sociosystemics, statistics, decisions

摘要

The current condition of knowledge about social world as reflected in political sciences, economics, management sciences, sociology, psychology, and their many derivatives is in deep disarray. It can be observed in the poor representation of the obtained results of scientific findings in practical issues as well as in the internal problems and inconsistencies within the respective branches of science. The exponentially growing volume of information in these areas is supplemented with less than linear growth of real knowledge, and even this one cannot be considered "hard knowledge" for many reasons. This phenomenon is not new, but the alarming gap between two flows of symbolic realm on the one hand, and between these flows as a whole and real practices on the other hand, is growing faster with every year. Further scientific specialization seems just to widen this gap. A need for some unifying principles overcoming narrow boundaries of particular sciences and even their composites (like behavioral economics or social psychology) becomes more and more clear. The attempts to solve universal problems using such grand concepts as general theory of systems, cybernetics, sociophysics, statistics have yielded many brilliant results, but haven't proven to become the sought-after unifying frame in many aspects. One of the reasons for that was their orientation to specific types of models, which, applied to social reality, do not work as expected. In this article, I'll try to introduce some principles of a new science, sociosystemics, which will hopefully help to transform over the cross a time the enormous volume of social information into meaningful knowledge to be used for analysis, prediction, finding innovative solutions, and decision making.