Empirical Generalization Method

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There are two components in Vernadsky's concept of the biosphere. The first is the proper biosphere concept, which can be called a verbal model of the biosphere. The second component is the method of study of such a complex system as the biosphere, which he called the 'empirical generalization method' (EGM). Vernadsky opposes the reliance on mere hypotheses, repeatedly insisting that the better suited method for a scientist is the Baconian system of accumulation of facts, as the generalizations become apparent from the data. That is essentially an inductive method and it indeed lies at the heart of the modern science. A perfect example of this method is the Periodic Table of the elements by Mendeleev. Certainly, the EGM is essentially wider than a method for the study of biosphere processes; it is a general scientific method. Let us remember Descartes' principle that ''Science is a method.'' Speaking in modern terms, the EGM is a typical method of systems analysis.

The empirical generalization is based on real facts collected in an inductive way, keeping in mind not to leave the domain of these facts. At this first stage all possible scientifically established facts about studied phenomenon must be collected. The next stage is the aggregation of collected facts into some more general categories, called proper empirical generalizations. Basically, it gives us the possibility to pass from a huge number of accumulated facts to a considerably lesser number of statements that, in turn, allows us to truly speak about the possibility to describe the studied large (complex) system quantitatively. This stage does not allow formulating any kind of hypothesis, on which there is inevitably a mapping not only of scientific ideas, but also of nonscientific ones.

Really an empirical generalization is a system of axioms, reflecting our level of empirical knowledge, which could be used as a basis for any formal theory developed in the future.

Hence, having the system of empirical generalizations, we can follow either of two ways, when we are constructing models. Either we remain within the framework of this system, constructing so-called 'phenomenological'

models, or complementing some hypotheses relating to the existing empirical generalizations, we shall get some new models. In accordance with Vernadsky's opinion, the choice on the set of these models, hypotheses must be produced by the coincidence of predicted and observed again facts. If this coincidence takes place, then the hypothesis becomes an empirical generalization of a higher level. From this point of view, for example, the practical astronomy of Ancient World was a typical empirical generalization, and ancient astronomers were successfully using the phenomenological model created on its basis. The same underlying empirical generalization is the basis of two principally different cosmogonic hypotheses by Ptolemee and Copernicus. If and only if new facts had appeared, the Copernicus cosmogony would have become a new empirical generalization. Therefore, the same empirical generalization can be a basis of different models.

However, the reciprocal picture can be possible, when an empirical generalization exists separately, without some kind of hypotheses and explanations from the viewpoint of contemporary science. For example, the radioactivity phenomenon could not be explained in frameworks of the physics of nineteenth century.

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