Der quantitative Beitrag der nach 1933 emigrierten Naturwissenschaftler zur deutschsprachigen physikalischen Forschung

By scientiometrically analyzing the physics-literature produced between 1925 and 1933 it is shown that the purely quantitative contribution of physicists subsequently emigrating from Germany to the literature produced by the physics community in this country was much lower than hitherto estimated. The actual figure is not in the range of 30%, as is generally assumed, but much nearer to 11%. Control analysis of three leading German physics journals and of memberships in the Deutsche Physikalische Gesellschaft confirms this result. Further investigation of university calendars shows that transferring these results to purely academic physics would amount to committing a “universalistic fallacy”. In academic physics emigré-physicists held a total of 15,5% of all teaching postitions. Differentiating the physics literature into various specialties allows further insights into the cognitive and social structure of the German physics community before 1933. Works of emigré-physicists are not randomly distributed over specialities; instead, the distribution reveals a nearly perfect correlation with what could be called “the specialty's paradigmatic age”. The spectrum begins with quantum theory, where future emigrants produced more than 25% of the literature, and fades away with acoustics, where their contribution amounts to less than 4%. The commonly accepted explanation of this phenomenon, which is based on the assumption that time of institutionalization of a specialty, “prestige” of that specialty, and entrance barriers for Jewish scientists are correlated, is falsified by two cases of non- or zero-correlation: by the very old specialties and by the technical disciplines. A new explanans is proposed which is based on the hypothesis of cognitive and social marginality being correlated and on a certain amount of cognitive marginality enhancing the disposition to innovative behavior and creativity.     

Wissenschaftswachstum in wichtigen naturwissenschaftlichen Disziplinen vom 17. bis zum 21. Jahrhundert

The Growth of Science within Important Scientific Disciplines from 17th to 21st century. – In this paper the growth of knowledge is investigated for the disciplines of Astrophysics / Astronomy, of Physics and of Chemistry in the last centuries. In this context the main emphasis is devoted to the discussion of the growth of literature. Besides, this is also illustrated by the growth of indicators like for example important books, new discoveries in science, the chemical elements, the known chemical compounds and the number of known inorganic chemical structures. Compared to numerous earlier studies a systematic evaluation of all presently available data sources is carried out. The data are fitted by different mathematical growth models (linear, quadratic, exponential, hyperbolic). These are discussed and compared. As far as the exponential growth model is applied the doubling periods obtained have values between 11 and 32 years for the cumulative total of publications, between 24 and 98 years for that of important books, between 79 and 163 years for that of new discoveries and between 10 and 14 years for that of chemical substances. From an order of magnitude point of view this is in agreement with the results of other authors. It is however also demonstrated that the exponential growth model which is normally used is not necessarily the best to describe the growth of the data. Other models are often better suitable to explain the growth. It is shown that linear growth of the yearly publications describes the data better than exponential growth in certain epochs. In this latter case it is demonstrated that the parameter (linear slope) for the rate of increase has a constant values in certain epochs, but rises in steps from epoch to epoch by a factor of 3 to 40. After the second world war the linear growth model for the yearly publications or the quadratic growth model for the cumulative total of publications respectively delivers the best results. This is therefore used for forecasting the future.