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Schwendtke, A.: Wissenschaftssystematik und Scientometrologie (1979)
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- Source
- Klassifikation und Erkenntnis I. Proc. der Plenarvorträge und der Sektion 1 "Klassifikation und Wissensgewinnung" der 3. Fachtagung der Gesellschaft für Klassifikation, Königstein/Ts., 5.-6.4.1979
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Solla Price, D. de: Little science, big science : Von der Studierstube zur Großforschung (1974)
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- Abstract
- Big Science ist so neu, daß sich viele von uns ihrer Anfänge erinnern. Big Science ist so groß, daß sich viele von uns vor den Ausmaßen des Monsters, das wir geschaffen haben, zu fürchten beginnen. Big Science ist so anders als alles Frühere, daß eine Betrachtung der 'Little Science', die einst unsere Lebensart war, nur ein wehmütiger Rückblick ist
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Garfield, E.: Essays of an information scientist (1977-)
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- Footnote
- U.a. Wiedergabe der Beiträge von E. Garfield in der Rubrik 'Current comments' in den 'Current contents'
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Murphy, L.J.: Lotka's law in the humanities? (1973)
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Mulkay, M.J.; Gilbert, G.N.; Woolgar, S.: Problem areas and research networks in science (1975)
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Rao, I.K.: ¬The distribution of scientific productivity and social change (1978)
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- Abstract
- Results in the literature concerning the probability that an author publishes r articles in time t are reexamined, and it is found that a negative binomial distribution bits scientific productivity data (by the chi-squared goodness-of-fit-test) better than many other distribution such as geometric, logarithmic, zeta, cumulative advantage, etc. It is shown analytically that the nagative binomial distribution describes a pattern of scientific productivity under the 'success-breeds-success' condition in a wide variety of social circumstances
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Bookstein, A.: ¬The bibliometric distributions (1976)
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- Abstract
- One of the most surprising findings in the information sciences is the recurrence of a small number of frequency distributions. In this paper, these distributions are described, and a point of view is adopted that allows us to understand them a being different versions of a single distribution. The empirical distributions are shown to be special cases of a single theoretic distribution. It is found that when random fluctuations are introduced, the distributions are not strongly influenced
