290
Russell C. Coile
Table 1 Bibliometric Data On Scientifi c Productivity (data sources are
shown in table 5)
Field
Authors
Papers
Years of
Survey
Percent
One Paper
Papers per
Author/Yr.
Chemistry 6,891
22,939
10
58
0.33
Mathematics 278
1,124
25
48
0.16
Fluidics 401
529
9
69
0.15
Genetics 826
3,662
33
51
0.13
Econometrics 721
1,759
20
60
0.12
Operations
Research
787
1,167
15
67
0.10
Computer
Science
420
383
10
83
0.09
Biology
130
264
28
59
0.07
A related problem in information science is the determination of the
scatter of papers in a specialized fi eld over a number of journals. Which
journals (like authors) are the more productive?
Is it possible to fi nd frequency distributions which will provide a
reasonable fi t to various collections of empirical bibliometric data? Will
these frequency distributions be versatile enough to be applicable to
different scientifi c disciplines?
The approach here has been to examine some of the theoretical
models which have been proposed during the past fi fty years, test their
validity against a variety of data from different disciplines and attempt to
fi nd relationships, if any, among these models.
Chapter I will be a brief historical survey of research conducted during
the past fi fty years on this question of frequency distributions of scientifi c
productivity. Details of the various historical studies will be found in
Appendices.
Chapter II will examine the mathematical relationships, if any, among
these different theoretical approaches.
Summary :
Chemistry 6,891 22,939 10 58 0.33 Mathematics 278 1,124 25 48 0.16 Fluidics 401 529 9 69 0.15 Genetics 826 3,662 33 51 0.13 Econometrics 721 1,759 20 60 0.12 Operations Research 787 1,167 15 67 0.10 Computer Science 420 383 10 83 0.09 Biology 130 264 28 59 0.07 A related problem in information science is the determination of the scatter of papers in a specialized fi eld over a number of journals.
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