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Abstract  

Aging is one of the properties of scientific and technical literature. The knowledge of the laws of aging is very important in the science of science, information science and library science. Methodological errors in studying the aging process cause wrong results. By means of non-traditional processing of well-known empiric data the author refutes such generally accepted ideas as the idea of very rapid aging of literature, the idea of more rapid aging of publications on rapidly developing fields of knowledge, the idea of the maximum of book use being only in a few years after its publication, and some other ideas.

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Abstract  

Relationships between age and scholarly impact were assessed by determining the number of times single-author articles (N=227) published inPsychological Review between 1965 and 1980 were cited in the fifth year following publication. There were substantial individual differences in citation rates, but this measure of scholarly impact did not correlate with either the chronological age of authors or their professional age (years since PhD award). Although the majority of articles inPsychological Review were published by authors under the age of 40, such a bias is to be expected in terms of the age distribution of American psychologists. When allowance was made for the number of authors in different age ranges, older authors were no less likely than younger authors to have generated a high-impact article (an article cited 10 or more times in the fifth year after publication). The data offer no support to claims that publications by young scientists have greater impact.

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Abstract  

This paper analyzes the relationship between age and productivity for Nobel prize winners in science during the period 1901–1992. The relationship found is field dependent as well as dependent upon the definition used to measure the age at which the ward-winning work was done. The results suggest that although it does not require extraordinary youth to do prizewinning work, the odds decrease markedly in mid-life and fall off precipitously after age 50, particularly in chemistry and physics. The discussion underscores the problem of drawing conclusions about the age structure of research by examining medians instead of the entire distribution.

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Abstract  

A linear increase law of optimum age of scientific creativity is proposed. The author has analysed the optimum age of major scientific discoveries (or inventions) by the least square method and an increase ratio has been obtained. The optimum age and the age of great fame in next half century are forcast also.

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Abstract  

In this paper we show that it is theoretically impossible to draw empirically founded conclusions about the relation between age and productivity. Only the relation between age and productivityincrease can be verified empirically. With this limitation in mind, a subsequent analysis of productivity data of Dutch physicists, chemists en economists, indicates that thegrowth rate of productivity is higher at ages under 35 than at ages over 35.

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Abstract  

This paper proposes to take the age at which a scientist achieved his first success as his famous-becoming age; uses a statistical method to obtaine the optimum age of scientists for making scientific discoveries; uses the same to find the experiential formula that explains the relationship between the number of scientific achievement and the number of scientists and their ages. Employing this formula, it expounds to some extent the Yuasa Phenomenon. For conclusion it analyzes the scientific value of experiential formula and the reliability of its scope of prediction.

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Scientometrics
Authors:
Liming Liang
,
Hildrun Kretschmer
,
Yongzheng Guo
, and
Donald deB. Beaver

Abstract  

This paper is a scientometric study of the age structure of scientific collaboration in Chinese computer science. Analysis reveals some special age structures in scientific collaboration in Chinese computer science. Most collaborations are composed of scientists younger than thirty-six (Younger) or older than fifty (Elder). For two-dimensional collaboration formed by first and second authors, Younger-Elder and Younger-Younger are the predominant age structures. For three-dimensional collaboration formed by first, second and third authors, Younger-Younger-Elder and Younger-Younger-Younger are the most important age structures. Collaboration between two authors older than 38 amounts to only 6.4 percent of all two-person collaborations. Collaboration between two middle-aged scientists is seldom seen. Why do such types of age structure in Chinese computer science exist? We suggest a tentative explanation based on analyses of the age composition of all authors, the age distributions of the authors in different ranks, and the name-ordering of authors in articles written by professors and their students.

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Abstract  

Varied empirical studies show that the average output (measured in various ways) of a scientific or technical research group is directly proportional to its size (also measured in various ways), when the size and output are measured independently. Hence groups of different sizes have the same average output per unit of size. There is no reliable evidence for the existence of a size or a range of sizes for a research group that maximizes output per unit of size. Present theoretical explanations for the proportionality between size and output are largely inadequate or untested. Similarly, among reported results on group age and output, the only consistency so far is that age, measured as years since the founding or first functioning of the group, is uncorrelated with output per capita. Again, there is no evidence for the existence of an age or a range of ages for a research group that is optimal.

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Abstract  

This paper is the continued study on age structure of scientific collaboration in Chinese computer science. Based on an extended database a new method is used to analyze the nature and preference of collaboration. Observed values of two- three- and four-dimensional collaboration were compared respectively with their expected values. Investigation covered co-authors" combination patterns, name permutations in their papers, especially the age of the first author.

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Abstract  

Certain similarities between the types of data reported in retrospective citation analyses and lifetime/survival/reliability models are noted. Graphical techniques much used in reliability analyses are exploited to throw further light on observed citation age distributions and these are then compared and contrasted with previously reported studies. These simple techniques allow systematic departures of empirical data from assumed theoretical models to be highlighted and the models to be compared.

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