An investigation on the skewness patterns and fractal nature of research productivity distributions at field and discipline level

The paper provides an empirical examination of how research productivity distributions differ across scientific fields and disciplines. Productivity is measured using the FSS indicator, which embeds both quantity and impact of output. The population studied consists of over 31,000 scientists in 180 fields (10 aggregate disciplines) of a national research system. The Characteristic Scores and Scale technique is used to investigate the distribution patterns for the different fields and disciplines. Research productivity distributions are found to be asymmetrical at the field level, although the degree of skewness varies substantially among the fields within the aggregate disciplines. We also examine whether the field productivity distributions show a fractal nature, which reveals an exception more than a rule. Differently, for the disciplines, the partitions of the distributions show skewed patterns that are highly similar

How long do top scientists maintain their stardom? An analysis by region, gender and discipline: evidence from Italy

We investigate the question of how long top scientists retain their stardom. We observe the research performance of all Italian professors in the sciences over three consecutive four-year periods, between 2001 and 2012. The top scientists of the first period are identified on the basis of research productivity, and their performance is then tracked through time. The analyses demonstrate that more than a third of the nation's top scientists maintain this status over the three consecutive periods, with higher shares occurring in the life sciences and lower ones in engineering. Compared to males, females are less likely to maintain top status. There are also regional differences, among which top status is less likely to survive in southern Italy than in the north. Finally we investigate the longevity of unproductive professors, and then check whether the career progress of the top and unproductive scientists is aligned with their respective performances. The results appear to have implications for national policies on academic recruitment and advancement

A review of the literature on citation impact indicators

Citation impact indicators nowadays play an important role in research evaluation, and consequently these indicators have received a lot of attention in the bibliometric and scientometric literature. This paper provides an in-depth review of the literature on citation impact indicators. First, an overview is given of the literature on bibliographic databases that can be used to calculate citation impact indicators (Web of Science, Scopus, and Google Scholar). Next, selected topics in the literature on citation impact indicators are reviewed in detail. The first topic is the selection of publications and citations to be included in the calculation of citation impact indicators. The second topic is the normalization of citation impact indicators, in particular normalization for field differences. Counting methods for dealing with co-authored publications are the third topic, and citation impact indicators for journals are the last topic. The paper concludes by offering some recommendations for future research

The measurement of low- and high-impact in citation distributions: technical results

This paper introduces a novel methodology for comparing the citation distributions of research units working in the same homogeneous field. Given a critical citation level (CCL), we suggest using two real valued indicators to describe the shape of any distribution: a highimpact and a low-impact measure defined over the set of articles with citations above or below the CCL. The key to this methodology is the identification of a citation distribution with an income distribution. Once this step is taken, it is easy to realize that the measurement of lowimpact coincides with the measurement of economic poverty. In turn, it is equally natural to identify the measurement of high-impact with the measurement of a certain notion of economic affluence. On the other hand, it is seen that the ranking of citation distributions according to a family of low-impact measures, originally suggested by Foster et al. (1984) for the measurement of economic poverty, is essentially characterized by a number of desirable axioms. Appropriately redefined, these same axioms lead to the selection of an equally convenient class of decomposable high-impact measures. These two families are shown to satisfy other interesting properties that make them potentially useful in empirical applications, including the comparison of research units working in different fields.