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

Connections matter: a proxy measure for evaluating network membership with an application to the Seventh Research Framework Programme

Although the topic of networks has received significant attention from the scientific literature, it remains to be seen whether it is possible to quantify the degree to which an organisation benefits from being part of a network. Starting from the concept of network value and that of Metcalfe’s Law, this paper introduces and defines the collective network effect (CNE). CNE is based on the concept that a network member is not only affected by its friends but also by the friends of its friends. By taking into account network connection patterns, CNE provides a proxy for quantifying the benefit of network membership. We computed the CNE for the nodes of a large network built using the whole set of common projects among the participants of the 7th Framework Programme for Research and Technological Development of the European Commission. The obtained results show that nodes with a higher CNE have access to substantially more conspicuous fundings than nodes with a lower CNE. In general, such a measure could supplement other centrality measures and be useful for organisations and companies aiming to evaluate both their current situation and the potential partners they should link with in order to extract the highest benefits from network membership.

High research productivity in vertically undifferentiated higher education systems: Who are the top performers?

The growing scholarly interest in research top performers comes from the growing policy interest in research top performance itself. A question emerges: what makes someone a top performer? In this paper, the upper 10% of Polish academics in terms of research productivity are studied, and predictors of entering this class are sought. In the science system (and Poland follows global patterns), a small number of scholars produce most of the works and attract huge numbers of citations. Performance determines rewards, and small differences in talent translate into a disproportionate level of success, leading to inequalities in resources, research outcomes, and rewards. Top performers are studied here through a bivariate analysis of their working time distribution and their academic role orientation, as well as through a model approach. Odds ratio estimates with logistic regression of being highly productive Polish academics are presented. Consistently across major clusters of academic disciplines, the tiny minority of 10% of academics produces about half (44.7%) of all Polish publications (48.0% of publications in English and 57.2% of internationally co-authored publications). The mean research productivity of top performers across major clusters is on average 7.3 times higher than that of the other academics, and in terms of internationally co-authored publications, 12.07 times higher. High inequality was observed: the average research productivity distribution is highly skewed with a long tail on the right not only for all Polish academics but also for top performers. The class of top performers is as internally stratified as that of their lower-performing colleagues. Separate regression models for all academics, science, technology, engineering and mathematics academics, and social sciences and humanities academics are built based on a large national sample (2525 usable observations), and implications are discussed.