The skewness of scientific productivity

This paper exploits a unique 2003-2011 large dataset, indexed by Thomson & Reuters, consisting of 17.2 million disambiguated authors classified into 30 broad scientific fields, as well as the 48.2 million articles resulting from a multiplying strategy in which any article co-authored by two or more persons is wholly assigned as many times as necessary to each of them. The dataset is characterized by a large proportion of authors who have their oeuvre in several fields. We measure individual productivity in two ways that are uncorrelated: as the number of articles per person, and as the mean citation per article per person in the 2003-2011 period. We analyze the shape of the two types of individual productivity distributions in each field using size- and scale-independent indicators. For productivity inequality, we use the coefficient of variation. To assess the skewness of productivity distributions we use a robust index of skeweness, as well as the Characteristic Scores and Scales approach. For productivity inequality, we use the coefficient of variation. In each field, we study two samples: the entire population, and what we call “successful authors”, namely, the subset of scientists whose productivity is above their field average. The main result is that, in spite of wide differences in production and citation practices across fields, the shape of field productivity distributions are very similar across fields. The parallelism of the results for the population as a whole and for the subset of successful authors when productivity is measured as mean citation per article per person, reveals the fractal nature of the skewness of scientific productivity in this case. These results are essentially maintained when any article co-authored by two or more persons is fractionally assigned to each of them.Ruiz-Castillo also acknowledges financial help from the Spanish MEC through grant ECO2010-19596

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

Altmetrics as an Answer to the Need for Democratization of Research and Its Evaluation

In the evaluation of research, the same unequal structure present in the production of research is reproduced. Despite a few very productive researchers (in terms of papers and citations received), there are also few researchers who are involved in the research evaluation process (in terms of being editorial board members of journals or reviewers). To produce a high number of papers and receive many citations and to be involved in the evaluation of research papers, you need to be in the minority of giants who have high productivity and more scientific success. As editorial board members and reviewers, we often find the same minority of giants. In this paper, we apply an economic approach to interpret recent trends in research evaluation and derive a new interpretation of Altmetrics as a response to the need for democratization of research and its evaluation. In this context, the majority of pygmies can participate in evaluation with Altmetrics, whose use is more democratic, that is, much wider and open to all

Within- and between-department variability in individual productivity. The case of Economics

There are two types of research units whose performance is usually investigated in one or several scientific fields: individuals (or publications), or larger units such as universities or entire countries. In contrast, the information about the university departments (or research institutes) is not easy to come by. This is important because, in the social sciences, university departments are the governance units where the demand for and the supply of researchers determine an equilibrium allocation of scholars to institutions. This paper uses a unique dataset consisting of all individuals working in 2007 in the top 81 Economics departments in the world according to the Econphd university ranking

Ranking authors using fractional counting of citations : an axiomatic approach

This paper analyzes from an axiomatic point of view a recent proposal for counting citations: the value of a citation given by a paper is inversely proportional to the total number of papers it cites. This way of fractionally counting citations was suggested as a possible way to normalize citation counts between fields of research having different citation cultures. It belongs to the “citing-side” approach to normalization. We focus on the properties characterizing this way of counting citations when it comes to ranking authors. Our analysis is conducted within a formal framework that is more complex but also more realistic than the one usually adopted in most axiomatic analyses of this kind

On the effects of the reunification on German researchers’ publication patterns

After developing independently following World War II, the research systems of East and West Germany reunited at the end of the Cold War, resulting in Westernization of East German Research institutions. Using data from the Web of Science over the 1980-2000 period, this paper analyses the effects of these political changes on the research activity of scholars from East and West Germany before and after the reunification. It shows that these groups differ in terms of levels of production, publication language, collaboration patterns and scientific impact and that, unsurprisingly, the scholarly output of the East became much more similar to that of the West after the reunification. At the level of individual researchers, analysis shows that East German researchers who had direct or indirect ties with the West prior to the 1990s were less affected by the reunification, or were perhaps quicker to adapt to this major change, than their colleagues who were more deeply rooted in the Eastern research system

How many is too many? : on the relationship between research productivity and impact

Over the last few decades, the institutionalisation of quantitative research evaluations has created incentives for scholars to publish as many papers as possible. This paper assesses the effects of such incentives on individual researchers’ scientific impact, by analysing the relationship between their number of articles and their proportionof highly cited papers. In other words, does the share of an author’s top 1% most cited papers increase, remain stable, or decrease as his/her total number of papers increase? Using a large dataset of disambiguated researchers (N = 28,078,476) over the 1980–2013 period, this paper shows that, on average, the higher the number of papers a researcher publishes, the higher the proportion of these papers are amongst the most cited. This relationship is stronger for older cohorts of researchers, while decreasing returns to scale are observed for recent cohorts. On the whole, these results suggest that for established researchers, the strategy of publishing as many papers as possible did not yield lower shares of highly cited publications, but such a pattern is not always observed for younger scholars

Scientific mobility indicators in practice : international mobility profiles at the country level

This paper presents and describes the methodological opportunities offered by bibliometric data to produce indicators of scientific mobility. Large bibliographic datasets of disambiguated authors and their affiliations allow for the possibility of tracking the affiliation changes of scientists. Using the Web of Science as data source, we analyze the distribution of types of mobile scientists for a selection of countries. We explore the possibility of creating profiles of international mobility at the country level, and discuss potential interpretations and caveats. Five countries—Canada, The Netherlands, South Africa, Spain, and the United States—are used as examples. These profiles enable us to characterize these countries in terms of their strongest links with other countries. This type of analysis reveals circulation among and between countries with strong policy implications.Este trabajo presenta y describe las oportunidades metodológicas que ofrecen los datos bibliográficos para producir indicadores de movilidad científica. El uso de grandes conjuntos de datos bibliográficos con autores y afiliaciones desambiguadas, abren la posibilidad de rastrear cambios de afiliación de investigadores. Empleando la Web of Science como base de datos, desarrollamos distintas perspectivas para mostrar la movilidad observable de una selección de países. Exploramos la posibilidad de crear perfiles de movilidad internacional a nivel de países y discutimos cómo interpretar estos indicadores así como sus potenciales limitaciones. Para ello, estudiamos los casos de Canadá, Países Bajos, Sudáfrica, España y Estados Unidos. Sus perfiles no solo nos permiten identificar a grupos de investigadores que muestran distintos tipos de movilidad, pero también nos permiten caracterizar los países según aquellos otros con los que tienen mayores vínculos. Este tipo de análisis permiten realizar comparaciones entre países de origen y destino de cada uno de los países analizados, especialmente relevantes en el contexto de política cientifica

Are migrants more productive than stayers? Some evidence for a set of highly productive academic economists

This paper compares the average productivity of migrants (who work in a country different from their country of origin) and stayers (whose entire academic career takes place in their country of origin) in a set of 2,530 highly productive economists that work in 2007 in a selection of the top 81 Economics departments worldwide. The main findings are the following two. Firstly, productivity comparisons between migrants and stayers depend on the cohort and the type of department where individuals work in 2007. For example, in the top U.S. departments, foreigners are more productive than stayers only among older individuals; in the bottom U.S. departments, foreigners are more productive than stayers for both cohorts, while in the other countries with at least one department in the sample the productivity of foreigners and stayers is indistinguishable for both cohorts. Secondly, when we restrict our attention to an elite consisting of economists with above average productivity, all productivity differences between migrants and stayers in the U.S. vanish. These results are very robust. However, our ability to interpret these correlations is severely limited by the absence of information on the decision to migrate.Albarrán acknowledges financial support from the Spanish MEC through grants ECO2009-11165 and ECO2011-29751, and Carrasco and Ruiz-Castillo through grants No. ECO2012-31358 and ECO2014-55953-P, respectively, as well as grant MDM 2014-0431 to their Departamento de Economía

The productivity of top researchers: A semi-nonparametric approach

Research productivity distributions exhibit heavy tails because it is common for a few researchers to accumulate the majority of the top publications and their corresponding citations. Measurements of this productivity are very sensitive to the field being analyzed and the distribution used. In particular, distributions such as the lognormal distribution seem to systematically underestimate the productivity of the top researchers. In this article, we propose the use of a (log)semi-nonparametric distribution (log-SNP) that nests the lognormal and captures the heavy tail of the productivity distribution through the introduction of new parameters linked to high-order moments. To compare the results, we use research performance data on 140,971 researchers who have produced 253,634 publications in 18 fields of knowledge (O’Boyle and Aguinis, 2012) and show how the log-SNP distribution provides more accurate measures of the performance of the top researchers in their respective fields of knowledge