Differences in citation impact across countries

Using a large dataset, indexed by Thomson Reuters, consisting of 4.4 million articles published in 1998-2003 with a five-year citation window for each year, this paper studies country citation distributions in a partition of the world into 36 countries and two geographical areas in the all-sciences case and eight broad scientific fields. The key findings are the following two. Firstly, the shape of country citation distributions is highly skewed and very similar to each other across all fields. Secondly, differences in country citation distributions appear to have a strong scale factor component. The implication is that, in spite of the skewness of citation distributions, international comparisons of citation impact in terms of country mean citations capture well such scale factors. The empirical scenario described in the paper helps understanding why, in each field and the all-sciences case, the country rankings according to (i) mean citations and (ii) the percentage of articles in each country belonging to the set formed by the 10% of the more highly cited papers are so similar to each other.Albarrán acknowledges additional financial support from the Spanish MEC through grants ECO2009-11165 and ECO2011-29751, and Ruiz-Castillo through grant SEJ2007-67436

Differences in citation impact across countries

Using a large data set, indexed by Thomson Reuters, consisting of 4.4 million articles published in 1998–2003 with a 5-year citation window for each year, this article studies country citation distributions for a partitioning of the world into 36 countries and two geographical areas in eight broad scientific fields and the all-sciences case. The two key findings are the following. First, country citation distributions are highly skewed and very similar to each other in all fields. Second, to a large extent, differences in country citation distributions can be accounted for by scale factors. The Empirical situation described in the article helps to understand why international comparisons of citation impact according to (a) mean citations and (b) the percentage of articles in each country belonging to the top 10% of the most cited articles are so similar to each other.The authors acknowledge financial support by Santander Universities Global Division of Banco Santander. Albarrán acknowledges additional financial support from the Spanish MEC through grants ECO2009–11165 and ECO2011–29751, and Ruiz-Castillo through grant ECO2010–19596

Within and across department variability in individual productivity : the case of economics

University departments (or research institutes) are the governance units in any scientific field where the demand for and the supply of researchers interact. As a first step towards a formal model of this process, this paper investigates the characteristics of productivity distributions of a population of 2,530 individuals with at least one publication who were working in 81 world top Economics departments in 2007. Individual productivity is measured in two ways: as the number of publications until 2007, and as a quality index that weights differently the articles published in four journal equivalent classes. The academic age of individuals, measured as the number of years since obtaining the PhD until 2007, is used to measure productivity per year. Independently of the two productivity measures, and both before and after age normalization, the main findings of the paper are the following five. Firstly, individuals within each department have very different productivities. Secondly, there is not a single pattern of productivity inequality and skewness at the department level. On the contrary, productivity distributions are very different across departments. Thirdly, the effect on overall productivity inequality of differences in productivity distributions across departments is greater than the analogous effect in other contexts. Fourthly, to a large extent, this effect on overall productivity inequality is accounted for by scale factors well captured by departments’ mean productivities. Fifthly, this high degree of departmental heterogeneity is found to be compatible with greater homogeneity across the members of a partition of the sample into seven countries and a residual category.Ruiz-Castillo acknowledges financial support from the Spanish MEC through grant SEJ2007-6743

The Accuracy of Confidence Intervals for Field Normalised Indicators

This is an accepted manuscript of an article published by Elsevier in Journal of Informetrics on 07/04/2017, available online: https://doi.org/10.1016/j.joi.2017.03.004 The accepted version of the publication may differ from the final published version.When comparing the average citation impact of research groups, universities and countries, field normalisation reduces the influence of discipline and time. Confidence intervals for these indicators can help with attempts to infer whether differences between sets of publications are due to chance factors. Although both bootstrapping and formulae have been proposed for these, their accuracy is unknown. In response, this article uses simulated data to systematically compare the accuracy of confidence limits in the simplest possible case, a single field and year. The results suggest that the MNLCS (Mean Normalised Log-transformed Citation Score) confidence interval formula is conservative for large groups but almost always safe, whereas bootstrap MNLCS confidence intervals tend to be accurate but can be unsafe for smaller world or group sample sizes. In contrast, bootstrap MNCS (Mean Normalised Citation Score) confidence intervals can be very unsafe, although their accuracy increases with sample sizes

National Scientific Performance Evolution Patterns: Retrenchment, Successful Expansion, or Overextension

This is an accepted manuscript of an article published by Taylor and Francis in Journal of the Association for Information Science and Technology on 17/11/2017, available online: https://doi.org/10.1002/asi.23969 The accepted version of the publication may differ from the final published version.National governments would like to preside over an expanding and increasingly high impact science system but are these two goals largely independent or closely linked? This article investigates the relationship between changes in the share of the world’s scientific output and changes in relative citation impact for 2.6 million articles from 26 fields in the 25 countries with the most Scopus-indexed journal articles from 1996 to 2015. There is a negative correlation between expansion and relative citation impact but their relationship varies. China, Spain, Australia, and Poland were successful overall across the 26 fields, expanding both their share of the world’s output and its relative citation impact, whereas Japan, France, Sweden and Israel had decreased shares and relative citation impact. In contrast, the USA, UK, Germany, Italy, Russia, Netherlands, Switzerland, Finland, and Denmark all enjoyed increased relative citation impact despite a declining share of publications. Finally, India, South Korea, Brazil, Taiwan, and Turkey all experienced sustained expansion but a recent fall in relative citation impact. These results may partly reflect changes in the coverage of Scopus and the selection of fields

Research assessment by percentile-based double rank analysis

In the double rank analysis of research publications, the local rank position of a country or institution publication is expressed as a function of the world rank position. Excluding some highly or lowly cited publications, the double rank plot fits well with a power law, which can be explained because citations for local and world publications follow lognormal distributions. We report here that the distribution of the number of country or institution publications in world percentiles is a double rank distribution that can be fitted to a power law. Only the data points in high percentiles deviate from it when the local and world $\mu$ parameters of the lognormal distributions are very different. The likelihood of publishing very highly cited papers can be calculated from the power law that can be fitted either to the upper tail of the citation distribution or to the percentile-based double rank distribution. The great advantage of the latter method is that it has universal application, because it is based on all publications and not just on highly cited publications. Furthermore, this method extends the application of the well-established percentile approach to very low percentiles where breakthroughs are reported but paper counts cannot be performed.Comment: A pdf file containing text, 9 figures and 4 tables. Accepted in Journal of Informetric

Individual and Field Citation Distributions in 29 Broad Scientific Fields

Using a large unique dataset consisting of 35.1 million authors and 105.3 million articles published in the period 2000-2016, which are classified into 29 broad scientific fields, we search for regularities at the individual level for very productive authors with citation distributions of a certain size, and for the existence of a macro-micro relationship between the characteristics of a scientific field citation distribution and the characteristics of the individual citation distributions of the authors belonging to the field. Our main results are the following three. Firstly, although the skewness of individual citation distributions varies greatly within each field, their average skewness is of a similar order of magnitude in all fields. Secondly, as in the previous literature, field citation distributions are highly skewed and the degree of skewness is very similar across fields. Thirdly, the skewness of field citation distributions is essentially explained in terms of the average skewness of individual authors, as well as individuals’ differences in mean citation rates and the number of publications per author. These results have important conceptual and practical consequences: to understand the skewness of field citation distributions at any aggregate level we must simply explain the skewness of the individual citation distributions of their very productive authors.This is the second version of a paper with the same title published in this series in January 2018. J. Ruiz-Castillo acknowledges financial support from the Spanish MEC through grants ECO2014-55953-P and MDM 2014-0431, as well as grant MadEco-CM (S2015/HUM-3444) from the Comunidad Autónoma de Madrid. Research assistantship by Patricia Llopis, as well as conversations with Ricardo Mora, and especially Vincent Traag, are gratefully acknowledged. All remaining shortcomings are the authors’ sole responsibility