Abstract
Skewed citation distribution is a major limitation of the Journal Impact Factor (JIF) representing an outlier-sensitive mean citation value per journal The present study focuses primarily on this phenomenon in the medical literature by investigating a total of n = 982 journals from two medical categories of the Journal Citation Report (JCR). In addition, the three highest-ranking journals from each JCR category were included in order to extend the analyses to non-medical journals. For the journals in these cohorts, the citation data (2018) of articles published in 2016 and 2017 classified as citable items (CI) were analysed using various descriptive approaches including e.g. the skewness, the Gini coefficient, and, the percentage of CI contributing 50% or 90% of the journal’s citations. All of these measures clearly indicated an unequal, skewed distribution with highly-cited articles as outliers. The %CI contributing 50% or 90% of the journal’s citations was in agreement with previously published studies with median values of 13–18% CI or 44–60% CI generating 50 or 90% of the journal’s citations, respectively. Replacing the mean citation values (corresponding to the JIF) with the median to represent the central tendency of the citation distributions resulted in markedly lower numerical values ranging from − 30 to − 50%. Up to 39% of journals showed a median citation number of zero in one medical journal category. For the two medical cohorts, median-based journal ranking was similar to mean-based ranking although the number of possible rank positions was reduced to 13. Correlation of mean citations with the measures of citation inequality indicated that the unequal distribution of citations per journal is more prominent and, thus, relevant for journals with lower citation rates. By using various indicators in parallel and the hitherto probably largest journal sample, the present study provides comprehensive up-to-date results on the prevalence, extent and consequences of citation inequality across medical and all-category journals listed in the JCR.
Highlights
The Journal impact factor (JIF) has been introduced by Garfield (1955) partly based on previous work by Gross and Gross (1927) and initially intended to assist librarians for deciding which journals to purchase for their institution (Garfield 2006)
The current study aimed to provide a comprehensive up-to-date analysis of the citation distribution characteristics based on three independent cohorts of journals listed in the recent Journal Citation Report (JCR 2018): journals of two complete medical categories, i.e. ‘Medicine, Research & Experimental’ and ‘Medicine, General & Internal’ and the three best-ranking journals in each JCR category
For (vii), the Gini coefficient as a measure of inequality (De Maio 2007; Gini 2005) was calculated based on the double cumulative percentages (% citations versus %citable items (CI)): for each journal’s Lorenz curve, the area (Aue) was calculated using the OriginPro INTEGRATE function
Summary
The Journal impact factor (JIF) has been introduced by Garfield (1955) partly based on previous work by Gross and Gross (1927) and initially intended to assist librarians for deciding which journals to purchase for their institution (Garfield 2006). Seglen (1998), Larivière et al 2016, Larivière and Sugimoto 2019; Casadevall and Fang 2014; Glänzel and Moed 2002)], the lack of correlation between JIF and article citedness is primarily based on the (highly) asymmetric distribution of citations to a journal’s published articles. This means that (1) the citations received by a journal are not distributed among the papers this journal has published, and that (2) the majority of papers in a given journal are cited infrequently compared to a few highly-cited ‘outliers’. The median value of citations to a journal was suggested to be more appropriate to express the journal’s citedness [e.g. Editor(s) (2011), Opthof (2019), Pulverer (2013, 2015), Weale et al (2004)]
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