Abstract
Journals are routinely evaluated by journal impact factors. However, more controversially, these same impact factors are often used to evaluate authors and groups as well. A more meaningful approach will be to use actual citation rates. Since in each journal there is a very highly skewed distribution of articles according to citation rates, there is little correlation between journal impact factor and actual citation rate of articles from individual scientists or research groups. Simply stated, journal impact factor does not successfully predict high citations in future. In this paper, we propose the use of Peirce’s measure of predictive success (Peirce in Science 4(93):453–454, 1884) to see if the use of journal impact factors to predict high citation rates is acceptable or not. It is seen that this measure is independent of Pearson’s correlation (Seglen 1997) and gives a more quantitative refinement of the Type I and Type II classification of Smith (Financ Manag 133–149, 2004). The measures are used to examine the portfolios of some active scientists. It is clear that the journal impact factor is not effective in predicting future citations of successful authors.
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References
Calza, L., & Garbisa, S. (1995). Italian professorships. Nature, 374, 492.
Garfield, E. (1955). Citation indexes to science: A new dimension in documentation through association of ideas. Science, 122(3159), 108–111.
Garfield, E. (1999). Journal impact factor: A brief review. Canadian Medical Association Journal, 161(8), 979–980.
Garfield, E. (2005). The agony and the ecstasy: the history and meaning of the journal impact factor. International Congress on Peer Review and Biomedical Publication. http://garfield.library.upenn.edu/papers/jifchicago2005.pdf.
Maffulli, N. (1995). More on citation analysis. Nature, 378, 760.
Peirce, C. S. (1884). The numerical measure of the success of predictions. Science, 4(93), 453–454.
Seglen, P. O. (1992). The skewness of science. Journal of the American Society for Information Science, 43, 628–638.
Seglen, P. O. (1994). Causal relationship between article citedness and journal impact. Journal of the American Society for Information Science, 45, 1–11.
Seglen, P. O. (1997). Why the impact factor of journals should not be used for evaluating research. British Medical Journal, 314, 498–502.
Smith, S. D. (2004). Is an article in a top journal a top article? Financial Management, 133–149.
Taubes, G. (1993). Measure for measure in science. Science, 260, 884–886.
Vinkler, P. (1986). Evaluation of some methods for the relative assessment of scientific publications. Scientometrics, 10, 157–177.
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Prathap, G., Mini, S. & Nishy, P. Does high impact factor successfully predict future citations? An analysis using Peirce’s measure. Scientometrics 108, 1043–1047 (2016). https://doi.org/10.1007/s11192-016-2034-y
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DOI: https://doi.org/10.1007/s11192-016-2034-y