[Insight-developers] Nature Article: Why Journal Impact Factors are Irrelevant

[Luis Ibanez]

http://www.nature.com/neuro/journal/v6/n8/full/nn0803-783.html

http://www.nature.com/neuro/journal/v6/n8/fig_tab/nn0803-783_F1.html


<quote>

The most obvious feature of these distributions is that they are highly
skewed (Fig. 1<http://www.nature.com/neuro/journal/v6/n8/full/nn0803-783.html#f1>);
in every case, the medians are lower than the means, reinforcing the point
that a journal's IF (an arithmetic mean) is almost useless as a predictor
of the likely citations to any particular paper in that
journal2<http://www.nature.com/neuro/journal/v6/n8/full/nn0803-783.html#B2>
.

...

What is most distinctive about the higher-impact journals is their long
tails, corresponding to a relatively small number of papers that are
exceptionally highly cited, and which therefore contribute
disproportionately to the IF and, presumably, to the overall prestige of
those journals. At the other end of the distribution, the lower-impact
journals tend to publish more papers with few citations.

...

Properly interpreted, citation data can be a valuable tool for evaluating
journals, papers, authors and perhaps even editors. But it is a blunt
instrument at best, and when complex distributions are reduced to simple
averages, then much of the usefulness is lost. Journal impact factors
cannot be used to quantify the importance of individual papers or the
credit due to their authors, and one of the minor mysteries of our time is
why so many scientifically sophisticated people give so much credence to a
procedure that is so obviously flawed.

</quote>
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