Making science (part XII): The problem with impact factors

I have been around long enough to remember the time when there were no impact factors. (Don’t know what an impact factor is? Read HERE). We all knew that, say, Nature, was more prestigious (or sexy, hot, trendy, impactful, whatever you want…) than, say, JBC. And that JBC was better journal than many (actually many!) other (ie lower) journals. We did not need any impact factors to realise that. And of course this “intuitive” information was used to evaluate job candidates and assess tenure. A paper in Nature was very important, we all knew that, and did not need any impact factors. The problem now is that impact factors  put a hard number on what earlier was an intuitive, soft process. So, now we know that not only is Nature “better” than JBC, it is actually 10.12 times “better”. And PNAS is 2.23 times “better”. That is what has generated so many problems and distortions. The temptation to use those numbers is just too high, irresistible. For the journals, for the papers in them, and for individual scientists. And the numbers change every year. When applied to individual papers this gets totally crazy. Imagine. The “value” of a given paper can be higher (or lower) this year than, say,  3 years ago when it was published. The same paper, the same data. And let’s not get started with what the impact factor has done to innovaiton and creativity. (For a good view on this, read Sydney Brenner’s interview HERE).

Here is an idea. Why don’t we all get together and sue collectively Thomson Reuters for having commercialised (or Eugene Garfield, for having invented) this monster and caused so much havoc?

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