The h-index attempts to reduce a researcher’s output to a single number: your h-index is the number of papers you’ve published, N, that have been cited at least N times. It seems like a broader measure than pure citation counts but is by no means a perfect measure. It is seen as mostly confirming past successes and it is variable between different subjects. Much has been written about it since it was first devised in 2005, and various attempts have been made to improve it.
A paper in this week’s Nature announces a new variant – the future h-index. This is designed to predict what your h-index will be a few years in the future, taking into account some additional factors. It seems interesting but still flawed.
Appearing in such a high-profile venue as Nature has given this new metric some prominence, and there has been much comment already (e.g. see this piece in The Scientist). On Twitter Noah Fierer commented:
In case you were wondering – secret to high H-index = lots of papers in high profile journals.
Hardly a surprising finding. The Chronicle of Higher Education has some further thoughtful comments on the new tool.
Konrad Kording, one of the authors of the paper in Nature, said that their future h-index has “proved more than twice as accurate as the h-index for predicting the future success of researchers in the life sciences”.
But Jorge Hirsch, the inventor of the original h-index is not impressed. The Chronicle reports
he said the factors added to his h-index appeared to have little meaningful effect. He suggested the additional factors had been devised by “optimizing the coefficients” for a particular set of authors covered by the paper. He said the predictive powers would not hold up for a wider set of test cases.
That echoes my thought. Publication patterns and citation practices vary between fields, so basing a general formula on researchers in one particular field is not realistic. The article mentions factors such as the quality of training and the standing of one’s PhD adviser (and I would add one’s postdoc supervisor and later mentors) but none of these factors are included in the new index as they apparently have only a small effect.
But, hey, everyone knows that these magic numbers are basically just that – a data reduction too far. As Stephen Curry said on Twitter:
scientists invent a new way to screw themselves over
So I think Wired magazine has the best idea:
while neither one’s h-index nor the predictions of this equation are destiny, playing with this formula certainly is fun.
You can try the formula for yourself.