The H-Index is ruling science these days.

Recently an interesting article appeared in EuroPhysics News. I think this paper is of interest to all scientists, and not only to physicists:

Europhysics News Vol. 40, No. 5, 2009, pp. 26-29
DOI: 10.1051/epn/2009704

Bibliometric evaluation of individual researchers: not even right… not even wrong!
Franck Laloë[1] and Remy Mosseri[2]

[1]  Laboratoire Kastler Brossel, ENS, CNRS and UPMC, Paris, France
[2]  Laboratoire de Physique Théorique de la Matière Condensée, UPMC and CNRS, Paris, France

Published online: 17 October 2009

Here is the pdf file. Or download it from the Europhysics News site.

The other day I met a professor from a pretty good department and he said something along the lines of “of course the h-index is not important but it is funny that all the hires we have made over the years had a normalised h-index of 1 or above and when they didn’t, questions were asked”. So the conclusion really is that to be hired you need a normalised h-index greater or equal than 1.

What’s this all about? First the h-index, in case you have been in the bush and haven’t heard about it yet. There’s good explanation on the wiki page on the h-index. Briefly, if you order your publications by the number of citations in decreasing order and index them 1,2,3, etc., when the index becomes equal to the number of citations, you have found your h-index. Thus, an h-index of 10 means that you have 10 papers with 10 citations or more. It filters for outliers such as one paper with a 1000 citations. The normalised h-index (hbar?) is the h-index divided by the number of years that have passed since your first publication. Supposedly (I can’t find where I read this now), an h-index of 20 when you have been in your career for 20 years qualifies you to become a full professor.

Last year, the UK had a giant review of all its university departments to arrive at rankings of departments by subject. This review was called the research assessment exercise (RAE) 2008 and my department (a physics department) didn’t do so well. Therefore, I had an extra good look at the RAE results. In January, we got some more details including a ranking of our papers. Each academic had submitted four papers published between 2001 and 2008, which were graded by a panel from 1* to 4*. The meaning of this ranking is 4* (world-leading), 3* (internationally excellent), 2* (internationally recognised), and 1* (nationally recognised). From my department’s result, I could work out a formula relating the impact factor (IF) of the journals to the quality of the paper as judged in the RAE 2008. The Physics panel chair Sir John Pendry vehemently denied a few weeks ago that his panel used IFs. That may be true but then my formula calculates the perceived quality of a paper as judged by our peers. I thought you might be interested in that judgement.

One writes a scientific article when she thinks she has enough new material in which a sizable fraction of the community is interested. In the time of writing, any article should be written with a lot of enthusiasm, as if it is going to appear on the cover of the most cited journal in the field. But sooner or later, one should decide about the submission destination.

Choosing the journal where you want to publish your article is a very nontrivial task. Frankly speaking, my mind gets occupied with this question, from a very early stage. It may be partly due to my lack of experience or because of my light-weighted publication list.

It may happen that even very experienced scientists cannot publish their article in their firstly-chosen journal. In these cases they may need to try 3 or 4 different journals, and re-format their article a couple of times. This process consumes a lot of work and energy, without adding to the scientific content. Some of this excess work could have been avoided if the first choice was made less ambitiously.

Not only the scientific glossy magazines but also the professional journals are invaded by the colorful graphs that either look like an artificially colored moon landscape, or like a collection of candy sticks or like a flying carpet. I do not like them and in particular the candy sticks I find ugly.

In physics and mathematics progress is made by generalizing and abstracting. The ultimate result is the capturing of one’s finding in a mathematical formula or an - admittedly dull - scientific X-Y graph. As a result physics papers were are full of these terrifying items. I say were, as the X-Y plot is on its way out.

The 3D plots are usually very difficult to interpret quantitatively. They are good to get an overall picture. It gets even worse if the authors - often on purpose - do not show the color scale. Wildly varying colors sometimes only indicate a variation of the magnitude of a variable by less than 10%.

Is it true that articles in high-impact journals involve, in average, more coauthors?

A while ago, I was involved in writing a review article, which finally included around 270 references. Being not very experienced in using BibTeX, I had to manually enter many references in my TeX-file. There I noticed that Nature and Science entries took more time to handle because they usually come with more than 4 coauthors.

Today, I searched a bit on the internet (around 2 hours) and I did not find a solid answer to my question. Instead, I found very interesting articles from Eugen Tarnow about coauthorship in physics and junior physicists’ perception of authorship. In these articles, based on detailed surveys, Tarnow discusses that not all the authorships are awarded decently. As an example, he has found that: “The probability of any third and subsequent coathors being judged as inappropriate is 23% for the APS guideline, [and] 67% for the tighter guideline of the International Committee of Medical Journal Editors“.

Ideal

Scientists that have made observations, or have obtained their results from a calculation or a simulation want to present these findings in a figure. If you are an old-fashioned scientist you use as format a dull plot with a labeled x-axis and a labeled y-axis and a curve mapping points on these axes. If you are a young guy or girl you spicy your paper up by presenting your data in fantastically shining 3D plot (from which it is always quite difficult to extract the quantitative information contained in the plot) . Usually the labels are scaled in such a way that they show cosmetically appealing numbers like 0, 1, 2. If the labels would contain numbers like 0.645 x 10^-3 we scale the axes and report in the caption what the scaling factor is. In such a way anybody that checks the figure gets all information and could - if needed - repeat the experiment or the calculation and check his graph against the published graph.