taliile yellene alston
Rachelle Kun
LINDENBERG: I started the book in 2006, when Craig Arnold and his son Robin and I were living together in Rome. It was a book about our unconventional little family, about love and its many complications. I always intended it to converse as well with a long tradition of poems about love, from Sappho to Frank Stanford. I worked on it slowly alongside other projects for a few years, and it was well underway, about half written, when Craig vanished in April 2009.
Some analogies: The Winter Olympics are like Christmas to me, except better, no offence intended to Jesus Christ, because they only come around once every four years. The Winter Olympics are like the Super Bowl to me, except better, no offence intended to Tom Brady, because the excitement lasts for two entire weeks.
I must begin my Anticipation Index by first noting a grave disappointment: once again there will be no NHL participation in the Olympic hockey tournament. This means that once again, we as a society are being deprived the opportunity to watch Sidney Crosby and Connor McDavid join forces on a power play unit, and considering Sidney is already 34 years old, we might not ever get the chance again. This is personally devastating to me. All I have wanted for many years is to experience my own version of the Gretzky to Lemieux pass from the 1987 Canada Cup. And yet, this universe rebuffs me again and again.
The Office managed to find a way to continue on after Steve Carrell, as Cheers once had to do after Shelly Long, and as Homeland had to after Damien Lewis. Somehow, we must also persevere through our first Olympics without Tessa Virtue and Scott Moir.
The Americans won the inaugural event in 98, then Canada went on to claim four consecutive golds (02, 06, 10, 14) before their streak abruptly ended in 18. I would love to see that pattern repeat itself again with another Canada victory in 22 setting the stage for the next three cycles.
For the first time, Mark will be at his full power during an Olympic competition, in search of the gold medal that will make his career complete. And I will be holding my breath the entire time, crossing my fingers until they bruise.
Suddenly I could see at a glance that I had too much action in the first half of the script and barely any in the second half. It showed me that the love sub-plot started way too late in the movie and I had to do something to start that storyline earlier. I also saw that I had too many characters and condensed several of them. And the cards revealed that my five acts really wanted to collapse into four acts!
Meanwhile, next door, my friend Alex (in photo at right), a writer who writes a lot and teaches writing, is working on an original TV pilot and using an index card outline in VERTICAL COLUMNS, one for each act! He says he likes horizontal flow for movies but vertical flow for a tighter structure like TV.
When you choose to publish with PLOS, your research makes an impact. Make your work accessible to all, without restrictions, and accelerate scientific discovery with options like preprints and published peer review that make your work more Open.
As an impressionable young graduate student, I saw my PhD supervisor regularly check his citations. Citations to papers means that someone used your work or thought it was relevant to mention in the context of their own work. If a paper was never cited, and perhaps therefore also little read, was it worth doing the research in the first place? I still remember the excitement of the first citation I ever received and I still enjoy seeing new citations roll in.
One of the ways in which I use the H-index is when making tenure recommendations. By placing the candidate within the context of the H-indices of their departmental peers, I can judge the scientific output of the candidate within the context of the host institution. This is a useful because it can be difficult to understand what is required at different host institutions from around the world. It would be negligent to only look at H-index and so I use a range of other metrics as well, together with good old fashioned scientific judgement of their contributions from reading their application and papers.
One of those extra metrics I use was also introduced by Hirsch, and is called m (Hirsch, 2005). M measures the slope or rate of increase of the H-index over time and is, in my view, a greatly underappreciated measure. To calculate the m-value, take the researchers H-index and divide by the number of years since their first publication. This measure helps to normalise between those at the early or twilight stages of their career. As Hirsch did for physicists in the field of computational biology, I broadly categorise people according to their m value in the table below. The boundaries correspond exactly to those used by Hirsch.
If we calculate their m-value, then we find that A has a value of 0.5, B has 0.94 and C a value of 1.67. So while each of these researchers has a similar H-index, their likelihood for future growth can be predicted based on past performance. Recently, Daniel Acuna and colleagues presented a sophisticated prediction of future H-index using a number of several features, such as number of publications and the number in top journals (Acuna et al. 2012).
As any serious citation gazer knows, the H-index has numerous potential problems. For example, researcher A who spent time in industry has fewer publications, people with names in non English alphabets or very common names can be difficult to correctly calculate, different fields have widely differing authorship, publication and citation patterns. But even considering all these problems, I believe the H-index is here to stay. My experience is that ranking scientists by H-index and m-value correlates very well with my own personal judgements about the impact of scientists that I know and indeed with the positions that those scientists hold in Universities around the world.
Alex Bateman is currently a computational biologist at the Wellcome Trust Sanger Institute where he has led the Pfam database project. On Novembert 1st, he takes up a new role as Head of Protein Sequence Resources at the EMBL-European Bioinformatics Institute (EMBL-EBI).
The alternative I propose is the H5Y factor. It is the H factor, but calculated only on citations received in the past five years. This equalizes the playing field and my guess is that it is a much better predictor of performance for the next five years than H or m. Who cares what you have published thirty years ago? (unless it is still being cited, of course!)
I agree with Constantin, and would add that the m-index is particularly unfair to those who take early career breaks, since it takes several years before the penalty of having a gap after their first few papers starts to become trivially small.
Funnily enough, I think Google are already using a better measure (which they call H5), but only for their journal rankings, not their author profiles, see e.g.
scholar.google.co.uk/citations?view_op=top_venues
This measure is the H-index for work published in the last five years, rather than just cited in the last five years, and they call this H5.
Most of the H-trajectory plots that I have created for active scientists do show quite a linear trend. I only showed three in my graph above, but researcher A was the only significant deviation that I found. Creating these H-trajectory plots was not as easy as I thought it was going to be. Downloading the full citation data is time consuming given the limits imposed by SCOPUS and ISI. I also found that the underlying data for citations was not nearly as clean as I expected.
I agree that it is important to be able to take account of career breaks so that we do not penalise researchers unfairly. Being able to plot the H-trajectory might help spot these. But as I mentioned in the article these metrics should only be used as part of a wider evaluation of individuals outputs. I tend to agree with the google view on the proliferation of metrics that this could lead to more confusion than it solves. But H5-like measures seem like another reasonable way to normalise out the length of career issue.
I find Google Scholar far better than ISI. It is updated more regularly and gives better representation to publications in non-English journals. I would choose it over others to calculate any sort of index.
I agree with Alex. I had the same experience, whether to recruit post-docs, young group leaders or evaluate tenure (and even in one case head of large institute). After 3, 10, 20 or 30 years of research, the h-index and m numbers are very good to evaluate not only the brilliance at one point, but also the steady success. You do not hire the genious who had only one magic paper and nothing else significant. The likelyhood that the magic happens again is very low.
You have to compare with peers though. Having been an experimental neuroscientist and a computational modeller I know that the citation patterns are quite different. However, when using the H-index to compare people, we are generally in a situation where we compare similar scientists.
All that of course being a way to quickly sort out A, B or C lists, and uncovering potential problems (100 publications and h-index of 10). After that step, you need to evaluate the candidates more attentively, using interviews etc. But interestingly you very rarely read the publications. In the first screen you have too many of them and in the second you do not need them anymore.
I think that is a good suggestion. It is important to take account of career breaks when judging peoples scientific output. Its not perfect to just subtract the break length or some combination of time. Even during a career break your pre-break papers will still be cited and potentially increasing your H-index. But to a first approximation what you suggest makes good sense. It would be interesting to look at the H-trajectories of people who have taken a career break to see how it affects growth of H-index.
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