Comments on: By any measure I’m average at most

By: Academic Career Links

Academic Career Links — Thu, 26 Mar 2009 19:46:35 +0000

However, some people argue that one can do great science without being genius: see e.g. the famous talk You and Your Research by Richard Hamming.

By: Yaroslav Nikolaev

Yaroslav Nikolaev — Mon, 11 Aug 2008 21:31:34 +0000

“research area” was also meant to be a part of the example..Its just the only semantic parameter of the research process (== keywords) which is reasonably defined within existing scientific literature. Having more semantics one would be able to make more elaborate requests than simply finding biggest shots in a particular area..but you’re right, have to see some sort of implementation first to be able to extrapolate on this topic.

By: Pawel Szczesny

Pawel Szczesny — Mon, 11 Aug 2008 08:07:38 +0000

Good question Yaroslav and I have no definitive answer. While it’s true that such scoring would allow for effective searching for big shots’ papers relevant to a particular query, finding them looks possible without it (see JANE, E-lise, Anne O’Tate). My feeling is that we could do better by defining similarity score between authors instead of defining research areas, but until somebody does the implementation of either approach I have no way to prove it’s better.

By: Yaroslav Nikolaev

Yaroslav Nikolaev — Sun, 10 Aug 2008 20:49:44 +0000

thanks for the enlightenment Pawel, its a great point!! Definitely no good using same number (IF) across the whole science domain, without normalization on the field, funding, research time frames, etc. But don't you think a score would become meaningful when applied to a narrow area of research? For example, a search filter in a semantically rich environment that gives a list of experts/groups from a defined research field ranked by some (user-defined) combination of the parameters from the "Shirley's equation".

By: Danny

Danny — Sat, 09 Aug 2008 05:31:48 +0000

Impact factor Perfect!

By: Pawel Szczesny

Pawel Szczesny — Sat, 09 Aug 2008 05:30:17 +0000

To find relevant science we need two decent services: search engine and recommendation engine. Algorithms used in both will significantly differ from each other and from an algorithm used to evaluate scientist’s performance (just compare Google, F1000 and IF). I’m not against attaching all meta information to the paper, but I would argue that whatever aim is it should be clearly defined – solving two issues with a single approach is likely to fail.

By: Pedro Beltrao

Pedro Beltrao — Sat, 09 Aug 2008 03:15:31 +0000

These additional measures should also help to filter scientific content not just to evaluate a scientist. Today we evaluate something first by where it was published and only then by reading it. We already sort and discard a lot of things just based on the evaluation of the editors. I am also arguing that having all this information attached to a publication will helps find more relevant science for us.

By: Paulo

Paulo — Fri, 08 Aug 2008 14:09:32 +0000

Excellent points Pawel, especially when you mentioned the lack of discussion of where grant money is being spent. Every time you look grants are getting more concentrated in a smaller number of places/people.

I stopped looking at IF some time ago. It doesn’t matter if an article was published in a 0.5 IF journal. If interests me and it is a sound well written publication it is good enough for me, an average guy like you.