Showing posts with label h-index. Show all posts
Showing posts with label h-index. Show all posts

Wednesday, April 12, 2017

The most "famous" ecologists (and some time wasting links) (Updated)

(Update: This has gotten lots more attention than I expected. Since first posted, the top 10 list has been updated 2 times based on commenters suggestions. You can also see everyone we looked up here. Probably I won't update this again, because there is a little time wasting, and there is a lot of time wasting :) )

At some point my officemates Matthias and Pierre and I started playing the 'who is the most famous ecologist' game (instead of, say, doing useful work), particular looking for ecologists with an h-index greater than 100. An h-index of 100 would mean that the scientist had 100 publications with at least 100 citations  and their other papers had less than 100 citations. Although the h-index is controversial, it is readily available and reasonably capture scientists that have above average citations per paper and high productivity. We restricted ourselves to only living researchers. We used Publish or Perish to query Google Scholar (which now believes everyone using the internet in our office may be a bot).

We identified only 12 ecologists at level 100 or greater. For many researchers in specialized subfields, an h-index this high is probably not achievable. The one commonality in these names seems to be that they either work on problems of broad importance and interest (particularly, climate change and human impacts on the landscape) or else were fundamental to one or more areas of work. They were also all men, and so we tried to identify the top 12 women ecologists. (We tried as best as we could, using lists here and here to compile our search). The top women ecologists tended to have been publishing for an average of 12 years less than the male ecologists (44 vs. 56 years) which may explain some of the rather jarring difference. The m-index is the h-index/years publishing and so standardizes for differences in career age.

(It's difficult to get these kind of analyses perfect due to common names, misspellings in citations, different databases used, etc. It's clear that for people with long publication lists, there is a good amount of variance depending on how that value is estimated).

Other links: 
(I've been meaning to publish some of these, but haven't otherwise had a time or space for it.. )
Helping graduate students deal with imposter syndrome (Link). Honestly, not only graduate students suffer from imposter syndrome, and it is always helpful to get more advice on how to escape the feeling that you've lucked into something you aren't really qualified for. 

A better way to teach the Tree of Life (Link). This paper has some great ideas that go beyond identifying common ancestors or memorizing taxonomy.

Analyzing scientists are on Twitter (Link). 

Recommendation inflation (Link). Are there any solutions to an arms race of positivity?