The EiC at Nature Materials takes to the blogosphere…to argue that journals are the only legitimate place to discuss science. The best part is where he claims that you can either be a scientist or a blogger, not both (seriously!) The same kind of thing absolutely could happen in ecology. I once had a very frustrating exchange of comments with a senior ecologist who complained that a blogger’s critique of a Nature paper “wasn’t peer reviewed” (never mind that face to face conversations aren’t either) and “didn’t give the authors an opportunity to respond” (never mind that anyone is free to comment on a blog post) And indeed, I myself have sometimes badly misunderstood, and so criticized, online activities with which I’m unfamiliar. So I do wonder what fraction of ecologists badly misunderstand and/or are actively hostile to blogging. (HT Ed Yong)
You may recall the Sokal hoax, when physicist Alan Sokal got a fake paper filled with gibberish accepted to a postmodern cultural studies journal. Turns out that people doing postmodern cultural studies aren’t the only ones who can’t tell real papers from gibberish. A computer-generated paper filled with nonsense mathematics was just accepted by a mathematics journal. This rather undermines this old xkcd cartoon. My question: to what extent do these hoaxes reveal something about the fields in which they occurred, and to what extent do they merely expose the editors and peer reviewers involved as lazy or incompetent? I’d guess it’s some of both. Think a decent ecology journal could be hoaxed this way? I don’t think so, but I could be wrong. (HT Ed Yong)
Crowds are not people. Interesting New York Times article on the science of how people behave in crowds. The issue of “scaling up” that we’ve been discussing a lot (see here and here for two recent posts, and also this recent AREES article) crops up in fields far outside ecology. The history of crowd behavior science apparently is one of the gradual recognition that you have to scale up from the (context dependent) behavior of individual people in order to understand crowds of people. (HT Ed Yong)
Good advice for potential academic bloggers from academic blogger Simon Wren-Lewis.
Looking for a belated Christmas gift for the statistician in your life? Why not a plush lognormal distribution? Or even better, a plush uniform distribution–which is indistinguishable from a regular rectangular pillow! I also like the baby onesies that read “my p-value just became significant” (Meg, do you need one of those for your impending arrival?) Now, how about something for the theoreticians? How would one make a plush differential equation? (HT Jacquelyn Gill, via Twitter) (p.s. via email, statistician Andrew Gelman notes that the plush distributions technically are truncated distributions, since otherwise they wouldn’t fit in your house.)
Back before the wide availability of (pseudo) random number generators, the Rand Corporation’s 1955 tome A Million Random Digits with 100,000 Normal Deviates was an essential reference. You can still buy it, and as noted by David Giles, the reviews on amazon.com are hilarious. “But with so many random digits, it’s a shame they didn’t sort them, to make it easier to find the ones you’re looking for.” LOL!
Last semester, I taught Intro Bio. Obviously that’s a rather broad course, and I imagine that anyone teaching it for the first time will be lecturing on some topics that s/he is not very familiar with. In my case, there were definitely topics that I hadn’t thought about since I was an undergrad (colonization of land by plants being just one example). When I questioned how I was supposed to lecture on some of these topics, a friend recommended this series of blog posts (part 1, part 2, part 3) which focus on a book entitled Teaching What you Don’t Know by Therese Huston. I think the ideas in the second and third posts are most useful and easily implemented. The suggestion in the first post to meet with someone who is an expert in that area for coffee just doesn’t seem realistic to me. In a class like Intro Bio, there is a LOT of material, and, well, I would have been highly caffeinated by the end of the semester if I went with that strategy. But it certainly is something that would be interesting to do over the period of several semesters, as I update and improve the course materials.
From the archives:
“Neutral” means “no selection”. “Neutral” does not mean “stochastic” or “drift”. Nor does it mean “dispersal limited”. More on this soon. There’s a lot that ecologists could learn from basic population genetics besides what “neutral” means. And yes, this terminological confusion matters, because it reflects underlying conceptual confusion.