My most heterodox scientific-writing lecture (or, how I annoy my colleagues in a good cause)

I’m well into my Scientific Writing course now, and I’ve just given the lecture that consistently annoys my faculty colleagues the most (well, it annoys many of them). It’s the one on writing the Methods section, and it’s heterodox in two rather different ways. This lecture stands out a bit – I don’t think my approach to IMRaD structure, or the content of the Discussion, or outlining, or writer’s block is all that different from the approach anyone else might take. But the Methods is different.

I said what I teach about the Methods is heterodox in two different ways.

Why my newest paper is paywalled

I’ve just returned the proofs for my latest paper. You can read about it, and access the preprint, here; or you can wait a little while and read the journal version in Proceedings B. Or, maybe you can. You see, it will be paywalled.*

Now, some folks find that scandalous: information should be free (or at least, that’s a common refrain. I have some sympathy, and I had the choice: I could have paid to make this paper open access. And all else being equal, yes: I’d rather my papers be open access than paywalled.

But that sentiment, noble though it may be, is uselessly naïve.

What an ecologist learned observing COP15

This is a guest post from occasional contributor Emma Despland. If you’re like me, you know that UN conferences like COP15 (more formally, the 2022 United Nations Biodiversity Conference of the Parties to the UN Convention on Biological Diversity) are, but you’re a bit mystified about what goes on at one. Here Emma gives an ecologist’s perspective on both the process and the product of COP15. The agreement (provided that it’s followed, of course) has huge implications both for our planet and for our academic field. Read on for Emma’s impressions.

Last month, I attended COP15 in Montreal as part of my university’s delegation. I volunteered mainly out of curiosity and didn’t really know what to expect.

ChatGPT did not write this post

Like everyone else, I’ve been watching the rise of “generative AI” with both interest and trepidation. (“Generative AI” is software that creates “new” text (ChatGPT) or images (DALL-E) from a user prompt – I’ll explain the quotes on “new” later.) Now, I know only a smattering about how generative AI works, so don’t expect technical insights here. But I’ve noticed an interesting gap between what I think these systems are doing and how people are reacting to them.

My interest in generative AI, especially text generators, is easily explained and probably obvious. Since I was in high school I’ve watched software get very slowly better at imitating the kind of writing humans do with great effort, and the kind of conversational interaction that humans do without a second thought.* The latest round is, superficially, really impressive: it can chatter pleasantly about nothing much, write a poem, program in R,** write an essay about Canadian history, explain linkage disequilibrium, and more. Or at least, it often looks like it can.

On rounding numbers, assumptions, and having one’s mind blown

Last week I had my mind blown. As I am something of a nerd, I had my mind blown by rounding numbers – or more specifically, by the fact that not everyone does it like I do. I know – that’s odd on several levels; but if you stick with me, I think there’s an important and generalizable message.

It started with a tweet*.