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.

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Originality is over-rated. (Including by me.)

Image: Tulips, Vera Kratochvil CC-0 released to public domain.

Last week I reviewed a grant proposal for one of the European national granting agencies.  It was an interesting piece of work, which – if funded – would gather probably our best dataset so far to test some longstanding questions in my field.  It was ambitious, thorough, and well planned.  But it didn’t blaze any particularly new path: the techniques were standard, the questions have been in the literature for decades, and every planned analysis has been done before (albeit with smaller and less suitable datasets).

Before I’d even quite noticed, I found that I’d written a sentence in my review saying “There’s nothing original about the proposed research”.  But as I looked at that sentence – and as it glared back at me from the screen – I felt like it was judging me more than the applicant.  And it should have.

You see, originality in science is highly over-rated. 

Are two years’ data better than one?

Photo: Two giraffes by Vera Kratochvil, released to public domain, via publicdomainpictures.net. Two giraffes are definitely better than one.

Ecologists are perennially angst-ridden about sample size.  A lot of our work is logistically difficult, involves observations on large spatial or temporal scales, or involves rare species or unique geographic features.  And yet we know that replication is important, and we bend over backwards to achieve it.

Sometimes, I think, too far backward, and this can result in wasted effort.