University support staff should understand universities

Warning: I’m grumpy today.

Every so often I reread one of my old blog posts (usually, it’s one I’ve forgotten that I wrote). Almost all the time, I find myself nodding in agreement – which, I suppose, won’t surprise you.* But this morning I reread University administrators should understand universities, and realized I had it wrong.

Well, not actually that wrong. I’d argued that higher-level university administrators (not Deans and Chairs, I mean, but Directors of Information Technology Services and their ilk) ought to have some idea what a university actually does, and how those of us who actually do it go about the doing of it. I’m still quite convinced that’s right! But then, about 2/3 of the way in, I found this howler:

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Convenience and ecological knowledge

Do you know the old joke about the fellow who was looking for his keys under a streetlight?  A neighbourly passerby came up and offered to help. “Did you lose your keys here?” he asked.  “No,” the fellow replied, “over there in that alleyway – but the light’s better here”.

This is quite funny until you realize that as ecologists, we do it all the time.

Why do pre-meds want to do research in my ecology lab? And should I let them?

When I got my (first) academic job and my lab opened for business, I got a surprise. I expected undergraduate students to ask me about doing research in my lab. After all, as an undergraduate myself I’d learned an enormous amount by doing research with mentors – some of whom I still talk science with today. I expected to have a lot of fun sharing my love of evolutionary-ecology research with students who were as excited about it as I was. But, as I said, I got a surprise.

It turns out that, over the years, many of the undergraduate students who’ve inquired about doing research with me aren’t actually as excited about evolutionary ecology as I am. That was the surprise: pre-meds wanting to do research in my ecology lab.*

Why would a pre-med student want to do research in my lab?

Do people really not know about research ethics boards?

Warning: I’m feeling cranky today.

It’s great to see scientists getting excited about doing interdisciplinary work – for example, in science studies.*  It’s embarrassing, sometimes, to see how bad they are at it.

Out in the forest, and out on a limb

Images: A field crew disappearing into the forest; field sites and gear for our soil-carbon project.  All © Stephen Heard CC BY 4.0

Warning: long and detailed – but the details are really the point, so don’t give up too quickly.

I called this blog Scientist Sees Squirrel in recognition of my lack of an attention span.  For 25 years, I’ve been bobbing and weaving academically, shifting research focus as collaborators, funding, access to systems, and just my idiosyncratic curiosity have favoured new projects asking new questions in new systems.  This has benefits and, no doubt, costs (so I’m definitely not claiming it’s right for everyone or even that it’s optimal for me), but it’s kept me excited about science for a quarter of a century.

And I’ve done it again.

My most important work is not what I’ve always thought

Image: This mobile, hanging in my office, was given to me by my friend Mary Harris when I got tenure.  It’s driftwood from the Skunk River in Iowa.  I’d just gotten tenure, and it’s made of dead wood – get it?

A rather poorly-executed and very poorly-communicated study made a big splash last week, with the claim that half of all ecologists “drop out” of the field within just 5 years.  The many, many flaws in this way of measuring and communicating people’s career trajectories have been thrashed out in other places, so I’ll just note for the record that by the paper’s critera, I myself have “dropped out” of the field.* 

Do I work for the Class that pays me? (guest post)

Image: Kya Sands/Bloubosrand by Johnny Miller used with permission.

This is a guest post by Artem Kaznatcheev, a researcher in the Department of Computer Science at Oxford University and the Department of Translational Hematology and Oncology at the Cleveland Clinic.  Artem also blogs as part of the Theory, Evolution, and Games Group.  I’m pleased to have this post, which pushes back in a very interesting direction against one of my posts from last year.  Read on!

At the end of last year, Stephen Heard wrote that he doesn’t work for the people that pay him. He wrote in his usual positive tone and focus. A positivity that has me coming back to this blog regularly. In particular, he pointed out that his work as an ecologist has a positive impact all over the world. Thus he is not working for the taxpayers of New Brunswick, but for people all over the world. He generalized this to all of scientific progress:

There’s an implicit global contract, I think, that having science progress is good for us, and that having universities helps science progress. Also part of this implicit contract is the idea that this is best done by everyone funding universities and setting scientists loose – rather than by New Brunswick funding a university with scientists who work only on New Brunswick problems, and likewise for other jurisdictions. The phenomenal progress of modern science, and its international connectedness, suggest that this implicit contract has worked very, very well.

He concluded with a reflection on the dangers of taking this global focus away from universities. And that he is unapologetic about not working for the people that pay him. Stephen was positive about the good that science does for the everyone, not just those that pay him.

But in this case, he found this positive tone by focusing on geographic divisions and geopolitical boundaries. He suggested that science often transcends these. I think this is probably correct, but — given my curmudgeon nature — I don’t think it is the most relevant division.

I don’t work for the people who pay me

Image: A bit of my salary. KMR Photography, CC BY 2.0.

I don’t work for the people who pay my salary.  Or at least, not always.  And this shouldn’t be a problem – but I worry that it’s becoming one.

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. 

What’s in an idea?

Image: Idea by Alexas_Fotos, CC-0, via pixabay.com

This is a guest post by Quinn Webber, a 2^nd-year PhD student at Memorial University (MUN) in St. John’s, Newfoundland. Quinn is an avid science blog-reader and has begun writing for the MUN Graduate Studies blog. His post there on the origin of ideas struck a chord with me, and I asked him if he would adapt it for Scientist Sees Squirrel.

As a 2^nd-year PhD student, I seem to spend most of my time coming up with ideas and plans for thesis chapters. As of now, the plan is for five chapters: a conceptual review that integrates the ideas underlying the rest of my thesis (currently in revision), followed by four ‘data’ chapters. Some of the ideas that make up these chapters have been rattling around in my brain for a few years, while others were conceptualized and refined in recent months after reading new literature and chatting with colleagues, lab-mates, and my supervisor. It’s the process of conceptualizing and acting on ideas that I’m interested in and excited about. Ideas become the blueprint that guide data collection, analysis, and ultimately the thesis or manuscript.