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. Continue reading
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. Continue reading
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. Continue reading
Image: Idea by Alexas_Fotos, CC-0, via pixabay.com
This is a guest post by Quinn Webber, a 2nd-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 2nd-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. Continue reading
Lock image: SimpleIcon http://www.simpleicon.com, CC BY 3.0
Every week or two I see a tweet, or overhear a conversation, from somebody bemoaning the difficulty of accessing a paper. Often it reads about like this:
Another day, another paywalled paper I can’t access and won’t cite. Moving on to read some open science….*
I get that open-access is an attractive model**. I’d be pleased if we moved all our literature this way, although only if that meant that we had solved the (enormous) transitional funding problems and dealt with the inevitable unintended consequences. But none of that matters to a simple and important point: I don’t care how fervent an open-access advocate you are; it’s still your job to use our literature properly. It’s absurd to claim that a paper deserves to be read and cited if it’s published in The American International Journal of Ecography (a hypothetical open-access journal that’s predatory with fraudulent peer review***), but not if published in The American Naturalist (a subscription-model journal of very high quality published by a great society). Absurd. Continue reading
Images: selections from Heard 1992, Patterns in tree balance among cladistic, phenetic, and randomly generated phylogenetic trees. Evolution 46:1818-1826. Orchid photo (Belize) © S. Heard.
While I think my research is interesting and important, I’m well aware that few of my individual papers are likely to change the world. Really, this is a normal feature of science: most progress comes from the accumulation and synthesis of many small results, not from a single mind-blowing paper. But some of my papers have been more influential than others. It’s interesting (and to be honest, a bit galling) that what I think is my most influential* paper (Heard 1992, Evolution, Patterns in tree balance among cladistic, phenetic, and randomly generated phylogenetic trees) was an accident. Continue reading
Photo: Mushroom arrays on the forest floor in a “play” experiment (S. Heard).
Much of science is a craft: doing it well involves the application of practiced skills, which can be honed (if never completely mastered) by anyone with time and experience. In an experiment, for example, we have powerful experimental design, meticulous repetition and recordkeeping, appropriate statistical analysis, and clear writing to report the results – all things we can become objectively better and better at with practice.
But there’s creativity in science too, and it lies in the source of our ideas. This part of science is more mysterious. Continue reading