Given my recent (and successful!) job search, I've thought a lot over the last several months about how I'm perceived as a scientist. My musings generally relate to how I explain my own expertise to my peers, both within subfields and to a broader set of academics. There was a certain amount of image revamping involved in my switch from plant systematics as a graduate student to more comparative genomics as a postdoc, and I spent a little time researching methods for effective professional rebranding. For example, I've found it valuable to think about how a professional bioinformaticist spends their time, and made sure I took classes, talked to people, and got a GitHub account. These things are useful as professional development, but also necessary to include on a CV and in other resources, to show that I know what I'm talking about.
While traveling recently, I came across a rather large advertisement in an airport which represents a much more dramatic attempt at rebranding the professional image of scientists. The Geoffrey Beene Rock Stars of Science program has been around a few years, and is aimed at promoting cancer research by bringing together scientists and rock stars. I don't know much more about it than that. Perhaps it was my lack of sleep or travel weariness, but it struck me as a rather comical attempt to merge the high-profile, devil-may-care attitude of the rock world with the meticulous, potentially life-changing realm of cancer research. I was left wondering about the main goal of this attempted merger. More importantly, I pondered what journal I could convince to publish my glam-rock album cover in their next issue.
The effect of this ad struck home when I started to think about larger patterns of how these professions individually are perceived by the public. The union of popular music with philanthropy is not new, and neither is an attempt to show scientists are more diverse than just balding, aging white men who wear lab coats and eyeglasses. I've had a number of articles kicking around my "To Write" list for awhile which address the phenomenon of Princess Scientists, or the representation of scientists who are also beauty queens, cheerleaders, and otherwise covered in lipstick and glitter. Given my choice of Princess Tradescantia as a blog title, the resulting debate is one I've followed with reluctant albeit vested interest. The opinions range from vehemently opposing the princess/scientist mashup to a more thoughtful piece by Stephanie Schuttler, one of my friends from graduate school. She contends that using conventionally feminine imagery to attract girls to science isn't necessarily a bad thing. I concur. To me, the only requirement for being a scientist is for someone to actually think about science. The main point is to eliminate additional expectations while simultaneously allowing for other identities, be it rock star, princess, or whatever your imagination desires.
At the end of the day, I still tend to prefer representations of scientists which encourage the full diversity of outside interests. A good example is This Is What A Scientist Looks Like. It's been awhile since the last update, but it's nice to look through and see scientists pursuing myriad activities, from painting to acting. Encouraging this type of plurality is especially important because of the intersectionality between this type of identity inclusion with acceptance of social, gender, sexuality, and racial minorities.
My identity includes scientist. It also includes fiber artist (knitter/spinner/etc), queer, and science fiction aficionado, among many other recurrent interests. Sometimes that includes princess, and that's OK. I couldn't find a picture of myself in full princess regalia, so please settle for this paltry offering of my wearing a silly hat. It has a little bit of shimmer, so hopefully that will suffice.
29 May 2014
28 May 2014
Even among big trees, I stare at the ground.
I flew out to California a few weeks back to meet my sister and mom for a road trip up to Reno for my brother's graduation. First off, congrats to Dr. Thomas J. Hertweck for completing his PhD in English (Literature and Environment) from the University of Nevada, Reno! I was pleased to be able to meet some of the other fantastic folks in his department, and am hoping to be able to collaborate on some Hertweck & Hertweck publications in the future. Although Tom professes to be "traditional" and eschews official obligations to social media, I know he still frequently lurks the interwebs…so good job, big bro.
Sequoia sempervirens, or redwood trees |
Glad to get the tree taxonomy off my chest! Turns out this trip was a good way to torment educate my family about botany.
Come to find out, even when I'm walking in a forest with some of the tallest trees around, I still tend to look down. Sometimes it's because a downward gaze lets you appreciate the size of these trees.
Come to find out, even when I'm walking in a forest with some of the tallest trees around, I still tend to look down. Sometimes it's because a downward gaze lets you appreciate the size of these trees.
Dicentra formosa, Pacific bleeding heart. Bleeding hearts are found all over the place, but this local species had nice pink flowers (I'm a sucker for them) |
Trillium chloropetalum, giant wakerobin (indeed, it was quite large, the size of a dinner plate!) |
Smilacina stellata, false Solomon's seal (widespread, the same one I see on the east coast!) |
I'll admit it…I really don't care about identifying trees from Rosaceae. |
Corallorhiza striata, an orchid (!) |
Sarcodes sanguinea, snow plant, a saprophyte from the heath/blueberry family |
I'm not gonna lie. I always feel pretty special when I see a saprophytic plant in the wild, and I think it's mostly just because they're so weird. Not green? Not a problem! Still a plant. I'm sure I'll wax philosophical about these and other topics again in the near future.
12 May 2014
Data management and maturing as a scientist.
I attended an awesome workshop last week called Data Carpentry. I briefly mentioned my attendance at a Software Carpentry Bootcamp a few years back, and suffice it to say that I was really excited for another two days of computational bootcamping. I even made a quick little Storify of a few of my tweets if you'd care to take a gander at some highlights.
I've spent quite a bit of time in my professional life learning to manage, analyze, and interpret data. In the 10+ years I've been conducting scientific research, my thought processes about how I relate to data have changed markedly.
I've spent quite a bit of time in my professional life learning to manage, analyze, and interpret data. In the 10+ years I've been conducting scientific research, my thought processes about how I relate to data have changed markedly.
- When I first started learning how to sequence data as an undergraduate, I thought the hardest part of science was collecting data, mostly because that's how I spent most of my time.
- As I started graduate school, I thought the hardest part of science was getting started on a research project. No doubt this was due in part to my adventures trying to collect plants for my dissertation.
- As I finished my PhD, I decided the hardest part of science was communicating scientific results to get them published, largely because I was being indoctrinated with publications demonstrating my value as a scientist.
- During the first part of my postdoc, I thought the hardest part was analyzing data. This is also unsurprising, as my work now is entirely computational (no data collection).
- The current iteration of my maturation as a scientist? I think the hardest part of science is keeping track of everything you've done and making it accessible to the rest of the community. It's a concept that encapsulates most of the previous "hardest parts," and while it doesn't often deliver tangible rewards like lines of code, pretty figures, or publications, it's satisfying and essential in its own way. Moreover, my career as a data vulture relies on the community's ability to maintain reproducible, open science.
Anyway, that's why I'm so excited about learning better ways to build/query databases, share code, and maintain data.
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