Last Monday, I faced a post-travel inbox filled with emails that needed replies. Some of them were invitations for things that would take up my time, but that seemed interesting or important or valuable or all three. And, then, of course, there were all the other things I needed to do as part of my job – editing manuscripts, writing letters of recommendation, sending emails to get people access to the lab, analyzing data, etc. And it was also the day where my post on seeing a therapist appeared, which led to lots of interactions on social media, via text, and through email. All of that led me to revisit a question that I am constantly asking myself, and that I surely will never stop asking myself: how should I spend my work time?
I couldn’t get this out of my head, and, as I walked to daycare, I realized that there are three questions I should consider as I evaluate whether to do something:
- Is it officially part of my job?
- Am I particularly good at it?
- Do I enjoy doing it?
I thought about how, ideally, I should try to prioritize things where the answer would be “yes” for all three. And I thought about how I spend a lot of time on things where the answer to all three of those questions is “no”.
When I got to daycare, I knew I wanted to think about this more, and was worried I would forget it. So, I pulled out my notebook in the daycare lobby, propped it on top of the stroller, and drew this:
Last week, I had the honor of being a plenary speaker at the biology19 conference in Zurich. This is an annual meeting of Swiss organismal biologists, where most of the attendees are Swiss graduate students and postdocs. When I first thought about my talk, I debated whether to use the last part to talk about mental health in academia, especially since I am on sabbatical this year and some of my sabbatical projects relate to student mental health. But, when I prepared my talk, I decided to just stick with my normal research.
On the first day of the meeting, I had several conversations with people that veered towards student mental health, which made me wonder if I should have included mental health in my talk. Then, the afternoon plenary on the first day was given by Virpi Lummaa. She gave a really interesting talk about her research, but pivoted at the end to talk more about the human side of science. It was inspirational. So inspirational that I went back to the hotel and changed the end of my talk to focus on mental health in academia. When I decided to make that change, I made another decision: I would admit to a room full of hundreds of my colleagues that I see a therapist regularly, and that doing that is essential to my ability to do everything I do, including my science.
As I’ve blogged about a few times recently, I have been working with a couple of collaborators, Susan Cheng and JW Hammond, on a project aimed at understanding student views on climate change. As part of this, I’ve been thinking about what we teach and how we teach it, and also about a common challenge faced by instructors who teach about climate change: how do we convey the severity of climate change without leaving students feeling depressed and hopeless?
As I was working on the manuscript describing the first set of our results, I typed a sentence to that effect, and then just sat and stared at the computer for a bit, wondering “Is it my responsibility as a biology instructor to leave students empowered and with a sense of purpose?”
Some ecologists start their careers planning to study climate change, and others make a decision to pivot towards that line of research. But something I find fascinating is that there are ecologists, myself included, who didn’t necessarily set out to study climate change, but who are accidental climate change biologists. To give just one example: if you work on a time series on natural populations, communities, or ecosystems that extends more than a few years, chances are you’ve found that climate change is now a part of what you’re studying.
I’ve thought about this over the years as projects we work on that started out as basic research into host-parasite interactions end up relating to climate change. Some links are obvious—wanting to understand how temperature influences host-parasite interactions leads pretty naturally to thinking about how climate change will influence host-parasite interactions. Some links are less obvious—for example, we wondered whether the light environment might be influencing when and where we saw parasite outbreaks. As I recall, our initial interest in this was not related to climate change. But lakes are getting browner, in part due climate change, so any work we do on how lake light levels influence disease naturally links with climate change. And we now have some data on host-parasite interactions in lakes that spans 1-2 decades. Once you’re into decadal time scales, you have to consider the impact of climate change on what you’re seeing.
I’ve also thought about this in terms of some projects I didn’t work on. When I started grad school, one of the projects I was thinking of working on related to what was going on under the ice in lakes in winter, and how things like snow cover influenced that. So, when I saw news articles about a new study showing that there will be an “extensive loss of lake ice…within the next generation”, I thought back to those grad school plans to work on lake ice & snow cover. My recollection is that my interest in that project was mainly wanting to understand the basic biology of lakes, but clearly it would have ended up being a study of climate change if I’d pursued it.
Based on conversations with colleagues, I know I’m not alone in coming to realize that I am an accidental climate change biologist.
So, I’m curious: for my fellow accidental climate change scientists, when did you realize you were studying climate change?
Last week, I wrote a post where I talked about how my training in evolutionary ecology led me to try reaction norms (that is, paired line plots) for plotting paired Likert data. I had already tried a few other options, but didn’t include them in that post, and I got some feedback on that post that gave me more ideas. There was also a request for code on how to actually generate those plots. So, this post shows four different ways of visualizing individual-level responses to paired Likert-scale questions (paired line plots, dot plots, mosaic plots, and heat maps). It does that for two different comparisons, leading me to the conclusion that the type of plot that works best will depend on your data. I’d love to hear which ones you think work best — there are polls where you can vote for your favorite! And, if you’re working on similar data and want to see code, there’s an associated Github repo, but it comes with the disclaimer that my code is good enough, but definitely not elegant.
Two things recently came across my twitter feed that relate to academics moving. First, there’s this piece by Dan Hirschman noting that academics often make multiple long-distance moves (in contrast to most Americans, who live close to family as adults), and asking what effect all this dislocation has on the research people produce. Second, there’s this piece in Nature on how academics navigate tenure denial, which includes advice to seek job offers from other universities while one is up for tenure.
At some point in an Ask Us Anything post, someone asked about things where our views have changed a lot over our careers. As usual, I didn’t manage to answer it, because, for some unknown reason, I stink at AUAs. But here is my very belated response: as an undergrad and a grad student, I bought the idea that I should be willing to move anywhere if I wanted a career in academia. Now I don’t.
Note from Meghan: This is a guest post by Gergana Daskalova, a PhD student at the University of Edinburgh.
I recently attended the British Ecological Society Annual Meeting, one of the biggest scientific conferences in the calendar year of an ecologist. Over the course of just one day, I got asked where I am from 18 times. I counted because in just four years of attending conferences, meeting with seminar speakers and engaging in similar activities, I have been asked where I am from way too many times. When the pattern repeated itself on day one of the BES conference, I thought I could do the actual count on day two of the conference. I, like many other of my fellow conference goers, get these questions at a very high frequency probably because our looks or accents give away that “we are not from here”. Though it may seem like an innocent question – where are you from? – it leaves me feeling like my fellow ecologists are more interested in why I stand out than why I belong.
To counter the question in a productive way and to get the focus back on my science, over the last year, I have made a point of replying that I am from the academic institution where I am doing my PhD. People always follow up with “No, I meant where are you from originally?” The problem is not that I want to hide where I am from, the problem is that in a professional scientific environment, where I am from shouldn’t matter. When people make general chat at conferences with a group of PhD students, most of them get asked what they do. When the conversation makes its way to me, I get asked where I am from. Followed by comments about my country of origin. Cool! Exciting! I’ve never been to that country. Why did you come here? What a poor country. Was it hard living there? The list goes on. Only just over half of the 18 people that asked me where I am from originally then went on to ask me about my work.
Reviewing is something that brings out my imposter syndrome, and I know I’m not alone. Being asked to review implies that someone views us as having expertise in a given area, which means that, if you screw up the review, you will reveal yourself as an imposter (or so our brains tell us). And, for journals that copy reviewers on the decision letter, one way to tell if you’ve messed up and are an imposter is by comparing your review to that of the other reviewer(s). Rarely, I’ve been unable to figure out which was my review, because the reviews were so similar. (Phew, not an imposter!) But what about when the other reviewer notes things I missed? Clearly that means I’m an imposter!
For a long time, I viewed it as a failure on my part if the other reviewer caught something I missed. I felt like it indicated that I hadn’t been careful or critical enough. If we aren’t super critical, we aren’t good scientists, right? (I’m being facetious. I don’t actually believe that being harsh = being a good scientist. And it is definitely not the case that the harshest review is the best review!) But what about cases where the other reviewer raises concerns or criticisms that seem important and insightful and constructive. If I missed those, I failed as a reviewer, right?
Again, not necessarily. The reason relates to something covered in a recent blog post by Stephen Heard, where he talks about finding reviewers. In it, he says he only uses one of the reviewers suggested by the authors, and explains that is because:
Last year, I supervised Honors Thesis research by Morgan Rondinelli related to mental health in two introductory science courses at Michigan (Bio 171 and Physics 140). Morgan’s survey included two common screeners, one focused on symptoms of depression (the PHQ-8*) and one focused on anxiety symptoms (the GAD-7). The survey also asked about previous diagnoses, stress mindset, resource usage and knowledge, barriers to seeking help, and demographic information. Here, I will briefly summarize some of our findings, but I will especially focus in on the area that seemed the most novel: student views on stigma associated with seeking mental health care.
The tl;dr answer to the question in the post title is: it seems possible.
Yesterday, I had a post about how it’s okay to start small when it comes to learning R or any other new technical skill. Today’s post takes that same “it’s okay to start small” message and applies it to public engagement.
Sometimes, a colleague will ask about a recent public engagement activity my lab worked on. After I describe it, they sometimes say something like “I’d like to do more outreach work, but my lab isn’t as big as yours – I don’t have those people to help me!” Often, that is said with a sense of resignation that it won’t be possible for them to do outreach. Or perhaps the conversation centers around an upcoming NSF proposal, where a colleague is trying to figure out what they could propose for the broader impacts section, feeling like they want (or need) to propose something, but that there’s no way for them to do that if they are just starting out or haven’t done much public engagement in the past. In these conversations, my messages are:
- it’s okay to start small, and
- take advantage of existing opportunities.