Déjà vu and the Balancing Act

Thanks to my brother Jake for altering this comic for me.

We have come to the time of year all grad students dread: the end of the summer, which means the return of the undergrads and our various semester-related duties (classes and/or teaching). In these last few uninterrupted days I am cramming in an immune assay that will be much easier to do when I’m not having to schedule it around meetings and teaching obligations.

This transition along with a New York Times special section on graduate school (came out a few weeks ago, but a professor just brought it to my attention) has me thinking about what the life of a grad student is “normally” like (and I guess when I say normal, I mean during the school year). We are always transitioning between one thing and another, going from teaching a discussion section in the morning to working on a grant application to doing some lab work, having to prioritize what we actually will get done (i.e. what can we half-ass the best today and what is going to take the front burner), with our constant companion being a guilty feeling like we should be working more, especially when we aren’t working and doing something like eating, watching TV, sleeping, or spending time with our spouse.

With any full-time job comes the multi-tasking and extra-busy periods, but I think the biggest difference is with a lot of jobs when you come home you leave your work at work. There isn’t the nagging feeling that you could or should be working on something all the time. Some grad students, they do work all the time, and a lot of them are really happy doing that and often have very productive PhDs as the result. But for those of us that can’t work all the time, it takes a while to find a balance between work and non-work where we don’t feel guilty and still get everything done.

The need for breaks was really solidified for me during pre-lims (part of our qualifying exams). This is a very intense period during our second year in grad school where we have six months to answer four essay questions and then orally defend those questions. There is so much to read and write that you can work all the time, and I did pretty much work on pre-lims whenever I wasn’t in class or sleeping. I did decide that I would take Saturdays off, or at least not work very much those days. I also started doing yoga that semester, which has become a regular part of my routine now. Making the decision to have a break helped be not worry all weekend that I should be working on my pre-lim answers. But, because I was taking a pretty hard class at the same time, I did end up working on the homework for that class with other people on Saturdays, which killed my one free day. The homeworks being really difficult for me would sometimes send me over the edge of stress, making me incapable of working at all that day and undoing any productivity. I felt like a huge bitch on the weeks where I ended up not having a break, even though my friends deny that I actually was.

Now that I am back at the point in the year when I can’t do whatever I need to do whenever I want because of teaching responsibilities and meetings, I need to get back to honing my multi-tasking skills. There is a lot of work to get done and never enough time to do it all. But making down-time one of the things that balances out the week will hopefully make this an efficient and enjoyable semester.

http://www.phdcomics.com/comics/archive.php?comicid=1073

ESA - more mobile blogging

This week is ESA (the Ecological Society of America) meeting in Austin, TX. Where 3,000 ecologists get together to talk about anything you can think of that goes under the umbrella of "ecology" (which is a lot!). I am giving a talk on my research Friday morning (the last session, where an unfortunate number of friends are giving overlapping talks). I am going to try some mobile blogging again, adding to this post throughout the day.

Me and my lab-mate Dan got in yesterday (Monday) afternoon. Pretty successful so far. Saw some mediocre talks go before my friend's very good talk, saw a couple people I've met at EEID meetings, and saw a former Madison classmate (we did a project on leaf-cutter ants for our tropical botany class) who will be defending his PhD from Princeton next week.

First session on trait-based approaches to disease ecology was pretty interesting. The best thing to come out of it was a discuss with a few of the other women working with tick-borne disease. Have a meeting with one of them who is worked on things really similar to me, immune function and how that relates to ticks and disease, since she will miss my talk on Friday. Its so nice to have the people who have the possibility of being academic rivals are actually really nice!

Doing the right thing

http://xkcd.com/552/

I’m not a very good liar, never have been (much to the chagrin of my teenage self). I have a big problem when people outwardly lie or try to deceive people (don’t even get me started on our current political situation). I sometime wonder if this is why I like science to think I make a good scientist, because ultimately we are looking for what’s true about the world. We look at data and see what it tells us about our research questions. A true scientist can have his preconceived views come crashing in around him at any moment if the evidence is there to overturn what he previously thought. There could be books written on “the best science at the time” and the significant repercussions of acting on what we thought was true then, and that we know isn’t true now. This can be really scary to people, knowing that you probably don’t have all the answers or that what you think one day can be completely challenged on the next. While most of the time this makes me feel good about my work, that it is honest and forthright, but there are days when I wish I wasn’t so truthful.

Sometimes it is really annoying to be a person who has to do thing, in this case concerning the data I am working on writing up as a manuscript to be submitted to a journal. Because I am dealing with field data, which is inherently messy, and a diverse community of multiple host and tick species, there are a lot of ways to analyze the data. There are many opinions on what the best way is. Which stats are best suited for the data, how to divide up and compare groups, how to/if transforming some of the data will improve the analysis. My head has been spinning the last couple weeks with all the data that I have available, how to describe it in a way that makes sense, and how to emphasize the patterns we think are the most important.

Unfortunately, the best solution on how to approach some of these issues would diminish the impact of our results a little bit. For instance, the data I have from the immune response assays I did with serum from the rodents needed to be transformed to deal with a handful of individuals who has somewhat strange patterns in the results of their test (I am going to withhold some of the details because this is unpublished work). There were two camps of how to transform the data, and I tried both out. Analyzing one kind of transformed data led to some near significant differences between groups of hosts. The other way showed far less statistically significant differences, and after digesting the pros and cons of each method seemed to be the more correct way to do things. This is pretty annoying because the differences I was seeing in these results we’re super significant and I thought this may diminish the impact of the story I was trying to tell. But in the long run I will feel better about presenting the results I think are the most accurate than cherry-picking the results that I “like” best. Still annoying, though.

This constant tug of war with wanting to find the answers and have mind-blowing results, and scientific integrity is a tough one. You’re not going to always get what you expect and you have to remember that negative or unexpected results are still results and they always teach you something. Whether it’s telling you that the pattern you expected isn’t actually what is happening, shows you that you need to improve your methods, or helps you design your next experiment. Because all scientists have probably experienced this in some way is probably why there is always such an uproar when its found out that someone faked their results. Top researchers have lost their jobs, or at least their credibility for doing dodgy science (for example: http://www.scientificamerican.com/article.cfm?id=fudge-factor). While I am definitely not at that extreme a point with my work, I can understand how tempting it is to present the results you think are true, even if they are not actually true. But that isn’t what being a scientist is about, and I think I’m ok with that.

P.S. The comic found here was shared by some friends on Facebook. It’s funny and true, it can makes the average grad student happy and sad at the same time (hehe)