Taking Stock 2/n How much should I work vs. how much did I work

Six years ago (nearly to the day) I started my lab at the University of Arizona. There have been numerous ups and downs in science and outside of science, but I'm still here. My tenure package was submitted last August (I've gotten good news but nothing official yet), we've just undergone about the third dramatic change in lab personnel, and there's plenty on the plate for the future. I figured it was a good enough time to sit down and begin to reflect on these last 6 years and dream about the next 30 or so. Not sure how many parts this is going to be, hence the /n in the title, but for this second post I'm going to at least provide my own slanted perspective on work/life balance. 1/n here: http://mychrobialromance.blogspot.com/2017/01/taking-stock-1n.html

Every once in a while the same arguments pop up on the tweets...they go something like this:

Passionate about science is great. But if we don't respect science as a normal 40-hour-per-week job, then we are hostile to diversification.

— Terry McGlynn (@hormiga) February 18, 2017

followed by

Disagree- if you are a GS and aren't living and breathing your research, do something else. https://t.co/S9IFWT9nPO

— Andrew Kern (@pastramimachine) February 18, 2017

and it escalates after that...

For clarity- I'm advocating that everyone sell their organs to fund their labs. https://t.co/HnMfl6Fkzs

— Andrew Kern (@pastramimachine) February 19, 2017

and so on and so forth.... Side note, for a great thread(s) check out what followed this tweet:

Okay, wading into something here and heading to bed....*taps mic*

— Needhi Bhalla 💅🏽 (@NeedhiBhalla) February 19, 2017

 Healthy discussion is great, sharing different viewpoints is great. They are all valid points, and much of the required nuance is trashed by the 140 character limit and difficulty in relaying tone because twitter.

I fall squarely in the camp that every single one of us has different work schedules and different requirements for how much to work in order to be "productive". Terry McGlynn hit the nail on the head exactly when he mentioned that one of the main problems with discussions about work/life balance in academia is that we inherently (ed: often not openly) disagree about what constitutes "success". Some want to win a Nobel prize. Some want to make a difference in the lives of those who have no one else to encourage them. In many ways, these are equally difficult challenges. There are many variations on what "success" is, and they're different for everyone.

One of the greatest challenges I've seen with being a PI is that, in the US system at least, we become used to judging our own worth compared to other people's metrics. Did I get an A in the class? Where do I rank with my GPA? This doesn't ever stop. Did I get into the program I wanted? That person in my cohort just published a paper, why haven't I published a paper? That person works more than me? and so on and so forth. At some point (I'd argue in grad school) we lose the ability to have definitive metrics to compare ourselves against and this is completely unsettling when your career is firmly placed in the context of data gathering. That first day you step into your empty lab space, you try and grab onto any foothold you can to try and gauge whether you are doing *enough*. Ideally, you have great mentors that can guide you along the way and offer advice, and ideally you are getting feedback from those on the tenure committee and during annual reviews, but there's no magical metric to tell you whether you're doing *enough*. Don't even get me started "how many grants and papers you need for tenure" because it's different for different people even in the same department. Allow me an (American) football metaphor for research...some teams try to score a touchdown every single play. Some teams are content to move the ball 3 yards forward every single play. You can be successful using both strategies and mixes of both but both require you to just move the ball forward by the end of the game. I'm not sure where defense plays into this, but I was on a roll so there you go.

There have been weeks when I've worked 80 hours and those that I've worked 0. There have been days when I've worked 24 hours (usually before a grant deadline). There have been many days that I haven't worked because (at least for me), I need to take at least one day fully off every week to stay sane. I tell the people in my lab that my metric for judging whether things are on the right track is that we should set up mutually agreed upon goals and work towards making constant progress towards these goals, and yes, I count failed experiments as constant progress. Aside from having to OK hours on a timesheet, I don't really keep track of how much or how little people work. I figure that everyone has their own rhythms and effective times and encourage them to make the most effective use of their time. I try to set an example through my own actions, but I don't expect them to exactly copy my work habits. Have goals, keep your eye on them, work enough to give yourself a fair chance at accomplishing them. Reevaluate the goals frequently because contexts change. Perhaps the second greatest challenge I've had as a PI is learning to have empathy for other people's working and learning styles. It's not easy, but it's incredibly important. That said, I understand and respect the other side of the argument but it's just not for me. We often have the opportunity to choose what we want in the labs we join, and I think the best we can do is represent how we view work/life balance and *success* so that those that are actively choosing can make an informed decision.

This is getting long, so one last observation about what "work" is. I've learned that I do my best writing and thinking when I'm running or otherwise being active. I've written a lot of my papers while not actually writing. I've written a lot of my papers and grants while not "at work", while in the shower, sometimes in dreams (for real...just kind of wake up sometimes and write stuff down and it's coherent). Does this kind of *work* play by a 9-5 schedule? Is it actually work? I have not clue...but it's what I've done and it's what works for me. I think this was Kern's point above before the nuance was lost to the twitter Gods.

Teaching Microbiology in the Era of #Fakenews

Wanted to briefly post about an interesting situation I'm encountering right now in my Microbial Genetics class. We just had a quiz exercise where I effectively asked this True/False question:

True/False During bacterial transcription, RHO-DEPENDENT terminators utilize a hairpin loop

To me, and my understanding of transcriptional termination, the answer is clearly false as far as science knows right now. I went over factor dependent and independent terminators and focused on how factor independent terminators can be identified by hairpin loops in the DNA/RNA sequence (usually followed by something like a run of Poly-Us) and contrasted this with how there was only a sketchy signal for rut sites in terms of rho-dependent termination.

It sucks to be wrong, and especially to make mistakes when lecturing to a class of undergrads, but there is a part of me that loves it when I get challenged by what I've said with actual data. It's a learning opportunity and I enjoy when students go above and beyond to find other sources of info.
My standing agreement with students is that if they can present me with primary literature that demonstrates their argument, I'll give them points regardless of how the quiz was originally marked. I think that's only fair...

However, a couple of times I've run into a situation this semester where students cite non-primary lit sources to demonstrate their point. In the case of the quiz question above, they've cited a couple of YouTube videos about Rho-dependent terminators (here and here) that AFAIK incorrectly state that rho uses hairpins.

I see this as a very small battle in the larger world of #fakenews where we are constantly barraged with other peoples digested opinions and views rather than read the original undigested words. Regardless it's troubling. I'm going to mention this in class example in class today, and point out that "when in doubt find a primary source and look at the original data" is a great go to for deciding what's "real" in these situations.