In one Seinfeld episode, George puts on an annoyed busy-all-the-time act at work. Consequently, nobody bothered him with work.
Here are a couple claims:
- In academia, the null hypothesis is that people are too busy to deal with your concerns.
- People are often poor judges about what another person thinks is important.
When people come to see you about things of no consequence, that is a Type I error. In this case they rejected the null hypothesis that you are too busy for them when in fact you are too busy for them. The probability of a Type I error is alpha.
When we act busy, we reduce alpha.
When others fail to approach you with something that is important to you, then that is a Type II error, as they accepted the null hypothesis that you are too busy for them but in fact you have time for them and their issue is important to you. The probability of a Type II error is beta.
We can minimize beta by acting open and free with our time. However, if we minimize beta, than we increase the threshold for a Type I error, and we get our time frittered away.
This statistical analogy of availability and time management falls apart at this point: In science, a Type I error is more grievous than a Type II error. In personal relations and mentorship, a Type II error can be catastrophic. Getting your time nibbled away piece by piece is problematic. But, it’s a lot worse when a student with a critical concern doesn’t come to talk to you, or when a colleague with a great collaborative opportunity thinks that you don’t have the time.
The people who need our time the most are the ones who feel anxious about wasting our time.
The marginalized people in your midst, who most need help and advocacy, feel the least entitled to make avail of your time. I really, really want people to approach me when it matters. It’s my job to be there for students and colleagues. If students are not comfortable approaching me about things that matter, then I’m doing my job badly.
On the other hand, if I was maxed out on the approachability meter, then it would be hard to get through any given day. There has to be some kind of balance.
However, of late, I’ve totally botched it. In the last few months, I’ve had two students with smallish-scale concerns that could easily have been addressed with a short conversation or set of emails. I’ve tried to let these students know that my job is to be there for them and to discuss matters like this. But, at the same time, I have presumably been projecting the fact that I’m busy with all kinds of stuff. So they didn’t bring these things up to me. And then these small problems grew, so that they were no longer small problems. And then because they felt bad that they didn’t approach me when it was a small problem, they avoided bringing the big problems to me, even though it was critical that I find out about these problems as quickly as possible to attempt to fix the situation that was now beyond the students’ ability to fix.
Not only did this create big problems for the students, but then they became big problems for me. They really should have brought these things to me earlier. I can’t blame them too much for not bringing it to me, because they felt that they couldn’t approach me at the time. That’s my bad. My students need to know that i’m available for them and that they’re my highest priority. I say this with words, and I try very hard to be welcoming, but my actions apparently belie my my attempt to be approachable. As I get older and more different from my students, this approachability problem isn’t getting any easier.
In statistics, the way to keep alpha low but also maintain a low beta is to use statistical approaches that maximize the power of the analysis (large sample sizes, robust tests). There are some people in my midst who manage to be approachable when it matters, but deflect or avoid the stupid stuff that saps away their time. That’s some kind of time management ‘power.’ I might have been professoring for more than 15 years, but I’m still puzzling through how to finesse this without resulting in the occasional laboratory meltdown.