This single Graham’s post explains more about productivity than most entire blogs on the topic out there. It was a revelation to me. Any day that has more than two non-clustered events becomes wasteful automatically. It’s like your mind can anticipate the futility of trying to get in the zone only to get kicked out of it by a meeting. This also explains why the typical ‘maker’ (a postdoc, or grad student working close to the data) tends to gravitate towards late nights work stunts, whereas professors rarely do. In fact, one big difference between professors and grad students is the number of meetings they have to endure… Can you be a maker and a professor? If so how do you do it?
Archive for category: Time management
In a previous episode, I suggested that productivity is really just an efficiency measure. Since the working currency for academics is arguably prestige, productive researchers are those that can acquire the most prestige for the least effort and this can be formally written as:
where each task t is assigned a prestige benefit (pt per activity × n activities) and an effort cost (attention units per hour at × ht number of hours).
The comments on the original post suggested that there was a lot of enthusiasm for implementing and testing the theory and so I’ve spent the past month gathering data and preparing for a bit of an empirical assessment. The results are a work-in-progress but I hope to keep the conversation going and get your feedback. Here then is a step-by-step guide to how I’ve analysed my productivity over the last month using the general model.
I want to try something a bit different in this post. Here at AP.com, we’ve talked a lot about tools, theory, trends and the general ephemera of academic productivity. But writing as academics, we should probably be trying to take this experience and build it into a cohesive model of productivity. So my goal here is to suggest a general model, one that we might use to understand what we’ve learned from previous posts and hopefully apply to our own work.
My starting point for this post was simple; I wanted to know how my productivity has changed (hopefully improved) since I first started my DPhil. From keeping a research journal, I know that some days are more productive than others and it would very helpful if I could understand when those fits and starts occur, to spot co-occuring events and thereby learn when to say “Forget work, I’m going for a run.”
In other words, I wanted to plot my productivity cycle over time. It might look something like this:
But the obvious problem with this exercise is how to measure productivity. It’s a subject that’s been tackled indirectly on this site before but going through the old posts, I haven’t yet find any attempts at a general theory – and related measures – of productivity. So drawing on the collected wisdom of previous AP.com posts, here’s a rough sketch of such a theory.
I am probably the only exception in the AP team. As a longstanding MacTeX user, I keep my references organised with BibDesk, one of the sweetest pieces of (open source) software ever written for TeX users working on Mac OS. When hunting for references, I use CiteULike as a fast and effective solution to bookmark and tag papers. My workflow usually starts with an exploratory phase based on CiteULike. As soon as I have read a paper and need to cite it, I export its reference from CiteULike into BibDesk, filing the PDFs with the help of the autofile functionality in BibDesk. So far I have been quite happy with this workflow even if it involves a little bit of fiddling to correctly import references into my local library.
Do you wonder why people without funding do research? Naw, probably not, because you do it too . Getting grant money involves a huge effort and most people do not have grants. However, everyone tries their best to get time to do research. In fact, universities encourage their faculty to focus on research at the expense of teaching time. This article covers a few theories on why this might happen. For example, Students gravitate toward research orientations, and Research quality has become a proxy for teaching quality. Interesting that two economists wrote it.