- This would have been handy when I was teaching intro to European Politics
How it started
It’s no secret that Mainz is a carnival hot spot. Shrove Monday, the day of the biggest parade and the most frantic celebrations, is a de facto public holiday in the city. But the de facto bit is important here: the city can’t make it a proper holiday, yet nobody who can possibly avoid it is working, so (collective) bargaining is important in a very practical sense.
At Mainz U, the workers’ representatives and the leadership must have come to an Agreement shortly after the war: on Shrove Monday, food outlets, libraries, departments, and central offices always were and always will be officially geschlossen, but there is a price. Until some years ago, we used to get reminders (on the back of our payslips) of the Arrangement: during an (extended) period of Lent, employees were supposed to work exactly 12 extra minutes per day to make up for the lost Monday. 17 minutes if you happened to be a Beamter (because of the slightly longer working week).
How it is going
Academics (who can work almost everywhere, have their own keys to the building, and are not known for their great sense of humour) used to laugh about it. Some even came in on Shrove Monday (if they could get past the hordes of drunk revellers filling the streets). But for the admin staff and even more so for the porters, janitors, or lab technicians, whose schedules were even more rigid than they are today, the Arrangement must have been a real achievement.
In the many years since the Arrangement was reached, working time has become more flexible for all employees. The 12-minutes-per-day rule was quietly dropped in accordance with that. Even working from home, an elusive privilege for many, has become the new normal, thanks to the pandemic.
And so you might think that the Arrangement, which decades ago brought some flexibility, could be handled in a flexible way this year. After all, there were no celebrations, hence no social pressure to be anywhere in particular.
But you would be very wrong. Just in time, the leadership reminded us that JGU observes Shrove Monday, and working from home is verboten on this very special day (which, in the absence of a parade or other distractions, had severe personal consequences for me). Explaining how this makes perfect sense from a bureaucratic/neo-corporatist point of view (I think it does) is left as an exercise to the reader.
Why yes, of course nothing says memefy just like a series of online lectures that everybody wants to fast-forward. And I have the tweets to prove it.
So I’m teaching a mandatory stats/methods class (always popular). Online. Following the advice from my own kids, I have memified the outline. For your own syllabus needs, here is the week-by-week program
Back in the mist of time that would eventually coalesce into my memories of the 1990s, I met a fellow PhD-er at a summer school. She had just returned to the fatherland after doing an MA in the UK and found re-integration into German Political Science rather difficult.
The toughest bit, according to her, was the collective obsession with Weberian concepts. She eventually solved that problem by assigning a set of (essentially random) choice MW quotes to the function keys of her keyboard. Or so she said.
I would not know, because this turned into reject after review and some substantial revisions. But after all these years, the meme still rings true.
Back in the mist of time, when I
should have been was working on my PhD, I found a blue book on the shelf that a previous occupant of the office had left there. As I learned later, it was The Blue Book that introduced the S language, the predecessor of R. I got sidetracked (as you do) and taught myself how to produce beautiful graphs in what is now known as base R, and how to run poorly understood time series analyses (impossible in SPSS at this point).
A little later, I got hooked on Stata, and to the present day, I refuse to be Stata-shamed, as Ben Stanley put it. 95 per cent of the time, it does the job, and quickly so. Also, the documentation is simply excellent.
But every now and then, I came back to R because I needed something specific. And it was mostly fun. Having access to all these APIs (in fact, concurrently having more than one data set in memory) was exciting. Having a real, reasonably straightforward scripting /programming language at my disposal instead of Stata’s hodgepodge of three (four if you count the graph language) half-baked syntaxes was exhilarating. Having a go at the latest methods on the basis of nothing more than skimming a working paper (skipping every non-trivial equation) was… I guess a little bit like trimming your hair with a chainsaw.
But finding, installing, updating and then loading three packages, just to make recoding a little more intuitive? Seriously, R? Not so cool. In fact, finding a variable (whose name and data set must be given in full) was usually enough to reduce me to tears. Attach() somehow never does what I think it should do. And so, I would return to Stata once more, like <insert awkward metaphor>.
Then, during one of my last forays, I began playing with the tidyverse. And as the young ones are prone to say: my mind was blown. Tibbles! Pipelines! Lots of yummie helper functions! Going from long to wide format and back (in various different ways)! Grouping, summarising, and even some pythonesque list traversing. This was no longer the fascinating but slightly stroppy R I used to know.
Compared to the handful of letters and abbreviations that I use in Stata to get things done, recoding-wise, this is still quite verbose, and I have to look up just about everything. But I really like it. Like, really like it. And so doing more stuff in R is firmly on the endless List Of Things I Want To Look Into. To end on the most positive note possible, here is a gratuitous picture of a cat.