I’m teaching a course for the CIEE study abroad program on Jordanian politics, and I was talking with a couple of colleagues about how nice it is to be back “in the classroom” and working with intelligent students. I’ve always been inclined to incorporate games or simulations or other ways of making course material and concepts “stick.” So a colleague and I were talking about running a simulation on a contemporary issue relevant to Jordan — perhaps a parliamentary debate over the “mubadara” initiative (since that’s gone so well in the real Jordanian Lower House), or of a crisis simulation dealing with spillover from the war in Syria, or perhaps a set of Palestinian/Israeli/Jordanian/US negotiations to construct our own ‘Kerry Plan’.
I’ve done quite a bit of this sort of thing previously, teaching Model United Nations, creating a simulation of the Iraq parliament, and doing a month-long simulation of government-opposition interaction in a fictional country called Authoritania in my class on authoritarianism.
Then I came across this excellent idea — teaching WWI in real time (a hundred years later). Very cool. Very inventive. There are so many possibilities from this one novel idea of making the past the present in the same chronological increments. I’m interested to see how Scott Wolford, the prof teaching the course, designs it. I assume it will be heavy on primary source materials. He’ll be blogging the process, so more inspiration to come, I’m sure.
In the process working on time series data for my dissertation, I recently came across an excellent utility for data visualization called CartoDB. Besides being an excellent mapping tool, it is particularly helpful for people less familiar with GIS technologies but nonetheless want to see their data spatially.
As my dissertation relates to leadership change in non-democratic regimes, succession events are a good candidate for taking this visualization tool for a spin. So I pared down the dataset I’m working on to a few key variables to create a dynamic view of leadership change across the world and over time. I should also note that I did have to import geocodings for the countries in my data (specifically their capitals) as this was not a piece of information I had previously. This was a pretty simple task thanks to an excellent geocoding database called “Countries of the World” The map I created is below and depicts all leadership changes (via Goemans, Gleditsch, & Chiozza’s ARCHIGOS dataset) in non-democratic regimes since 1946 (from Milan Svolik’s data from his excellent book on authoritarianism).
You can go HERE for the direct link to the visualization.
I have other variables in the table that differentiate between types of succession (regular, irregular, natural death of the incumbent), but for now this visualization gives a good sense of the density of leadership change in authoritarian regimes across the globe. It would be nice to distinguish between these different types of succession the map, but as Jay Ulfelder notes in his visualization of coups d’etat, it doesn’t seem possible yet on CartoDB’s Torque (time series) option.
There are a bunch of other visualizations I’d like to do using CartoDB given the efficiency of using this cloud mapping utility and its high-quality products. John Beieler has mapped protests from GDELT data which received a lot of media attention, and there’s a lot more to visualize with that data at the country-level going forward.
Reposted from Jay Ulfelder who used CartoDB with data on coups d’etat around the world to provide an excellent visualization over time.
via EVEN BETTER Animated Map of Coup Attempts Worldwide, 1946-2013 | Dart-Throwing Chimp.
A week ago, I posted an animated map of coup attempts worldwide since 1946 (here). Unfortunately, those maps were built from a country-year data set, so we couldn’t see multiple attempts within a single country over the course of a year. As it happens, though, the lists of coup attempts on which that animation was based does specify the dates of those events. So why toss out all that information?
To get a sharper picture of the distribution of coup attempts across space and time, I rebuilt my mashed-up list of coup attempts from the original sources (Powell & Thyne and Marshall), but now with the dates included. Where only a month was given, I pegged the event to the first day of that month. To avoid double-counting, I then deleted events that appeared to be duplicates (same outcome in the same country within a single week). Finally, to get the animation in CartoDB to give a proper sense of elapsed time, I embedded the results in a larger data frame of all dates over the 68-year period observed. You can find the daily data on my Google Drive (here).