Categories ▸ Politics
I saw this pie chart via Beth Popp Berman on Twitter yesterday:
Pie charts of student debts by percent of all borrowers and percent of all debt. As you probably know, the perceptual qualities of pie charts are not great. In a single pie chart, it is usually harder than it should be to estimate and compare the values shown, especially when there are more than a few wedges and when there are a number of wedges reasonably close in size.
The Congressional Budget Office released its cost estimate report for the American Health Care Act yesterday. There are a few tables at the back summarizing the various budgetary and coverage effects of the proposed law. Of these, Table 4 is pretty interesting. The CBO “projected the average national premiums for a 21-year-old in the nongroup health insurance market in 2026 both under current law and under the AHCA. On the basis of those amounts, CBO calculated premiums for a 40-year-old and a 64-year-old, assuming that the person lives in a state that uses the federal default age-rating methodology”.
Update: Since writing this post, I’ve repeatedly tried to delete the offending review from my profile, but Google Scholar keeps re-inserting it as part of its automated trawl through its corpus of articles. So it seems that the robots are determined to grant me these citations whether I want them or not.
Google Scholar is one of the most visible and widely-used examples of the rise of “impact measurement” in academia.
I was playing with some county-level data from the U.S. general election, partly out of a spirit of honest inquiry and partly out of a feeling of morbid curiosity. Because I had some county-level census data to hand, I took a look at the results using some extremely basic demographic information—the two variables that structure America’s ur-choropleths, namely population density and percent black. I focused on the counties that flipped from their vote in the 2012 general election.
The apparently failed coup against President Erdoğan of Turkey continues to unfold this morning, in what remains a very uncertain and fluid situation. Last night, during the most chaotic sequence of events, Erdoğan gave an interview via a video chat service on his iPhone, where he asserted the legitimacy of his government’s authority and called on the Turkish people to take to the streets against the coup. The picture of him talking via Facetime is already one of the iconic images of the night.
You may have heard the news that Lee Sedol, a Go Master, has been defeated by a computer program created by a group of Google engineers. A second match is underway today. The Google/DeepMind team has a technical paper in Nature describing AlphaGo, the program they wrote. Various commentators have remarked on the sometimes surprising but extremely effective moves that AlphaGo made. And of course there’s the usual half-serious musings about the inevitable robot uprising that this victory portends.
The FBI obtained a court order requiring Apple to unlock an iPhone 5C belonging to the San Bernardino killer. A public letter from Tim Cook lays out the grounds for Apple’s refusal. The debate about this conflict is developing quickly on both the technical side of things and the public policy side.
As a sidelight to this debate, I want to ask why is it that Apple, of all companies, is the one taking such a strong stand on this issue?
The current occupation of a federal wildlife refuge building in rural Oregon prompted me to make a map of the land owned or administered by the US government. There are a few such maps floating around, but I wanted to see if I could draw one in R. The US Geological Survey makes a shapefile available containing the boundaries of federal lands, so I grabbed that and simplified the category codings a bit, to make the main classes of land a bit more tractable.
This morning, Social Science Twitter is consumed by the discovery of fraud in a very widely-circulated political science paper published last year in Science magazine. “When contact changes minds: An experiment on transmission of support for gay equality”, by Michael LaCour and Donald Green, reported very strong and persistent changes in people’s opinion about same-sex marriage when voters were canvassed by a gay person. The paper appeared to have a strong experimental design and, importantly, really good follow-up data.
This UK Election data is really too much fun to play around with. Here’s a (probably final) collection of pictures. First, a map of the turnout (that is, the percentage of the electorate who actually voted) by constituency, with London highlighted for a bit more detail.
Constituencies by Turnout. There’s a strong suggestion here that Labour areas have lower turnout. Here’s a scatterplot of all seats showing the winning candidate’s share of the electorate plotted against turnout.
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