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.
The hosts at Accidental Tech Podcast have been thinking about how to broaden their base of listeners to include more women. Good for them. They’re getting plenty of advice (and a certain amount of flak), which I won’t add to. But in general when doing this kind of thing it can be helpful to look back on what your past practice has been. For example, it can be useful to audit one’s own habits of linking and engagement.
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.
I’m still playing around with the UK Election data I mapped yesterday, which ended up at the Monkey Cage blog over at the Washington Post. On Twitter, Vaughn Roderick posted a nice comparison showing the proximity of many Labour seats to coalfields.
That got me thinking about how much the landscape of England is embedded in its political life. In particular, what do the names of places tell you about their political leanings?
The United Kingdom’s election results are being digested by the chattering classes. So, yesterday afternoon I thought I’d see if I could grab the election data to make some pictures. Because the ever-civilized BBC has election web pages with a sane HTML structure, this proved a lot more straightforward than I feared. (Thanks also in no small part to statistician Hadley Wickham’s rvest scraping library, alongside many other tools he has contributed to the community of social scientists who use R to do data analysis.
A side-note to the enjoyable exchange with Dr Drang about sales trends in Apple products, which was picked up by John Gruber. The LOESS decompositions I posted looked like this:
Quarterly sales decomposition for iPhones. One or two people remarked that these figures were shorter and wider than they were used to seeing. I did this on purpose—following the approach taken by William Cleveland and others, the charts are banked, meaning the aspect ratio is set to make it easier to pick out trends.
Update (April 30th): I redrew the decomposition plots this morning, and added a couple more.
Another Twitter conversation, this time in the evening. Dr Drang put up a characteristically sharp post looking at sales trends in Apple Macs, iPhones, and iPads. He used moving averages to show long-term sales trends effectively, and he made a convincing argument that iPad sales are in decline. I ended up grabbing the sales data myself from barefigur.
Following a conversation on Twitter this morning, here’s a quick plot of some GSS data from 2000. Respondents were asked to estimate the percentage of people in the United States who fell into a range of (not necessarily exclusive) categories: White, Black, Hispanic, Asian, and Jewish. Here we show the median guesses of White respondents and Black respondents, together with the actual percentage of people in each category, based on the 2000 Census.
Thanks, Paddy. I’m very sad to hear that Paddy O’Carroll died this weekend in Cork. He was one of my first teachers in Sociology, and a man of deep intelligence, humanity, and insight into Irish society and especially its political community. Famously disorganized in lecture, he was nevertheless sharp as a pin in conversation. I can’t count the number of times he brought me up short with some observation or anecdote that I’d spend the rest of the day thinking about.
Last Thursday I gave a talk at the American Philosophical Association’s Central Division meetings about patterns in publication and citation in some of the field’s major journals. I have a more extensive analysis of the data that’s almost done, but that deserves a paper of its own rather than a post. Here I’ll confine myself mostly to descriptive material about some broad trends, together with a bit of discussion at the end.