A friend sent me the link to this very short article in Perspectives on Psychological Science that use precious journal space to highlight a lot of rather disturbing parallels between (social) science and Dante’s Inferno in creative ways. It would seem that we are all sinners, which, on second thought, is hardly news. For once, the article is not behind a pay-wall which reminds me of a glaring omission in the piece: there is no mention of the 99 extra circles reserved for predatory publishers.
The US might face unprecedented levels of turnout in tomorrow’s election, but historically, the non-voters are the biggest camp in American politics. One intriguing explanation for this well-known fact is that low turnout could be a consequence of the very high (by any standard) levels of income inequality: because voters lack experience with universalistic institutions, they are less likely to adopt norms and values that foster participation in elections. This is the gist of an article that appeared recently (by social science standards) in the British Journal of Politics and International Relations. While the thesis is interesting enough, I did not find the evidence (design, operationalisation, statistical model) particularly convincing and consequentially embarked on a major replication exercise. As it turned out, there are indeed major problems with the original analysis, including a rather problematic application of the ever popular time-series cross-sectional approach (aka Beck&Katz). Last week, my own article on the (non-)relationship between inequality and turnout has finally appeared in the BJPIR. If you don’t have access to the journal, you can still download the preprint version (“Something Old, Something New, Something Borrowed, Something True?”) from my homepage. And if you in turn find this rather unconvincing, you can download the replication data for the various inequality/turnout models and do your own analysis. Enjoy.
Technorati-Tags: turnout, elections, inequality, tscs, beck and katz, time-series cross-sectional data, replication, data, usa, oecd, social, norms, download, bjpir, bootstrapping
Our project on social (citation and collaboration) networks in British and German political science involves networks with hundreds and thousands of nodes (scientists and articles). At the moment, our data come from the Social Science Citation Index (part of the ISI web of knowledge), and we use a bundle of rather eclectic (erratic?) scripts written in Perl to convert the ISI records into something that programs like Pajek or Stata can read. Some canned solutions (Wos2pajek, network workbench, bibexcel) are available for free, but I was not aware of them when I started this project, did not manage to install them properly, or was not happy with the results. Perl is the Swiss Army Chainsaw (TM) for data pre-processing, incredibly powerful (my scripts are typically less than 50 lines, and I am not an efficient programmer), and every time I want to do something in a slightly different way (i.e. I spot a bug), all I have to do is to change a few lines in the scripts.
After trying a lot of other programs available on the internet, we have chosen Pajek for doing the analyses and producing those intriguing graphs of cliques and inner circles in Political Science. Pajek is closed source but free for non-commercial use and runs on Windows or (via wine) Linux. It is very fast, can (unlike many other programs) easily handle very large networks, produces decent graphs and does many standard analyses. Its user interface may be slightly less than straightforward but I got used to it rather quickly, and it even has basic scripting capacities.
The only thing that is missing is a proper manual, but even this is not really a problem since Pajek’s creators have written a very accessible introduction to social network analysis that doubles up as documentation for the program (order from amazon.co.uk, amazon.com, amazon.de. However, Pajek has been under constant development since the 1990s (!) and has acquired a lot of new features since the book was published. Some of them are documented in an appendix, others are simply listed in the very short document that is the official manual for Pajek. You will want to go through the many presentations which are available via the Pajek wiki.
Of course, there is much more software available, often at no cost. If you do program Java or Python (I don’t), there are several libraries available that look very promising. Amongst the stand-alone programs, visone stands out because it can easily produce very attractive-looking graphs of small networks. Even more software has been developed in the context of other sciences that have an interest in networks (chemistry, biology, engineering etc.)
Here is a rather messy collection of links to sna software. Generally, you will want something that is more systematic and informative. Ines Mergel has recently launched a bid for creating a comprehensive software list on wikipedia. The resulting page on social network analysis software is obviously work in progress but provides very valuable guidance.
In a recent post, I have commented on a (now scrapped) law from the 1930s that made it technically illegal for “foreign” PhDs to use their titles in Germany. A superficially similar case concerns the German citizenship law that was first enacted in 1913 (the Empire happily existed without a concept of federal citizenship for more than four decades) and remained in force with minor amendments until 2000. At the core of this law was the idea that one cannot become German. Rather, one is German by virtue of the bloodline, i.e. by having German forefathers (the original sexist bias of the law was ameliorated in the 1970s). This is the infamous ius sanguinis. However, while the PhD regulations were half-forgotten and rarely enforced (though they provided an income for dubious lawyers), the continuity of the citizenship law after the war was clearly the result of political intent and was even enshrined in article 116 of the constitution.
While the ius sanguinis is archaic, the West German elites had two good reasons for not modernising the law. First, given that Bonn did not accept East Germany’s claim to sovereignty, meddling with the concept of citizenship was obviously dodgy. Second, West Germany considered itself a safe haven for millions of ethnic Germans who were still living in Central and Eastern Europe. Sticking with the traditional concept of citizenship kept the door wide open for these people: like in the case of refugees from East Germany, there was no need to apply for citizenship, because they were already German. Moreover, German citizenship was not exactly in high demand after the war.
One unforeseen consequence of the citizenship law was, however, that children born in Germany by foreigners remained themselves foreigners. By the 1990s, Germany had a sizeable and growing population of several million second (and third) generation foreigners, but thanks to the phenomenal inertia of Germany’s political system and their political persuasions, the Kohl-led governments of the 1980s and 1990s made only token attempts to remedy this situation. The (then new) SPD/Green government, however, came up with some rather radical reform ideas soon after it was elected in 1998. Howard’s article tells the complex and heroic tale of these reforms and the immense political backlash they created. It’s highly recommend for anyone who wants to understand the intricacies of the political battle of citizenship and immigration.