One particularly annoying aspect of doing reviews for learned journals is that assignments tend to arrive in clusters. Six months ago, I found myself in a bit of a pickle, with loads and loads of requests arriving within a short time. And just five weeks ago, another volley of invitations to review hit my mailbox within the space of hours, in one instance within minutes, which looked suspiciously like a flaw in the matrix. As these systems are fully computerised, automated and increasingly urgent reminders are now clustering in my mailbox, too.
As predicted yesterday, the nuclear disaster in Japan is having a profound impact on something as trivial as three state election campaigns in Germany, more than 9000 kilometres away. Roughly 70 per cent of the population believe that an incident on the scale of the Japanese catastrophe could happen in Germany, too. The Federal Government has declared a three-month “moratorium” on its controversial decision to extend the life-span of German nuclear plants, what ever that means. Meanwhile, they want to reconsider their position on the issue and to re-assess the status of the German plants. It makes you wonder if/why they have not assessed those plants in the first place.
It’s amazing: Just 36 hours after the horrible earth quake in Japan, 60000 people are demonstrating in Swabia – against nuclear energy. While we do not know whether the Japanese plants are actually in meltdown, for the German liberal-conservative coalition, this is certainly the Most Credible Accident.
In the olden days, the world was simple. The average extreme right party was strictly socially conservative, to say the least. Abortion and homosexuality were considered sinful, mostly so because both practices deprived the fatherland of future soldiers and potential mothers of even more soldiers. So sex was supposed to be intramarital and had one purpose only: to procreate for the fatherland. Then came Pim Fortuyn and somewhat confused the message, but this was of little concern to members of the German NPD, who sometimes seem to live blissfully in a parallel universe where the 1930s never came to an end.
Recently, the good folks over at the Exzellenzcluster (that’s German new-speak, folks!) Trier invited me over for a talk on our “networks in political science” project (which is not dead, just moving very slowly). Since this is multimedia month, they captured my voice and re-synched it with the presentation. Spooky stuff: all silly jokes, every “errrr” and all my nasty comments on various colleagues near and far are now online forever. Makes you wonder about scientific, technical and social progress. But if you could not be at Trier on this evening, or just cannot get enough of my lovely voice, just click below.
Martin-Quinn Scores : Description – Measuring the relative location of U.S. Supreme Court justices on an ideological continuum allows us to better understand the politics of the high court. In addition, such measures are an important building blocking of statistical models of the Supreme Court, the separation of powers system, and the judicial hierarchy. This website contains the so-called “Martin-Quinn” measures of judicial ideology developed by Andrew D. Martin (Washington University, School of Law) and Kevin M. Quinn (Harvard University, Department of Government)
Data.gov – The purpose of Data.gov is to increase public access to high value, machine readable datasets generated by the Executive Branch of the Federal Government.
CRAN – Package LearnBayes – LearnBayes contains a collection of functions helpful in learning the basic tenets of Bayesian statistical inference. It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms for summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.
Event History Analysis: Statnotes, from North Carolina State University, Public Administration Program – Event history analysis (also called survival analysis, duration analysis, or transition analysis) is an umbrella term for a set of procedures for time series analysis. Coleman (1981: 1) defined event history analysis in terms of three attributes: (1) data units (ex., individuals or organizations) move along a finite series of states; (2) at any time point, changes (events) may occur, not just at certain time points; and (3) factors influencing events are of two types, time-constant and time-dependent. Event history models focus on the hazard function, which has to do with the probabilities that an event will occur after any given duration. Duration to the hazard of death was the classic example in medical research, but the hazard may have a positive meaning also, such as duration until the event of adoption of an innovation in diffusion research.
Professor Jan Box-Steffensmeier Political Science 867 Event History – With reading list and slidesTopic 1: Event History Models: Introduction and Overview Topic 2: Parametric Models Topic 3: Cox’s Proportional Hazards Model Topic 4: Discrete Time Formulations Topic 5: Model Selection Topic 6: Model Selection, Assessment, Specification, & Diagnostic Methods Topic 7: Heterogeneity and Multiple Events
