cluelessresearch.com

typographic humor

(via daringfireball and Bryan Bell)

The never ending ongoing political reform debate is a never ending source of amusement and befuddlement for anyone with even paltry knowledge about the effects of political institutions. Fernando Rodrigues, for example, claims that the system as it is, which is to say as dysfunctional as it is, is better than most proposed reforms. Although I do not agree with the specifics of his arguments, he is probably correct in the overall assessment.

Case in point, the proposed reforms that the Câmara president, Arlindo Chinaglia, wants to start discussing on the floor in the next week or so. It proposes to change to a closed list proportional electoral system. Comparative scholars everywhere know that such a system is purported to increase the roll call discipline of legislators. The mechanism is simple, legislators that do not behave in accordance to the political party recommendations risk not being placed at or near the top of the list in the next election.

And herein lies is the Brazilian twist: in the proposed reform, legislators running for reelection are placed at the top of the list by default! plus ça change …

Read on for the relevant excerpt from the bill (in Portuguese.)

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Someone I helped this week at work sent me this video. Very funny. I think this is Norwegian, but it is subtitled.

There are a few websites/startup companies trying to fly the idea of being a repository and visualization engine for data that anyone can upload. Swivel, for example, made some splash in the past few months as the “youtube for data”.

I experimented with Swivel and a few others. The main problem with all of them is the lack of tools allowing conditioning, at least in an easy way. Conditioning is important for constructing small multiple plots, or even plotting groups in different colors in scatter plot. For example, take the ideal point data I uploaded:

In order to different parties in different colors I would have (as far as I know) to upload a different dataset for each party! It goes without saying that this is unnecessarily burdensome.

Many Eyes is also very impressive, with more advanced visualization plots. It is java based, and does not play so nicely in firefox at the mac, unfortunately. I also had problems with the ideal points dataset there. It doesn’t allow one to create a scatter plot with only two variables (!!!) requesting a third to be displayed as the size of the symbols.

The focus on bar charts on both platforms is also annoying… dotplots and boxplots would be nice.

There is another site data360, but I didn’t have much luck. It is more “professional”, allowing one to pull data directly from the web automatically. But its focus on time series data makes it simply unusable for the example I tried.

Of course, all three are just beginning and we might be hearing a lot about them soon. And the graphs they make are not half bad. Not until you consider rich chart live, that is. This one is ugly! And I mean, it makes you miss excel kind of ugly:

Last month at Machine Learning there was a discussion about the creation of a machine learning department at Canergie Mellon University. The discussion of the post was fairly interesting, in particular this pearl by John Langford:

I regard ‘rogramming as the missing member of reading, ‘riting, and ‘rithmetic, and I’ve found a statistical understanding of the world genuinely valuable.

I couldn’t agree more. As social scientists, we need a much better training in programming if we are to partake and benefit from the high paced increase in computer power available. The question is, how can we properly train graduate students in the social sciences, who tend to start the program with very little knowledge or interest in programming?

It seems to me that the classes and books available miss badly the mark. They either assume a lot of programming experience (e.g S Programming by Venables and Ripley and Programming with Data by John Chambers) or focus too much on the statistics side of things without a proper discussion of the basic programming concepts.

I am certainly not alone in this assessment. Back in November 2006, Jan de Leew made the following suggestion in the StatCompute mailing list:

This is the title of a series of free computer programming
textbooks, started by Alan Downey. There are versions
for C++, Java, Logo, and Python.
…
Since the LaTeX for these books is also freely available,
it may not be too hard (and possibly quite useful) to
make an R/S version. What seems to be common practice is to edit
the original LaTeX and then add your name to the author list.

But should (most) social scientists learn how to program? This was a topic of an extended discussion at PolMeth . The main argument against it was that we should leave programming to the “pros”, i.e. the programmers at Stata/SAS/R. We perhaps shouldn’t trust computer code written by us plain social scientists. My own take is that a large chunk of data analysis is simply indistinguishable from programming. The problem is that it currently mostly done via a non-reproducible, error prone and downright ugly way. Even the most basic understanding of flow control, loops and data structures will be a quantum leap for most of the current statistical practice, at least in political science.

Therefore, something should be done to cover the gap. Luckily this is not only a problem for us lowly social scientists. Alan Downey, the author of “How to Think Like a Computer Scientist”, is currently finishing up a book on “Physical Modeling in MATLAB” which appears to have the same basic idea, although focused on a “real” science and a different language. It is a “free book” covered by the GNU Free Documentation License, so it is possible to adapt it (or even combine it with part of the “How to Think…” series) in order to make it more applicable to social scientists.

Easy to install bash script by Gunnlaugur Þór Briem.