Smooth

Rose:

“The problem is not that knowledge of such group intelligence differences is too dangerous, but rather that there is no valid knowledge to be found in this area at all. It’s just ideology masquerading as science.”

We make choices every day about the problems we choose to study, and the hypotheses we choose to test. You can’t just pick any question – it needs to be a question for which your inquiry can result in an increase in useful knowledge. In Popper’s language – your hypothesis must by falsifiable in principle, and there is no point doing the work if it’s not falsifiable in practice. In more Bayesian terms, your research ought to be able to adjust your prior belief. Rose argues that in questions of race an intelligence it is simply not possible to do meaningful science. Then there are questions of research ethics and morality.

When you choose to spend your research capital (intellectual and monetary) testing the hypothesis that one ‘racial group’ are less intelligent than another you are supporting prejudice. You are doing this in three ways: by making the question seem civilised; by providing cover for more politically motivated race scientists; by risking producing results that are statistically underpowered or ambiguous such that they can be use to support racism.

I simply can’t see why anyone would touch this kind of research with a ten foot pole.

It’s pie in the sky to expect today’s scientists to construct portable scripts to reproduce not only their results but their publication quality graphics.

Desirable, sure, but completely unrealistic.

There is a world of difference between getting a nice script going to make your work more productive, and being able to reproduce your own work cleanly, to the hard work of polishing that script so that it’s ready for public distribution.

If a compentent coder can reproduce the analysis provided in the paper by following its prescriptions, then surely that is a sufficient standard of reproducibility.

Last time I looked at the software carpentry course, I though it was a nice intro to software eng, but I struggled to see how a working atmospheric scientist would integrate the material into their workflow. Well intentioned, but too scattered to make an impression on most of the scientists I work with.

I’m a computer science guy who spends much time trying to get the atmospheric scientists I work with to use SVN, to help maintain shared libraries, and to standardise on coding styles. And I think the standard of programming in science leaves a lot to be desired. But the arrogrance of many CS types about this issue is equally annoying.

Environmentalists are joyless misanthropists. There is no environmental crisis, well maybe there is but we can solve it with tech. And factories, with workers in them, who the environmentalists hate, because they want everyone to live in caves and only eat fallen fruit.

…

One one level I get it. On another, I don’t. These guys believe more deeply in the creative power of capitalist development than most normal free marketeers. Their philosophical lineage is obvious from their writing, unlike a lot of the left they have not capitulated or tried to absorb green philosophy, in fact their main motivation these days seems to be avoid ‘green contamination’ which makes them look a lot like literate la Rouchies.

It’s all polemic, and its not about the evidence. At least they don’t try to be all ‘I am science’ like many in the OB crowd who have elevated Bayes theorem to a universal philosophy. Not that I’m against bayesian approaches. Hey, maybe when I finish reading about how Jayne’s proposes to build his robot I’ll be a convert. Let’s just say my prior is biased to the skeptical side of probability space.