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Racialism is Bogus

The Unwelcome Revival of Race Science is far longer than need be, and carries a certain amount of unnecessary political baggage, but nonetheless, there’s some gold among the dross.

Gist: racial theories are on the rise, particularly among today’s alt-right. To understand why the claims of race theorists are bogus, the author examines the data. A currently popular theory is that Ashkenazi Jews are particularly intelligent; but when tested in the 1920s, the data shows that they were less intelligent than other whites. This article does not mention it, but a prominent eugenicist of that era, Herbert Spencer Jennings, found that the Irish were particularly deficient. Asians of that era, similarly, scored badly on IQ tests.

Much has been made of twin research, but a confounding variable is that adopted twins usually go to families of similar socio-economic status; similar outcomes might be due to similar upbringing. When adopting families are very different in socioeconomic status, the data finds differences in measured IQ.

A most interesting result is the Flynn Effect. IQ tests have to be renormed every decade or so, because each succeeding generation achieves higher scores. By today’s norms, your grandparents had an IQ of only 70. Today’s “racialists” would argue that such morons as their own grandparents were therefore unfit for democracy, and perhaps should have been sterilized.

The entire edifice of ethno-nationalism is based upon shoddy science.

Now, I disagree with the Guardian as to their advocacy of a large welfare state. In particular, it is my belief that today’s schools tend to disadvantage minorities and those of low socioeconomic status; despite spending vast sums on their education, these schools tend to lead to horrible outcomes.

Those of low socioeconommic status who seek their own solutions – by working with their own children, teaching them at home or in co-ops, sending them to charter schools, and otherwise enriching their educational experience – tend to obtain superior results. Hence, I do not trust the political process to uplift those who are at the margins. I advocate educational freedom as in libre, not free as in free beer.

But as to the science, the Guardian and I are on the same page; racialism is a bogus construct, a zombie idea, and the sooner we consign it to oblivion, the better.

You Are Your Own Worst Critic

Over the past forty years of striving to make computers do what I want, I have gained a few hard-won truths. One is that we can be very poor critics of own ideas. We love those ideas; we poured our own blood, sweat and tears into them. Of course they must be right; of course the computer must have misunderstood what we intended to happen.

Well, no. Whether we refer to computer programs, science, politics or economics, when we get stuck, or even when we think everything is going swimmingly, we need to bring in other pairs of eyes to take a fresh look, to spot what we may have blocked ourselves from seeing.

As I write this, Brian Wansink has made the news in a very unfortunate manner; he unwittingly invited people to scrutinize his research and his writings, and the results were not pretty. Now, I must stress that his conclusions might be right; we don’t know one way or the other. What we do know is that he didn’t take care to prove his points; his methods were not up to the task.

Brian Wansink, bless him, is probably a good fellow who was trying to do the right thing. But he admits that he hasn’t kept up with what we now know as the Replication Crisis – the fact that many research papers, especially in the social sciences, cannot be replicated.

I say to anybody in search of the truth: invite criticism. Borrowing from the experiences of those who create and use Open Source Software, open up your data, your methods, your research; your little “tricks” and “kludges” and “smoothing” algorithms. If you had good, solid reasons for your tweaks, they’ll stand the light of scrutiny. As Eric Raymond put it, given enough eyeballs, all bugs are shallow – or perhaps it is better to say that problems are easily solved if you can find the right pair of eyes with the right expertise to examine them. Many people, it seems, assume that they already have sufficient expertise; they hoard their data, their algorithms, their thinking processes, and declare that the “science is settled” rather too easily.