It has become fashionable in certain intellectual circles to regard the inadmissibility of racism and sexism as a mere PR problem stemming from the (arbitrary) outcome of World War II. So, we see a re-branding of these ideas as HBD (Human Bio-Diversity) which is supposed to ring all the right PC bells on the level of sound-bites, yet bring back the "good old times" of "racial realism" and "gender realism". In this article, I would argue that racism and sexism are still wrong. Both are based on a mathematical fallacy and thus following their advice is predictably perilous. You confuse …That i…The outcome of World War II was not arbitrary at all.
First, let us take a good hard look at the bell curvebell?? Why n…For PR…, one that describes the distribution of a characteristic that emerges from the contribution of a sufficiently large number of sufficiently independent additives. Omitting all the constants, the formula is y = exp(-x²). Or, perhaps even more expressively y = 1 / exp(x²). It is the reciprocal value of an exponential of a square function. In qualitative terms, it is the reciprocal value of something that increases very-very fast. Much faster, than the functions an untrained intuition is well-equipped to handle. Example:
exp…In other words, the bell curve behaves very differently near the average and far from it. This unusual nature of normal distributions is what leads to the fallacies underpinning racism and sexism, as we shall see.
Let us introduce two more parameters into the equation (while still omitting scale constants for the sake of clarity and brevity): mean (denoted by μ) and standard deviation (denoted by σ). In plain English, μ moves the bell curve left and right, σ makes it fatter or thinner. The equation becomes y = 1 / exp[([x - μ] / σ)²].
Many genetically influenced traits exhibit a larger standard deviation in men than in women. There are numerous reasons for this, but let us just accept it as fact for now. Similarly, the means of genetically-influenced traits are slightly different between different races and ethnic groups. This and the above-mentioned unintuitive properties of normal distributions lead to some surprising consequences and their incorrect interpretations.Graphic Illu…
Suppose, there is some genetically influenced trait I and some ethnic group J, whose mean I is very slightly higher than that of other ethnic groups. Because of the way bell curves are, the further up you move in I the larger the proportion of Js becomes relative to others. Even if the absolute number of Js is fairly small, far from the average the proportion of Js will be surprisingly large and the people with the highest I are very-very likely to be why not give…For tw…Js. Does that mean that ethnicity J is a good predictor of trait I? Hell, no!
In particular, if you seek a partner (or employee, or boss) with high But if you o…Well, …Basi…I, you do yourself a huge disservice by restricting your search to ethnic Js: the vast majority of Js has an I well below the level where the proportion of Js becomes visibly larger than that of their proportion unconditional on I. Moreover, the average I of the best J you can find will be much loweragain, could…There … than the average I of the best person you can find. Even if there is a high probability that the best person you can find happens to be JBut your mai…Well, ….
While I is a surprisingly good predictor of J, J is a very poor predictor of I. Poor to the point of irrelevance. The policy of using it as such is actually very-very counter-productive. If you recruit your warriors exclusively from the race or ethnic group from which most of the best come, expect to be defeated.
With gender, the story is very similar. Extremes on genetically-influenced traits are very likely to be men. But giving preferential treatment to men when selecting people for roles demanding extreme ability is a bad policy. There will be fewer women among those, who fit the bill, but the best person you can find will be, on average, much better than the best man you can find.No, usually …Much b…Usua…