In June 2017 I declared open season on Davide Piffer, inviting criticisms of his findings:
The official response to Piffer is: “publish, and then we will give you our comments in reply.” This will take time, but it is the traditional way of doing things.
The unofficial response is to encourage more criticism right now, because if the finding is the result of a simple error, it should be exposed and corrected as soon as possible.
It is open season on Piffer’s methods. Recruit critics and get them conduct their peer reviews right now.
We are facing a French dilemma: Piffer has an approach to the genetics of racial differences in intelligence which seems to work in practice, but should not work in theory. His technique appears to run against the general trend of genetic research, in that he appears to be getting good results predicting group differences in intelligence on the basis of just 18 SNPs, while genetics researchers are getting only reasonable results in predicting individual intelligence on the basis of lots of SNPs.
For example, people skilled in these matters tell me that they did an out of sample prediction in an independent but European population, and they got 4.8% of the variance, using all SNPs. That is the upper limit of prediction in a non-European population using all SNPs. Pfiffer used just 18 SNPs in non-European populations and his correlation is huge, which does not make sense.
Piffer explained how he was able to achieve his results:
These SNPs that explain variance within populations are markers of polygenic selection. They do not have to explain a lot of variance between populations, or even within populations. The polygenic evolution model predicts that a few SNPs will have frequencies correlated to frequencies of countless other SNPs. I just need to know the few most important SNPs to gather a signal and infer to the distribution of the other unknown SNPs.
If selection pressure acted on these 9 SNPs by driving their frequencies up in population A compared to B, then it has also done the same to other SNPs. We don’t need to know what these other SNPs are because theory predicts that they will have similar distribution.
So, now that the massive James Lee study has been published, where does this leave Piffer’s polygenic evolution model prediction?
By the way, Piffer publishes in the modern sense of that word: he posts up his findings, together with all the code he used to generate his new results, thus allowing all and sundry to see inside the closet, and to check his figures for errors. You can peer review it and tear it apart here:
You can see the results for the 52 populations below:
You can see the results for the major continental groups below:
You can see Piffer’s conclusions and cautions below:
In sum, Piffer has provided a further test of his approach. He cautions that some of the sample sizes are far too small. With any luck this can be dealt with by sampling more widely and in greater numbers. Larger samples may become available with time.
The general pattern is interesting, in that it is broadly in line with the expectations from intelligence testing drawn from country averages, and racial group averages.
Once again, in the spirit of the fearless examination of the intellect, I ask you to subject his work to merciless enquiry and savage criticism. Over to you.