“Scott Alexander” writes,

If ten different factors caused the decline in crime, that would require that ten different things suddenly changed direction, all at the same time in 1994. That’s a pretty big coincidence. . .we should give some credibility penalty to a story with ten factors.

I do not buy this argument. I do not think that one should automatically penalize a study more for claiming that there are ten factors rather than one prominent factor.

My view would be that when there is a lot of causal density, one should be skeptical of any study that claims to have the answer, whether the answer consists of one factor or many. Take as an example the financial crisis of 2008. There are many plausible causal factors. Should we prefer a study that attributes the crisis entirely to one factor rather than a study that attributes it to a combination of factors? I think not. Instead, given the non-experimental nature of the problem, I think we need to accept the fact that we will have to live with some uncertainty about what exactly caused the crisis.

For a phenomenon that is amenable to replicable experiments, it may be possible to obtain evidence against causal density and in favor of an explanation based on one or two factors. But not for something like the drop in crime over the past two decades.

Bryan Caplan writes,

In the GSS, males report an average of 14.19, women an average of 4.76.* If you mean the median, then males report a median of 3, woman a median of 2.

In my statistics course, I use this as a classic example of biased statistics. Here is why I suspect bias.

Suppose that the number of men is M and the number of women is W. Suppose that an omniscient voyeur can count all of the heterosexual relationships. Call this number n. Then the average number of sex partners for men is n/M. For women, it is n/W. Assuming that W and M are about the same, then the omniscient voyeur will know that the averages are about the same. So if the reported averages are different, then the reported averages are biased statistics.

Plomin and Deary write,

(i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence.

Pointer from Kyle Griffin. Read the whole thing. The authors’ discussion of Genome-wide Complex Trait Analysis, a new method of examining genetic influence, was new to me. Deary is the author of Intelligence: A Very Short Introduction, which doubles as an excellent introduction to statistical methods in research.

In my appearance in St. Louis in six weeks, I will be talking about the forces that cause stratification of earnings to accelerate. One of those factors is assortative mating based on g.

The podcast with Russ Roberts is here.

Taleb’s point is that “science” cannot prove that GMO’s are safe. We know that when organisms evolve using a trial-and-error process of gradual tweaking, that process is safe. But direct intervention to create GMO’s is not the same process.

Taleb says.

The big risk is what can happen when you have two things going together–which is, what happens, Soviet style, is a combination of monopoly of some plants over others, that it’s too large a system; and of course creation of other species that will themselves also be too powerful and then you may kill the GMOs or one may kill the other and you may have huge imbalances in nature. And these imbalances in nature can produce large deviations.

I think I get Taleb’s point. But it strikes me that to cause catastrophic harm, a GMO has to be both weird enough to cause unprecedented things to happen but not so weird that it fails to function as a living organism. That may be an impossible combination.