There are more geniuses among men than among women, and more idiots too

Deary and colleagues (2007) conducted an interesting study on differences in intelligence scores among men and women. In the context of this blog, this study highlights yet one more counterintuitive and intriguing aspect of Darwinian evolution, adding to points previously made in other posts (see here, and here). Evolution may look simple at first glance, but that is a bit of a mirage. In my opinion, to really understand it one has to understand the mathematics underlying it, a lot of which comes from the field of population genetics.

What makes the study by Deary and colleagues (2007) particularly interesting is that its participants were opposite-sex siblings. This helped control for the influence of environmental factors. The downside is that the effect sizes might have been decreased, because of the high gene correlation among siblings, so we could expect larger differences between unrelated groups of men women. The differences, as you will see, are not in overall scores, but in score dispersion.

Let us get straight to the point made by the study. On average, men and women seem to score equally well on intelligence tests. The main difference is that there is more variation in the scores achieved by men than by women, which leads to an interesting effect: there are more geniuses and more idiots among men than among women.

This does NOT mean that a man’s genius is of a higher order; just that there is a tendency for more men to be geniuses (and idiots) than women in any random population sample. The women who are geniuses can be super geniuses, like two-time Nobel Prize winner Marie Curie, the first PERSON to receive such an honor. Albert Einstein is said that have greatly admired her intelligence.

As an illustration of this score dispersion effect, Deary and colleagues (2007) note that: “… for example, in terms of indices of scientific achievement, men were awarded 545 out of the 557 Nobel prizes awarded for science.” On the “idiot” end of the scale: there are a lot more men than women in prison, and one common denominator of prison inmates is that they tend to score very low on intelligence tests. (This is not to say that all criminals have low intelligence; perhaps mostly the ones that get caught do.)

Having said that, it is important to acknowledge that there are multiple types of intelligence, and even multi-indicator intelligence coefficients are usually poor approximations of an overall measure of intelligence (if there is one). This does not invalidate the main point of this post, which is related to score variability.

The table below (from: Deary and colleagues, 2007; click on it to enlarge; full reference at the end of this post) shows scores obtained by men and women (1,292 pairs of opposite-sex siblings) in various subtests of the Armed Services Vocational Aptitude Battery (ASVAB) test.

Note that nearly all of the differences between means (i.e., averages) are significant, but the direction of the differences (captured by the signs of the Cohen’s d coefficients, which are measures of effect size) varies a lot. That is, on several subtests (e.g., “Arithmetic”) men score higher, but in others (e.g., “Numerical operations”) women score higher. It all comes down to men and women scoring equally well overall.

Now look at the columns showing the standard deviations (“SD”) for men and women. In all subtests but two (“Coding speed” and “Numerical operations”) the standard deviation is higher for men; in many cases significantly higher (e.g., 44 percent higher for “Mechanical comprehension”). The standard deviations are about the same for “Coding speed” and “Numerical operations”. What this means is that variability in scores is nearly always higher, often significantly higher, among men than among women. I prepared the schematic figure below to illustrate the effect that this has on the numbers of individuals at the extremes.

The figure above shows two (badly drawn) quasi-normal distributions of scores. (This post shows a better illustration of a normal distribution.) The red curve refers to a distribution with a lower standard deviation than the blue curve; the latter is flatter. Each point on a curve reflects the number of individuals obtaining a particular score, which would be indicated on the horizontal axis. The number of individuals with that score is on the vertical axis. As you can see, the numbers of individuals scoring very high and low (geniuses and idiots, if the scores reflected intelligence) are greater for the blue curve, which is the curve with the higher standard deviation (higher dispersion of scores). The farther one goes to the left or right (the extremes), the bigger this difference becomes.

What does this have to do with evolution?

Well, there are a few possibilities, two of which appear to be particularly compelling. Maybe this effect is due to a combination of these two.

One is that ancestral women, like women today, selected mating partners based on a wide range of traits. Ancestral men on the other hand, like modern men, focused on a much smaller set of traits (Buss, 1995). The end result is more variation in traits, generally speaking, among men than among women. This refers to traits in general, not only intelligence. For example, there seems to be more variation in height among men than among women.

The other possible explanation is that, in our ancestral past, staying out of the extremes of intelligence was associated with higher survival success in both sexes. It seems that the incidence of certain types of mental disease (e.g., schizophrenia) is quite high among geniuses. This leads to more deaths due to related issues – suicide, depression leading to the metabolic syndrome, etc. And this is today, where geniuses can find many opportunities to “shine” in our complex urban societies. In our ancestral past the cognitive demands would have been much lower, and so would the practical value of being a genius.

If staying out of the extremes has indeed enhanced survival success in our evolutionary past, then it is reasonable to expect more women to fit that pattern than men. As with almost any “thing” that enhances survival success, women (especially pre-menopausal) naturally have more of that “thing” than men (e.g., HDL cholesterol).

The reason is that women are more important for the survival of any population than men; today and 1 million years ago. A population of 99 women and 1 man can potentially generate 99 children every few years. Here inbreeding in subsequent generations will be a problem, but that is better than extinction. A population with 99 women and 99 men (or even 1,000 men) will not generate significantly more children.

Reference:

Buss, D.M. (2003). The evolution of desire: Strategies of human mating. New York, NY: Basic Books.

Deary, I.J., Irwing, P., Der, G., & Bates, T.C. (2007). Brother–sister differences in the g factor in intelligence: Analysis of full, opposite-sex siblings from the NLSY1979. Intelligence, 35(5), 451-456.

Lucy was a vegetarian and sapiens an omnivore: Plant foods as natural supplements

Early hominid ancestors like the Australopithecines (e.g., Lucy) were likely strict vegetarians. Meat consumption seems to have occurred at least occasionally among Homo habilis, with more widespread consumption among Homo erectus, and Homo sapiens (i.e., us).

The figure below (from: becominghuman.org; click on it to enlarge) shows a depiction of the human lineage, according to a widely accepted theory developed by Ian Tattersall. As you can see, Neanderthals are on a different branch, and are not believed to have been part of the human lineage.

Does the clear move toward increased meat consumption mean that a meat-only diet is optimal for you?

The answer is “perhaps”; especially if your ancestors were Inuit and you retained their genetic adaptations.

Food specialization tends to increase the chances of extinction of a species, because changes in the environment may lead to the elimination of a single food source, or a limited set of food sources. On a scale from highly specialized to omnivorous, evolution should generally favor adaptations toward the omnivorous end of the scale.

Meat, which naturally comes together with fat, has the advantage of being an energy-dense food. Given this advantage, it is possible that the human species evolved to be exclusively meat eaters, with consumption of plant foods being mostly optional. But this goes somewhat against what we know about evolution.

Consumption of plant matter AND meat – that is, being an omnivore – leads to certain digestive tract adaptations, which would not be present if they were not absolutely necessary. Those adaptations are too costly to be retained without a good reason.

The digestive tract of pure carnivores is usually shorter than that of omnivores. Growing a longer digestive tract and keeping it healthy during a lifetime is a costly proposition.

Let us assume that an ancient human group migrated to a geographical area that forced them to adhere to a particular type of diet, like the ancient Inuit. They would probably have evolved adaptations to that diet. This evolution would not have taken millions of years to occur; it might have taken place in as little as 396 years, if not less.

In spite of divergent adaptations that might have occurred relatively recently (i.e., in the last 100,000 years, after the emergence of our species), among the Inuit for instance, we likely have also species-wide adaptations that make an omnivorous diet generally optimal for most of us.

Meat appears to have many health-promoting and a few unhealthy properties. Plant foods have many health-promoting properties, and thus may act like “natural supplements” to a largely meat-based diet. As Biesalski (2002) put it as part of a discussion of meat and cancer:

“… meat consists of a few, not clearly defined cancer-promoting and a lot of cancer-protecting factors. The latter can be optimized by a diet containing fruit and vegetables, which contain hundreds of more or less proven bioactive constituents, many of them showing antioxidative and anticarcinogenic effects in vitro.”

Reference:

Biesalski, H.K. (2002). Meat and cancer: Meat as a component of a healthy diet. European Journal of Clinical Nutrition, 56(1), S2-S11.