Michael Eriksson's Blog

A Swede in Germany

Posts Tagged ‘homosexuality

A few thoughts after watching Hjernevask

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A while back, I wrote a post with an excursion on the TV series “Hjernevask”. Having a number of thoughts in my head after watching said series, I wrote most of the below a day or two later, but I never got around to complete it, in particular having several other sub-topics unstarted. As is, I just publish what I have—especially since I want to reference it in the post I started today…

Thoughts on homosexuality:

An often cited problem with the existence of homosexuality is the apparent contradiction of evolutionary principles: Reproduction is not possible between members of the same sex in humans (and a great many other animals, likely including all mammals); ergo, men who like men and women who like women will not have children; ergo, if homosexuality has a genetic background*, it should be a fringe phenomenon.

*This is not a given, even if we see homosexuality as something mainly or entirely congenital. An entirely different line of explanation is then simply that homosexuality has a non-genetic background. Below I will make the “for the sake of argument” assumption that the reasons are genetic (or otherwise inherited by a sufficiently similar mechanism).

This has led to all sorts of speculation and explanation attempts, e.g. that homosexuals could benefit their non-homosexual relatives (who share a considerable amount of genes) in a way that partially outweighs the immediate reproductive disadvantages. This might or might not be true; but is not that convincing because the proper focus of selection is usually the genes themselves and the non-homosexual relatives would still have to share in the “homosexual” genes for this to work out. (While this is by no means impossible, e.g. through some constellation of recessive genes, it requires additional assumptions to be true.)

There is an easier way out, however: What if homosexuals do reproduce in the ordinary manner? My own father, e.g., is a gay man with two children; I am a straight man with no children. (In both cases, that I know of.) In fact, in cultures with a low tolerance for homosexuality, chances are that most homosexuals will lead more or less normal reproductive lives. They will try to fit in, they will marry, they will have children*, and they will pass their genes on. A low-tolerance society is good for homosexuality (but not for homosexuals). In contrast, in a high-tolerance society, like the current, homosexuals will have a far lower probability of having children—it is bad for homosexuality (but not for homosexuals). There is much more evolutionary pressure against homosexuality in the tolerant society.

*It is true that they will be less interested in intercourse with their partners. However, we have to consider factors like the own wish for children (no need for “gay adoption”), the partner’s wish for children, the partner’s wish for sex, and that lack of other release possibilities can make sex with even the “wrong” partner a positive. The latter in particular in cultures that frown upon masturbation.

This applies already for homosexuals. If we widen the field to include bisexuals*, the effect in the low-tolerance society is strengthened; however, it is weakened in the high-tolerance society.

*If homo- and bisexuality do have a genetic background, it would be surprising if they were unrelated.

Thoughts on comparisons and the effects of variation:

A problem with making comparisons is the lack of a common base line, as well as the choice of an unsuitable base line. This is exemplified e.g. by claims that men and women are so similar that it does not make sense to focus on the differences: For some base lines and some purposes this will be true; for others, it will be false. (Cf. also the “math professor” example from the original post.)

If we make a four-way comparison between a male and a female human and a male and a female horse, e.g., we will likely see (although this could depend on what is compared) that the interspecies differences dwarf the intraspecies differences. (Still there will be some aspects of being a male shared by horse and human, but not male and female, and so on.) Add a mollusk and even the human/horse differences seem small. Throw in a rock and they might seem negligible. Why? Because the reasonable base line for the comparison changes.

Still, while a horse and a human may seem similar when compared to a rock, horses and humans are normally seen as living very different lives, having very different capabilities, whatnot. Why? Because when comparing humans and horses in everyday life, the relevant baseline is not the baseline from the comparison with the rock. The observable differences do not arise out of similarities—but out of underlying, genetic* differences. Now, the smaller the differences are, the lesser the effect might be and the fewer areas might be affected. Indeed, the differences between men and women are much smaller than between humans and horses, and their lives, abilities, whatnots, are correspondingly closer.

*The human–horse differences can probably be safely considered genetic; however, quite often the wider set of congenital differences should be considered, including when comparing humans with other humans. (In all fairness, even the human–horse difference could have a non-genetic component, because minor parts of the differences could go back to the uterine environment and gestation process—and in the highly unlikely event that a horse/human could be gestated by a human/horse, then some of these difference might manifest in the wrong species. For species that are considerably closer related, e.g. donkeys and horses, this might be an interesting experiment.)

However, men and women are biologically different, even mentally. Open for discussion is only by how much and how relevant the differences are. It borders on a statistical impossibility that there would not be some difference. Sign two letters, even the one immediately after the other, even using the same pen, same ink, and same type of paper, even while deliberately trying to keep the signature constant, and there will be differences in the result. Likely, they can be seen by the naked eye; if they cannot, a microscope will show plenty of differences. Even the minor differences in input that will still occur, say a minuscule difference in the placing of the hand, a slight hesitation in a stroke, whatnot, will lead to differences in the result. Male and female brains have physiological differences akin to writing on a different day, with different pen, ink, and paper, …—possibly even a different hand. That they would happen to neutralize so perfectly that differences in behavior, abilities, preferences, whatnot, are not obvious is unlikely—that there would be no difference at all, well, that is virtually impossible.

Now take even a small difference and look at what can happen in sub-populations. Imagine a hypothetical type of competition where men have an average result of 100s, women 98s, both (unrealistically) a standard deviation of 10s in an approximate normal distribution and assuming equal amounts of training* (etc.). Gather your colleagues, put them through training, and have a competition: Pick a man and a woman completely at random and the chance of the man or woman placing better is toss up; and whether a man or a woman wins will depend mostly on whether there are more men or women among your colleagues… In stark contrast: What would be the sex of the (non-segregated) Olympic Champion? Very likely a male if a higher time is better; very likely female if a lower time is better. Indeed, chances are that the field would be dominated accordingly. This through a difference of two parts in a hundred in one single aspect (resp. one fifth of a standard deviation, which is mathematically more significant). Let us say that you have to be one in thirty thousand**/*** to make the final. This corresponds to being roughly four standard deviations above the mean. Looking just at women and assuming that a lower time is better, the limit for a final would be 58 (= 98 – 4 x 10). Any man who wants to make that final has to have a score no worse than 58 (but possible better). Now, this corresponds to 4.2 standard deviations (58 = 100 – 4.2 x 10) or roughly one in eighty thousand. In other words, if 240 thousand women compete at this sport, roughly eight would be candidates for the final; among 240 thousand men, only 3. Assuming eight-people finals (as in e.g. the 100m dash), we might have six women and two men. We might have two or three female medalists to one or no male medalists—and the winner is very likely a woman.

*This is of course unrealistic in the real world, or even when looking at the Olympics (cf. the rest of the discussion). It might e.g. be necessary to use a greater standard deviation in the example calculations, which would make the effect smaller—but would not change the principles. When looking e.g. who excels at what profession, we might find a variety of unrelated caused (notably variations on interest and ability), some of which might favour the one sex, some of which might favour the other. It is, however, enough for there to be a net difference to be present in these for a net difference in outcome to result. Of course, depending on how these turn out, they can make the net difference larger than if only one factor had been present, just as they could make it smaller or turn it around.

**In the following some numbers are a mixture of experiments with a statistical package I am unfamiliar with and rough guesstimates. The math could be wrong in detail, but not in a manner that invalidates the principle. For the purposes of demonstrating the effects at extremes, the above should be sufficient. If in doubt, just throw on another standard deviation and any misestimate will be dwarfed.

***Looking at the global population in sports, we have to factor in the many people who do not compete in a given sport, are too old or too young, or might have some other reason for being out of the race. Olympic champions are typically nowhere near one-in-seven-billion. A small sport might have someone as low as one in a few hundred; a large one might conceivably go into one in a few millions. (However, feel free to do calculations based on one in billions—my point will be even clearer.)

A pseudo-paradoxical result of attempts to “even the playing field” is that those factors that are not evened out will be the more important. Now, barring massive interventions, congenital factors cannot be evened out after the fact; while e.g. factors like number of school years can. Consider a situation where men and women are perfectly equal in all rights, responsibilities, opportunities, whatnot. Any variation of outcome will now be explained by one of two things: Congenital factors and coincidence. Looking at sufficiently large samples, the effects of coincidence will even out and disappear—and differences in sample outcome will depend only on congenital factors!

When we look at sufficiently exclusive groups, then, (even small) differences in e.g. ability distribution have a larger effect* on an even playing field than they do on an uneven one. To boot, using the same principles as above, given a sufficiently exclusive group, even very small differences will have an effect. The result is that if it were true that a difference in outcomes was un- or only weakly related to ability in 1917, 1967, or even 1987, it could very well be strongly related in 2017.

*Which is not automatically to say that the differences in outcome are larger. If women are not allowed to run for office, they will not land in office (barring some exceptional scenarios like a woman running for office under a false, male identity). At the same time, in that scenario, no difference in ability distribution, no matter how large or in what direction, between men and women will have any effect on the sex distribution of those successfully elected. Allowing women to run will decrease the difference in outcome—while increasing the importance of the differences.

A somewhat similar mechanism is suggested in Hjernevask: Women (and men) might be more prone to follow their natural inclinations in today’s West than in poorer parts of the world or in the West of earlier days. Because society is more affluent, survival is easier, etc., they have less external restrictions in the form of e.g. lack of money, and they can afford to forego a better paying career in, say, software development, for a worse payed career in nursing or teaching (should they find the latter more interesting). If women do not move into lucrative careers that are open to them, chances are that they have other, natural preferences; ditto, if e.g. Norwegian women stay away from tech and Indian* do not. If and when India grows more affluent, it will be interesting to see whether its women will be more or less interested in tech careers.

*As occurs to me, the proportion of female software developers (in particular) and IT people (in general) with a foreign background has been considerably higher than for male ones in the projects that I have worked in. (With both men and women, Eastern Europe has been the main source.) For instance, out of three women in the IT department of my current client, one was a native (German), one is Romanian (?), and one was Iranian—and at the moment only the Romanian remains. The project before that had one out one being native but likely from the former GDR area (the project was in an “East-German” city, Chemnitz, and most of the team members were “Easterners”); the one before that one out one Eastern European; with similar numbers going back. However, I caution both that the statistical sample could be too small to draw conclusions and that foreigners are by no means rare among the men either.

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Written by michaeleriksson

August 26, 2017 at 7:10 pm