Men and women

[bladespark]

I've been reading some feminist stuff lately, sparked by the recent renewal of discussion about the Gor books. And some random comment, I can't even recall where now, made me think of a way to explain something about gender differences.

Men and women are different. That's fairly evident to anybody with eyes. They're different. The problem is when we take the real differences further than they go. Particularly when we forget that the differences between men and women are smaller than the differences between individuals within one gender. I shall illustrate this point with a simple, easily verified fact comparison. Men are taller than women. This is a fact. Men are taller than women. Nobody disputes this. But let us look at some numbers. The average American male is 5' 9.2" tall. (175.8cm for you metric types.) The average American female is 5' 3.77" (162.5cm) tall. (This is, in fact, almost exactly how tall I am.) So men are, on average, 5.43 inches (13.3cm) taller than women, at least here in the USA. But that's not telling the whole story. The shortest woman who ever lived was Pauline Musters, who stood exactly 2 feet (61cm) tall. The tallest woman was Zeng Jinlian, who was 8' 1.5" (248cm) tall. Thus the variation among women's heights is six feet, 1.5 inches (187cm) or more than fourteen times greater than the height difference between men and women in general.

Now, apply that to all the other statements about the differences between men and women that you hear. Men are better than math. Women are more emotional. Men are stronger. Women are better with children. In all of those cases, the variation between individuals of the same sex dwarfs the variation between sexes.

This is why gender roles tend to be silly. They can make sense if you're only looking at averages, but once you start considering cases, you find they very often just don't apply at all.

Comments

[harliquinnraver.livejournal.com]

They can make sense if you're only looking at averages, but once you start considering cases, you find they very often just don't apply at all.

ah but thats the case with EVERYTHING :)

[aoanla.livejournal.com]

I should note that taking the extremum to extremum range is slightly naughty of you, mathematically; by definition, only one human woman ever has been that small or tall. (The tallest man ever, interestingly, was taller than the tallest woman by a larger margin than the average man is taller than the average woman.)
The standard deviation of human height is between 5 and 6 centimetres, for both men and women, however. Hence, it is true that there is overlap, at around the second standard deviation level, between male and female height within the same culture - this corresponds to roughly 5% of women being taller than the average human male, and roughly 5% of men being smaller than the average human female, which is a notable, but not significant overlap. It is certainly statistically true that, based on this evidence, the statement "men are taller than women" is verifiable, more so than "men are stronger than women", where I believe the standard deviation is much more significant compared to the difference in the means.

[bladespark.livejournal.com]

You appear to have ENTIRELY missed my point.

[aoanla.livejournal.com]

Not at all. You stated:

"The problem is when we take the real differences further than they go. Particularly when we forget that the differences between men and women are smaller than the differences between individuals within one gender."

The accepted statistical measure of variation within a normally distributed statistic is the standard deviation. It turns out that your example, human height, is one where the difference between genders is larger than the standard deviation, by a quite significant degree. The extremum-extremum range , which you used, is almost always a bad measure of variation in a statistic - one freak or sport at either end can distort the measured variation out of all proportion with the actual distribution. In actual fact, if you have a job which requires someone of average male height, or above, then that requirement will be satisfied by more than ten times as many men as women. Similarly, if you have the requirement that you select people of below average female height, you will get ten times as many women as men.

My point, therefore, was that your statement that

"In all of those cases, the variation between individuals of the same sex dwarfs the variation between sexes."

is true on some of the cases you have noted, but (ironically) not in the example you decided to use.

[sparkindarkness.livejournal.com]

Men and women are different - but then so are all people. There are so many differences in the world that you can't pigeon hole people that neatly

[bladespark.livejournal.com]

*rolls eyes* Perhaps I should have laid things out in tiny, excruciating detail.

I mean that you can't judge.

I mean that you never know.

I mean that the intellectual equivalent of Zeng Jinlian could be the female you're condescending to.

I don't give a flying flip about statistics. I am illustrating a POINT and my use of extremes was deliberate.

[aoanla.livejournal.com]

But, of course, you can make reasonable assumptions based upon statistical likelihood. If you assumed that, without seeing them, of two people the male would be taller than the female, you would very rarely be wrong. If you then discovered that the female was the taller, you could adjust to that situation, but it wouldn't make the assumption a silly one.

Of course, you could be wrong, and, without measurement you can't know the value of a statistic for a particular member of a population. But we have generalisations (and, indeed, statistics) for a reason, and retreating to your position of "variation exists in a population, hence you should treat everyone as a special case" is counter to how all humans think, and also counter to reasonable behavior with respect to statistical variables.

If your point is that "in normally distributed variables, the tails are long", then it doesn't need to be made, as that's a clear and self-evident fact.
If your point is "because the tails are long, we can't make reasonable assumptions based on the differences between the means of two normally distributed variables", then you're suggesting that because a rule is right 95% of the time, we shouldn't assume it as a first guess just because of the 5% it fails for. This seems silly.
If your point is "there are always exceptions to a statistical rule, so you should allow for them" then yes, you're right, but this doesn't mean that the statistical rule isn't generally good.

And, of course, I should note that the means for IQ are nigh-identical between men and women (although the standard deviations are different).