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March 28, 2016 - Jordan B. Peterson Podcast
01:13:50
2016 Personality Lecture 12: Gender Differences: Agreeableness and other traits: the Science
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All right On to another trait.
So, we talked about extroversion and neuroticism, and I basically laid out a case for you that extroverted people were more sensitive to incentive reward, and people who are high in neuroticism were more sensitive to anxiety and to emotional pain.
And that there are fundamental biological subsystems associated with those dimensions.
And that it's not a single dimension, which is also, you know, a very important thing to note, because people tend to think of happy as the opposite of sad, you know, and it's not.
It's not.
Because you can be happy or not happy, and you can be sad or not sad, and I suppose if you're really sad, you're not happy and sad at the same time, right?
So that would mean that you'd be an introvert or somebody who's high on neuroticism and high on introversion.
You know, you're not very enthusiastic under those circumstances and you're quite sensitive to negative emotion.
So, and...
Well, that's just how it goes.
And now, you know, the traits...
You might think that in some sense you could score high on a trait and low on a trait and that maybe high would be better than low.
It's very, very complicated.
I mean, basically what you have to assume is that the traits are not normally distributed—I think I have a normal distribution here—you know, so that there's an average, most people cluster around the average, and then there's, you know, increasingly few people as you move farther and farther to the extremes.
Well, the reason that there's a normal distribution is because there are adaptive advantages—speaking from a biological perspective—there are adaptive advantages to every position on that distribution.
So you might say, well, what's the use of being extremely anxious and easily hurt?
And the answer to that might be, well, it's complicated.
But some potential answers might be, well, it's not clear how sensitive you should be to distress if you're going to be a good caretaker of small infants, for example.
And I think that that's a relevant issue because women tend to be higher in trait neuroticism than men.
It's about half a standard deviation.
That occurs, interestingly enough, pretty much right at puberty.
So if you look at boys and girls before puberty, there's not much difference in sensitivity to negative emotion.
There seems to be a hormonal transformation.
And, you know, we don't know exactly why that is, although we do know that it manifests itself in a couple of different ways.
First, it never goes away after that.
So women and men never equalize again in terms of their sensitivity to negative emotion.
Second, it's true cross-culturally pretty much wherever you look.
And we'll talk about the cross-cultural findings a little bit in more detail today because they're quite interesting.
And third, it's also in keeping with the clinical findings that women are much more susceptible to both depression and anxiety from a clinical perspective.
So maybe three to four times as susceptible.
It depends on how you measure it, obviously.
But, you know, there's a lot of converging evidence that suggests that.
And then, well, it's not the only gender differences.
The other big gender difference is in agreeableness, and that's the trait we're going to talk about today.
Agreeableness is a tricky trait.
It's not that easy to figure out, because it overlaps to some degree with what you might think about extroversion.
Like, extroverts are enthusiastic and assertive, but they're also really social, right?
They're gregarious, and they like to be around people, and they like to tell jokes.
And you might even think of them as friendly, in that if you meet an extrovert, they're going to make friends with you pretty quickly, or they're going to try, or they're going to try to charm you at least, or try to amuse you at least.
And then you think, well, agreeableness is compassion and politeness.
So how does that exactly differ from friendliness?
And the answer is, well, warm, compassionate, or compassionate, empathic people care about you.
Whereas the extrovert doesn't necessarily care about you.
I mean, they're interested in being around you.
That's not the same thing as caring for you.
You know, like you could be interested in being around dogs to play with them, let's say, but that doesn't necessarily mean that you'd have any interest in caring for them.
And so agreeableness looks like a caring dimension.
And I think the right way to think about it seems to me to be something like this.
Imagine that during your life you engage in a sequence of reciprocal trades or reciprocal interactions.
Okay, and you might say, well, how often should you give and how often should you take?
And roughly speaking, it should be 50-50, right?
And hopefully, the consequence of that is each person gains more, in fact, than they would if they were just working in isolation, so it's a really good deal.
But I would say, roughly speaking, that as you become more agreeable, It's more like 60-40 for the other person, or 70-30 for the other person, or 80-20.
And then as you become more disagreeable, it's the other way around.
It's 60% for me and 40% for you, and so forth.
So one tails off into extreme selfishness, and the other tails off into extreme self-sacrifice.
And too much selfishness puts you in prison, and too much self-sacrifice, well, That's more complicated.
I would say that part of the pathology that Freud identified as characteristic of the Oedipal family is actually a consequence of too much agreeableness.
It's sort of the Hansel and Gretel story.
You know, you all know the Hansel and Gretel story?
Hansel and Gretel have their two little kids, and I think their mother gets remarried, or their father, I think it's their mother, but I don't remember.
And anyways, the step-parent decides that the kids are kind of a pain, and that She or he convinces the alternate partner to take them out in the forest and just abandon them.
They make their way back once, but then they take them deeper into the woods the second time.
Anyway, so they're wandering out.
They're all lost in the woods, right?
Which is a kind of a symbolic descent into chaos, right?
And they find a gingerbread house.
And, you know, that's a pretty good deal when you're a little kid and you're lost and cold and it's dark.
It's such a good deal that you might be a little suspicious of it, because not only is it a house, which is right on, but it's a house made out of cookies, you know.
And inside there's an old woman who wants to fatten up the kids and eat them.
And, you know, they eventually manage to fool her and push her in an oven.
It's quite a bloodthirsty story, like a lot of these fairy tales are.
There's a really profound moral in it, and the profound moral is something like, beware of someone who does too much for you.
Because there's a devouring element to that, you know?
And this is why, look, most of the time when you hear people talk about things like compassion and empathy and, you know, and politeness and that sort of thing, they're treated as if they're untrammeled virtues, and that's a mistake.
It's a mistake.
Agreelness is a weird trait, because there are marked advantages and disadvantages to people all along the distribution.
So, you know, disagreeable people, they're blunt, so that would be the impolite element, and they don't shy away from conflict.
And you might think, well that doesn't sound very good, but that's not right.
Lots of times, especially if you're trying to solve hard problems, you want to have people around you who are blunt and somewhat Unafraid of conflict, because very frequently there isn't any difference between thinking about something and having conflict.
You know, so if you're really committed to an idea—and I'm committed to an idea—we're either going to act it out mutually and actually engage in either competition or direct, you know, combat, roughly speaking, or we're going to hash it out so that we can exist harmoniously as we move into the future.
And the problem with avoiding conflict is that Conflict's inevitable.
Like, because sometimes, A, you don't know what to do, and it's a really complicated situation.
You know, so you have one position on it, maybe your partner has another position.
Both positions are justifiable, say, with regards to disciplining children, because that's one—or with finances.
Those are common points of contradiction between couples.
It's like, it's not obvious who's right.
So how do you figure it out?
Well, you either push each other around, Physically, or you push each other around mentally, which I think is maybe even worse over the long run, or you hit the problem straight on and address it, and then there's conflict.
But maybe, if you're fortunate, you get through the conflict and you figure out the problem, and then you can have peace.
So the downside to agreeableness, as far as I can tell, is that it's over-concerned with the establishment or the maintenance of peace in the present.
And under-concerned with the establishment of peace in the future.
And I think that's what conscientiousness does instead.
So my idea, and I have no idea if this is correct, by the way, so I'm moving out towards the fringes of knowledge on personality, but I think what happened, it's hard to get conscientiousness out of animals.
You know, like most things you can develop an animal model for, right?
Conscientiousness, that's a tough one.
We haven't been able to come up with a reasonable animal model, or a neuropsychological model, or a psychopharmacological model, or a theoretical model, or a cognitive model.
Like, the things we don't know about conscientiousness are manifold.
But anyways, I think what's happened is that agreeableness is a good Heuristic for establishing harmonious egalitarianism in very small groups.
So, you know, if you're in a family, and you have parents, because generally if you're in a family you do, you know, one of the concerns about the parents is that resources are fairly distributed.
You know, and generally parents are loath to really produce much of a dominance hierarchy in terms of affection in relationship to their children, right?
It seems kind of like a violation of the parental contract.
So, but then the question is what happens when you enter into bigger organizations where familial ties Either can't be maintained merely because of the size of the organization, or because the organization is just too complex to be run that way.
I think that's when conscientiousness kicks in, and conscientiousness is more of a cold virtue.
It's not exactly based, as far as we can tell, it's not based in any social emotion.
It's more like, here are the articulated rules whereby the social organization functions, I'm going to adhere to those and follow them, and that's what makes me conscientious.
Now, there's an orderly part, and that would be absence of rule-breaking and keeping things in their proper position.
And then there's an industriousness element, which also seems to have something to do with keeping social norms, like although there's an element of going for the ideal instead of just not breaking rules in industriousness.
Conservative people are more conscientious than liberal people, and that kind of makes sense, right, because conscientiousness is concerned with the maintenance of current social rules and then playing the game according to the rules.
Liberals are higher in openness and lower in conscientiousness, so they're more likely to transform the rules, which is something conservatives don't really like because they're doing fine playing the current game, you know, and there's some real utility in maintaining the current game because if it's too unstable then Well, then you have a descent into chaos, and that's not good for anybody.
Okay, so back to agreeableness.
Now, so the big difference between men and women in terms of traits seems to be—so you could put—first of all, I should show you—let's see if I've got this here.
Yeah.
So there's two overlapping normal distributions, okay?
And the blue ones are women and the red ones are men.
And the blue is agreeableness.
Like, the blue is shifted over to the more agreeable side and the red is shifted over to the less agreeable side.
The first thing that you should notice about that isn't that the differences exist.
The first thing that you should notice is that almost all of the territory is overlapped.
And so what that means is that if you took men and women—if you drew men and women randomly from the population, there'd be a deviation from 50-50 with regards to who was the most agreeable individual.
But at least—now, let's see if I can get this right.
I probably can't because I don't remember exactly the effect size.
It's probably about.2.
Maybe it'd be 60% probability that you draw out a woman who was as more agreeable, and 40% probability that you draw out a man, you know, as a deviation from 50-50.
So there's lots of women who are more disagreeable than men, and there are lots of men who are more agreeable than the typical woman.
But there are differences, and one of the things that's really worth noting when you look at a normal distribution, because this is where things get weird, So you could say there's not that much difference on average between men and women, but the thing is the average is often not the relevant issue.
The relevant issue is often the extreme.
So, for example, if you're going to imprison people—so look at that red curve—what you see is that if you—although it's not drawn exactly perfectly—but what you would see if the curve was proper here Is that once you were out here, say, where you're only interested in the one out of fifty most disagreeable person, all those people would be men.
And that's partly why almost everybody in prison is male.
Because you don't put people in prison unless they're very extreme, and one of the things criminals tend to be extreme in is they're low in agreeableness.
Surprise, surprise.
They're kind of callous.
They're in it for themselves.
You know, they're stubborn.
They don't care about you one way or another.
And if they're low in agreeableness and in conscientiousness, then they don't care about you and they aren't going to play by the rules.
That's starting to touch on psychopathy.
So you can model psychopathy pretty well with the big five.
Low agreeableness, low conscientiousness.
So then you get someone who could care less about you, who lies all the time, or who doesn't follow the rules, who won't work, so they have a parasitical lifestyle, which is actually one of the dimensions of psychopathy.
A parasitical lifestyle.
Yeah, and then if you look over on the other direction and you took the one in fifty person who was the most compassionate, then that would be—virtually all those people would be women.
So, oh, I've got it there.
Its probability is 63%.
So it's 63% chance that the woman you drew out would be more agreeable, and 37% chance that the man would be.
So, you can convert most effect size statistics into odds ratios like that, and I'll actually tell you about how to do that later.
It's quite cool, and it really gives you a much bigger understanding of what an effect means.
Like, one of the things you won't be taught about properly, in all likelihood, when you take your statistics, although it might have changed, is that They won't tell you how to interpret the size of an effect, and really the only thing that matters is how big is the effect, right?
And that would be, in most studies, that would be The size of the effect would be the distance between one of those peaks and the other.
That's how much the groups differ.
And then of course the groups differ but the spread of the people within the groups differ as well.
So the statistical calculation takes into account how big the mean difference is while correcting for the spread of the numbers around that mean.
And so you need to know how big that effect is and you need to be able to understand that in a way that's visualizable.
For example, you might have a correlation coefficient of.2.
So what you'd imagine, imagine a graph like this, and then a bunch of dots, and then a line running through them.
At.2 there's a lot of dots that aren't on the line, because it's only accounting for 4% of the variance, right, because you square it to get proportion to the variance.
So.2 there's some relationship but not much, there's an awful lot of scatter.
So the two variables are related.
If you have an R of 0.2, you can calculate an odds ratio.
It turns out to be 60-40.
Because the R is the difference between The probability of drawing out a member of one group characterized by that particular feature compared to the member of the other group.
So you've got to have an at-hand way of understanding these effect sizes because otherwise you can't understand psychological papers.
Like, what's a correlation of point one?
What's that good for?
What's a correlation of point two?
A correlation of point three?
And it's very, very tricky because There are people who've made sort of tables of whether or not you should consider an effect size large, medium, or small, but it was basically a guess, just like the.05 level of significance was an arbitrary, somewhat arbitrary decision.
Now, one of the things you'll find is that in psychology you rarely see two variables that are related to one another more than.3.
Okay, you need to know that, because if you don't know that, you have no idea what to make of a given phenomenon.
So, for example—and it's tricky—so, for example, an optimized combination of IQ and conscientiousness can predict your job performance at somewhere between 0.5 and 0.6.
So, now, if you square that, that's 25 to 36% of the variance, and you think, well that's not very much, it's only a quarter of the variance in job performance.
But, it's hard to measure job performance, so there's lots of error in it, and there's error in the measurement of conscientiousness, so some of that's just noise.
But, importantly, even if it's 25% of the variance, so we set a correlation of 0.5, then you could use it to raise the probability that you'd pick of an above average employee From 50-50 to 75-25.
Because 75 minus 25 is.50.
So it's a big effect, and then the economic consequences of that are massive because it turns out, you know, if you're very good at what you do and you're not very good at it, I might say, well how much more is it to my advantage to employ you rather than you?
And one of the questions would be, well how much difference in performance is there between people?
Like if everyone lines up, like maybe it's an assembly line job, and once you get it, Once you're trained, everyone has exactly the same rate of production.
Well then it doesn't matter if you have a higher IQ and you're more conscientious, because there's no variability in the performance, but in lots of jobs there's massive variability.
It might even be non-linear, and we'll talk about that when we get to our discussion of the Pareto distribution.
So, what that means is that some people are not only not productive in their job, they're negatively productive in a big way.
You hire them and they take money out of the company.
So this often happens, for example, if you hire incompetent managers, because not only are they not doing their job, they're stopping twenty other people from doing their job while they're, you know, eating resources like mad doing that.
So it can be a real catastrophe.
So a bad hire If someone's making $100,000 a year, a bad hire costs the company about $350,000.
So you don't need many of those before, especially if you're a small company, before you're just done.
So, and the distribution between people in terms of performance varies with job, but with some jobs it's tremendous, like in sales.
You know, so in sales you really see a Pareto distribution where almost everyone is making no sales and then there's a few people at the end of the distribution who are doing all of it.
So, and, you know, there's lots of jobs that are like that.
They're not normally, production isn't normally distributed.
So, alright, so anyways, back to the aggression, or agreeableness here.
So most of the time, most of the time, what you'll see in psychology is that the statistical assumption that's made in a paper when they're comparing Two groups, you know, is one group significantly different than the other?
The statistics are predicated on the assumption that the distribution of those scores is normal.
And what you'll hear psychologists telling you is this central limit theorem, which is, this theorem says that if a random variable x is the sum of a large number of small and independent random variables, then almost no matter how the small variables are distributed, X will approximately be normally distributed.
Well, you think, if you take human traits like, let's say, intelligence for that matter, God only knows how many random genetic factors that could have been one way or another have to sum up to cause, you know, to produce the To influence the intellectual capacity of one person, and then to produce that amount of variation.
It's a lot of random things, and so what happens is it comes out basically normally distributed.
But some things aren't randomly distributed, and production seems to be one of them.
And success seems to be another, which is why, you know, 1% of the people have 50% of the money, because what happens is, well, if you're smart and you work hard, then you multiply how smart you are, right?
But then it starts to accrue to you.
You know, so if you have $100,000 in the bank and it's making, say, 5% a year, you make quite a bit of money just because you already have the money.
So having the money puts you in the game like it does if you're in the real estate market.
And once you start to become successful at something, well then, people expect you to be successful, and they open up more doors to you, and your network of influence widens, and so you have more opportunities, and then people come to you, and so what happens is that as you start to become successful, the probability that you're going to become increasingly successful increases.
And so you can get into an exponential rate of return, which is exactly what you want to have happen if you start a startup, right?
You don't want linear growth, you'll just die.
You want it to go viral.
And most things don't, but the things that do are super successful.
People go viral during their lifetime, especially if they're engaged in some kind of creative, in some sort of creative enterprise.
And making money actually turns out to be From the entrepreneurial perspective anyways, essentially a creative enterprise.
It's not that surprising.
Now, one of the things that no one will probably ever show you is why things are normally distributed and what exactly that means.
And so I'm going to show you something.
Maybe I even have a saved video of it, which would be smart, but unlikely.
Thank you.
Sorry, I should have had this, but I forgot about it until now.
Well, we'll just look on YouTube.
And that should do the trick.
Galton.
Maybe that's a good one.
Galton.
What you do is you take
a ball, you drop it into the top, and it bounces off all these nails before eventually going into one of these categories.
And when the ball hits, it is a...
This is a Galton board, because the first person to make one of these and name it after himself was called Galton.
And what you do is you take a ball, you drop it into the top, and it bounces off all these nails before eventually going into one of these categories.
And when the ball hits each nail, in theory, There is a 50-50 chance of it going left or right.
So each path is pretty much unpredictable.
If I was to take two balls and put them in, even if I try and put them in exactly the same, they will end up in completely different positions.
We cannot accurately predict where any given ball will go.
However, we can make a few statements.
We can say that a ball is more likely to end up in the middle than the edge because these centre categories, there are lots of different paths that end up here.
There are only a few paths that end up on the edge.
So what we can do is take this piece of scientific equipment to the top and start putting these in by a handful.
If we put in absolutely loads of these balls, Okay,
so now imagine, when you're looking at mean differences between groups, that's in some sense analogous to asking if all the balls have fallen into a pattern because there's one entry point or two.
Right?
And you might say, well, what's the difference between one and two?
Because maybe one entry point is here and one entry point is here.
Is that the same?
Or maybe they're here.
You know, so there's a continuum of same and different.
You can calculate the probability that a distribution is a single distribution from a single point, which would be there's no mean differences, or that it's from two different points, which would be a mean difference between the groups.
So you get a curve like this and a curve like this, then you can do a statistical calculation that would tell you what the probability of that shape emerging merely from chance would be.
And what we've picked in psychology, in many sciences, is this.
If there's less than a 1 in 20 chance that the shape of the distribution is by chance, then you can infer that there's a significant difference between the two groups.
Because you could have a pattern like that emerge in this experiment just out of chance.
In fact, if you see the one that's on the board there right now, you see there's two peaks in it.
You might say, well, those are the peaks of two different populations.
It's very unlikely.
How you calculate whether the difference between those two peaks is significant from a statistical perspective is partly based on chance, right?
It's just the probability that that distribution would manifest itself spontaneously.
But it's also affected by how many balls you drop down.
And the reason for that is that if you only drop down one ball, Do you have a normal distribution?
Well, maybe, but you can't tell because there's only one ball.
And maybe you drop ten down and, well, you're going to get something that maybe is patchy and maybe has one or two places where there's two balls stacked, but still not much of a normal distribution.
But if you drop 150,000 of them down here, It's going to be virtually perfect.
And so basically what happens is that the statistics infer, or based on the presupposition, that the more subjects you have in the experiment, the better the shape of the normal distribution, which would be the tighter the approximation of the sample To the underlying population, to the actual population, and the less difference you have to have between the groups in terms of magnitude for that to not be a consequence of chance.
Okay, so you need to know three things when you're interpreting the straightforward statistics that have to do with group differences in psychology experiments.
You need to know, number one, how big the sample is.
Because the bigger the sample, the smaller the effect will be significant.
You need to know how significant the effect is, that's the probability, and you need to know how big the effect is, that's the effect size.
And you can't know one of those things without knowing all three of them, so when you're interpreting an experiment you always need to know effect size, The probability that that effect size is due to chance, and how many subjects there are in the experiment.
Okay?
Because those things are related and you can't interpret one of them in the absence of the other.
Okay, so.
And I'll show you.
I should show you this Pareto distribution.
Maybe I can find this.
I might as well show it to you now.
Pareto distribution.
What's it called?
Animation.
Maybe it'll show up.
That would be lovely.
Now let's see.
I haven't looked at this one.
No, that's not it.
Nothing like an audio-only video.
Okay.
Let's see.
Psychophysics.
Animation.
Yeah, I can't find it.
So I'll just tell you about it instead.
It'll work, alright.
So you play in Monopoly.
Okay.
Monopoly is an interesting game, to some degree.
But one of the rules in Monopoly is that there's a finite number of properties and a finite amount of money.
Okay, so that's an important feature.
Because what that means is that there's going to be winners and losers if you play the game long enough.
Okay, that's what it absolutely entails.
Now, you know, economists argue about whether or not the economy is a zero-sum game, where there has to be winners and losers, or whether it's a more infinite game because the amount of money continually increases, right?
So, you know, if the amount of money continually increases, it's not obvious that anybody has to be poor.
Okay, so here's what happens in the monopoly.
So first of all, you all start out with the same amount of money, right?
So that's fair.
Okay, and then what do you do?
You shake dice.
And you make some decisions.
And so, it's not a bad model for life.
The dice shaking is the random element.
And, you know, what happens to you in your life is going to be a reasonable chunk of random.
You know, I mean, because you can be struck by illnesses or a family member can.
You know, there's arbitrary things that are going to happen to you.
You need to know that, because you have to think when something bad happens to you about whether or not that was just random or whether you caused it.
And, you know, It's kind of horrible to think that it's random, because then you can't control it.
But on the other hand, it also means that sometimes when you fall down, it's actually not your fault.
It just happened.
And so you need to know that.
Randomness has a fair—like, it's a non-trivial contribution to people's life course.
Okay, so the dice represent the randomness.
Now, and then you make decisions about what you're going to do with your opportunities.
And, you know, I think if you took 20 people— And they had different levels of experience and expertise with Monopoly.
My suspicions are, is that there are better players and that they would win more often if you, you know, played them across time.
That it's not purely a random game.
Although maybe it is.
So anyways, what happens is, you basically start trading, right?
You trade with the bank, you trade with the board, and you trade with other players.
And so, and you do that randomly.
And what happens is that with each trade, someone gains a bit more and someone loses a bit more.
But something else happens, which is, as you gain more, your options increase, and as you lose more, your options decrease.
Right?
So by the time you're down to, you know, a thousand dollars and three properties, and it's three quarters of the way through the game, you know you're in a hole in your heart—it's very unlikely that you're going to climb out of it, because one little negative event will take you out of the game.
Now, you know, there's some trivial probability that you'll get back into it, but everyone knows that sinking feeling that occurs when you're just more or less baggage on the game, you know?
But what happens to the other people is that one of them starts to pull out way ahead, and what happens as you continue to run the game, we'll say for the moment, merely as a consequence of chance, someone will end up with all the money and all the properties.
Now, like, the importance of that can't be overstated.
That's a non-normal distribution.
And although you won't hear about this in psychology ever, I didn't understand this until like five years ago, which is absolutely pathetic.
Maybe it's ten years ago now.
But, because I was under the assumption that almost everything that psychologists studied that was important was normally distributed.
That's wrong.
Lots of things are distributed in a Pareto distribution.
And that's—I think what happens is that You get feedback loops developing.
You know, as you fall, the probability that you're going to fall increases because you're not as resilient and because things can take you out faster.
You know, you start to get poorer, well then you don't eat quite as well.
You're rushed off your feet more, so you're sick more often.
Then your income falls.
Then you have to—you're either under severe financial stress, or you have to move to a poorer neighborhood, and then if you move to a poorer neighborhood, the people around you aren't characterized by as many opportunities, you know, and maybe it's rougher, and so that makes you more depressed, and you can just see it's this.
And then, but, on the other hand, if you're starting to climb up, you get exactly the opposite phenomena, which is you start putting away some money so you're more resilient to, you know, random economic occurrences, and as you become—well, for this argument, we'll just use wealth—as you become wealthier, you know, you move into better and better neighborhoods, and then the people around you have more and more opportunities to distribute, and you can go like that.
And that's what happens to people.
So, but most people End up stacked down near the barely clinging to the edge of the world end of the Pareto distribution.
You know, and a huge part of our economic and political discourse is really what to do about that.
Like, there's maybe two arguments.
One is, should there be a Pareto distribution at all?
Should it just be normally distributed?
Which is kind of what a middle class society would look like, right?
Most people have the average amount of money, there's some people who are maybe three or four standard deviations above the mean, and there's some poor people.
And you just can't flatten it out more than that because you'd end up with tyranny.
You know, because if you push a system You can push a system to do anything you want it to do, but as you deform and warp it, it takes more and more force to regulate it.
Now, the distribution of money isn't even close to a normal distribution.
In fact, if you take the top 1% of people who have the money, and you look at that distribution, it's a wild Pareto distribution.
And if you take the.1% and you look at that distribution, it's a wild Pareto distribution.
So, like, it's 1% of the 1% who own half of what the 1% own.
You know, so it just doesn't end until you get to the richest person in the world, you know, and then they own something like… The richest person in the world probably has a hundred billion dollars, that would be my guess.
It might be Putin.
So, but a hundred billion dollars is a lot of money.
It's a very large amount of money, and so… He's like fifty standard deviations above the mean, way out where it's not even imaginable.
Now, you might say, should it be normally distributed?
It's sort of the ideal democratic socialist society in some sense.
Then you might say, well, perhaps not, because maybe you want an undue proportion of the rewards to go to people who are unduly productive.
Now, you know, you think you have a huge advantage, for example, to be born into money.
But it actually turns out that in the United States, anyways, if you had to choose between being born at the 95th percentile for wealth or the 95th percentile for intelligence, you'd be better off at the age of 40 if you were born at the 95th percentile for education or for intelligence.
So wealth matters, or hereditary wealth matters, but it doesn't matter as much as people think it matters.
But that's partly because you actually can get ahead in a functional society if you're smart and hardworking.
You know, if you're in a corrupt society and Work just makes you into a sheep to be fleeced, well then it's obviously better to be born rich.
And so, I would say, the advantage to being born rich is proportional to the amount of corruption in the society.
If it's a corrupt society, it's your only hope.
If it isn't, it might not even necessarily be all that good for you.
You know, what's his name?
The best investor in the world, the richest investor in the world.
His name escapes me.
What's that?
Yeah, yeah.
He's not leaving very much money to his kids.
Like, it would be a lot by our standards, but by his standards, it's like, you know, the pennies in the bottom of his ashtray in his car.
So, and the reason he doesn't want to leave them a lot of money is because he actually thinks it deprives them of necessity.
And depriving someone of necessity is not really a very good thing because, you know, partly the reason you're motivated isn't only because you want some good things to happen.
It might also be because, you know, you better watch out and get your life together or you'll get cut off at the knees.
And, you know, if you're too protected then that all goes away.
And so it isn't necessarily obvious that that's for the best.
So, then you might think, well we should have a modified Pareto distribution, because that'll enable people who are hyper productive to be rewarded for it, but more importantly, if you don't have a Pareto distribution in your society, there aren't individuals who amass large pools of capital, and then it's very difficult for there to be investment taking place, because some things are really expensive.
So, for example, if you want to build a fabrication plant to make computer chips, you need about four billion dollars.
And it isn't really all that useful—it seems to me that it wouldn't be all that useful if the only institution who ever had that much money was the government, because that would mean that the government would have to be the lead investor in everything.
And that's just not tenable, you know, you can replace all the venture capitalists with government agents, you know, government workers.
That's not going to work.
So you do want there to be fairly large pools of capital, and you can also make a case that You don't want all the power centralized, and so if you take wealth away from people, I mean high levels of wealth, what happens is again you start to centralize power in the government because it's the only institution that's large enough to wield a lot of clout.
You know, and they say in the U.S. that most billionaires now are self-made.
And so then you might think, well if someone is capable of parceling out the crooks—there's always going to be crooks— If someone is capable of generating a billion dollars by the time they're forty, it's conceivable that that's the sort of person you want to have that much money.
Because obviously they know what to do with it, right?
I mean, it's easy to waste money.
You can do that.
I mean, I've seen people blow through three million dollars in two years with no problem.
Like, you can distribute money if you're not careful Like snow melting in your hands.
It's hard to keep it, it's hard to use it, it's hard to invest it properly.
And it's certainly possible that you want fairly large pools of capital distributed in the society so there are multiple points of power.
But you could still argue about exactly what sort of Pareto distribution you'd want.
And there's some good demonstrations in the in the US.
I can show you that too.
That's a good one There's a chart I saw recently I can't get out of my hand A Harvard business professor and economist asked more than 5,000 Americans how they thought wealth was distributed in the United States.
This is what they said they thought it was.
Dividing the country into five rough groups of the top, bottom, and middle three 20% groups.
They asked people how they thought the wealth in this country was divided.
Then he asked them what they thought was the ideal distribution.
And 92% That's at least 9 out of 10 of them, said it should be more like this.
In other words, more equitable than they think it is.
Now that fact is telling, admittedly, the notion that most Americans know that the system is already skewed unfairly.
But what's most interesting to me is the reality compared to our perception.
The ideal is as far removed from our perception of reality as the actual distribution is from what we think exists in this country.
So, ignore the ideal for a moment.
Here's what we think it is again.
And here is the actual distribution.
Shockingly skewed.
Not only do the bottom 20% and the next 20%, the bottom 40% of Americans barely have any of the wealth.
I mean, it's hard to even see them on the chart.
But the top 1% has more of the country's wealth than 9 out of 10 Americans believe the entire top 20% should have.
Mind-blowing.
But let's look at it another way, because I find this chart kind of difficult to wrap my head around.
Instead, let's reduce the 311 million Americans to just a representative 100 people.
Make it simple.
Here they are.
Teachers, coaches, So that's the monopoly game.
Now, let's reduce the total wealth of the United States, which was roughly $54 trillion in 2009, to this symbolic pile of cash.
And let's distribute it among our 100 Americans.
Well, here's socialism, all the wealth of the country distributed equally.
We all know that won't work.
We need to encourage people to work, and work hard to achieve that good ol' American dream and keep our country moving forward.
So, here's that ideal we ask everyone about.
Something like this curve.
This isn't too bad.
We've got some incentive, as the wealthiest folks are now about 10 to 20 times better off than the poorest Americans.
But hey, even the poor folks aren't actually poor, since the poverty line has stayed almost entirely off the chart.
We have a super healthy middle class with a smooth transition into wealth.
And yes, Republicans and Democrats alike chose this curve.
9 out of 10 people, 92%, said this was a nice, ideal distribution of America's wealth.
But let's move on.
This is what people think America's wealth distribution actually looks like.
Not as equitable, clearly, but for me, even this still looks pretty great.
Yes, the poorest 20 to 30% are starting to suffer quite a lot compared to the ideal, And the middle class is certainly struggling more than they were, while the rich and wealthy are making roughly a hundred times that of the poorest Americans, and about ten times that of the still healthy middle class.
Sadly, this isn't even close to the reality.
Here is the actual distribution of wealth in America.
The poorest Americans don't even register.
They're down to pocket change.
And the middle class is barely distinguishable from the poor.
In fact, even the rich between the top 10 and 20 percentile are worse off.
Only the top 10 percent are better off.
And how much better off?
So much better off that the top 2 to 5 percent are actually off the chart at this scale.
And the top 1 percent?
This guy?
Well, his stack of money stretches 10 times higher than we can show.
Here's his stack of cash, restacked all by itself.
This is the top 1% we've been hearing so much about.
So much green in his pockets that I have to give him a whole new column of his own, because he won't fit on my chart.
1% of America has 40% of all the nation's wealth.
The bottom 80%, 8 out of every 10 people, or 80 out of these 100, only has 7% between them.
And this has only gotten worse in the last 20 to 30 years.
While the richest 1% take home almost a quarter of the national income today, in 1976 they took home only 9%, meaning their share of income has nearly tripled in the last 30 years.
The top 1% owned half the country's stocks, bonds, and mutual funds.
The bottom 50% of Americans own only half a percent of these investments.
Which means they aren't investing.
They're just scraping by.
I'm sure many of these wealthy people have worked very hard for their money.
But do you really believe that the CEO is working 380 times harder than his average employee?
Not his lowest paid employee.
See, that's the one error, I think, that's in this video.
How hard you work is irrelevant in terms of how much money, or almost irrelevant in terms of how much money you generate, right?
Because, obviously, the people who work really hard I mean, who works hard?
Those guys that are digging holes out in the road in the winter, they're working hard, right?
But you're not rewarded for the physical effort that you put in, or rarely.
There's some association, but not very much.
And so it isn't whether or not the CEO works 380 times harder.
It's whether or not their productivity can be leveraged enough to justify that level of what?
Compensation.
Now you can make arguments on both sides of that and it depends a lot on the industry and on the individual and all of those things, but you don't want to reduce this argument to one of hard work.
It's not appropriate.
It's too unsophisticated.
Not the janitor, but the average earner in his company.
The average worker needs to work more than a month to earn what the CEO makes in one hour.
We certainly don't have to go all the way to socialism to find something that is fair for hardworking Americans.
We don't even have to achieve what most of us consider might be ideal.
All we need to do is wake up and realize that the reality in this country is not at all what we think it is.
Yeah, so there's a two-minute explanation for Trump and Sanders.
Really, I'm dead serious about that.
I'm dead serious about that.
You know, because the right wing, the working class right wing, they think they've been absolutely screwed over, and they have.
And then, you know, the left thinks, well, there's way too much power concentrated at the top, and that distribution would be the answer.
The problem is, is that—and this is the real problem—it's not that easy to figure out how to distribute the money.
Like, first of all, there's a natural proclivity, you might say.
You can model it with laws of physics.
There's a natural proclivity of money to rank itself out like that.
And so that happens in every culture.
Now, maybe you can modify the steepness, but it's not easy to figure out how.
You know, and there's a bunch of problems, because there's a bunch of problems that are associated with the more dim-witted solutions.
For example, lots of people think that poverty is caused by lack of money.
And that's really not a very sophisticated theory, because there's lots of things that cause poverty.
Low IQ causes poverty.
And I'm not saying that all poor people have low IQ, because that would be stupid.
But, obviously, if you have an IQ of 80 and you can barely read, the probability that you're going to end up poor is pretty damn high.
Right?
So, you've got that.
And, you know, it's about 10% of the population who has an IQ of less than 80.
That's a lot of people.
And so they're not literate.
So you think about what they can do.
They can't run computers, generally speaking.
Okay.
Well then there's people who are ill.
You know, there's a lot of them.
Then there's people who are alone, and that's a big problem because they're one step away from disaster, right, if you're alone.
Then there's people who have alcohol and drug problems, and people with screwed up families, and you know, you can go on and on to add up the reasons that people fall off the edge of the world.
And money Won't scratch the surface for many of those problems.
For addiction, for example, now maybe spending on programs that would remediate addiction would be useful, but if you're an addict and you get money, that's not a good thing.
Because all that means is that you're going to just run out the addiction until you run out of money.
And so, you've got to have a more sophisticated idea of what constitutes poverty before you can properly address it.
And then you also have to take into account That a lot of what's driving people crazy, say in places like the US, isn't the fact that there's absolute poverty.
Because there's actually not that much absolute poverty in the US. So if you take the bottom 5% of the US population, by world standards they're doing just fine.
But by American standards they're doing terribly.
And so you have the relative poverty problem.
And relative poverty drives aggression.
And so that's something that's really worth knowing, and this is something that the conservatives just haven't seemed to figure out as far as I can tell, because the conservatives might say, well, you should let the money pile up on the right-hand side because, you know, the system is fair and smart, people deserve to be rewarded, and so on and so forth.
The problem is, is that as that curve increases in height, the probability that the surrounding society is going to become violent starts to ratchet up tremendously, and you see this in places like Central America, where if you have money, you have to live in a bubble, because if you don't, people will kidnap you.
And so then you might think, well, if you have a billion dollars but you can't go outside except in a helicopter with armed guards, how rich are you really?
You know, in a place like Canada, like in Montreal or Toronto, there are good examples, the city is so damn safe that you don't have to live in your house.
You can live in the city, and that's a massive economic, like, that should be calculated as part of your net worth.
And that's a consequence of reasonable public programs and the fact that, you know, the distribution of income in Canada hasn't got to the point where things are destabilizing.
And so conservatives should be watching out for that incredible disproportionality of income as much as anyone else, if one of their prime concerns is to maintain social stability.
The problem that we haven't been able to solve as a culture from an economic perspective is how to distribute money down the Pareto distribution in a way that actually works.
It's way harder than you think.
You know, so, for example, if you set up large social services institutions, governmental institutions, or charities even for that matter, the problem is that the What would you call it?
The baseline cost of the organizations is so damn high that hardly any of the money ever gets to the people that it's supposed to be helping.
I mean, that's really the case with foreign aid in places like Africa, where the poor people virtually never get any money.
You know, so you think a corporation spends about 95% of its time just ensuring that it survives, right?
It uses that much resources just to keep running.
You set up a charity or a, you know, a social welfare institution, you get the same problem.
All the money's eaten up by the people who are running the institution.
And I'm not being cynical about that.
They have to live, you know.
It's really expensive to hire someone.
You know, if you want someone qualified, if you pay them $50,000, that basically costs you $100,000, because you have to give them an office and it has to have light and heat and all of that.
So, you know, ten employees, it's a million bucks already.
And so if you're fundraising as a charity, To just get past the point where you're surviving is almost impossible.
And then there's the logistical difficulties of actually distributing the money.
How the hell do you do that?
It's not easy.
Finland has instituted a guaranteed minimum wage, minimum salary, per month.
You know, and they're experimenting with that.
But it's a small country, and it's relatively homogenous.
It's more like a big city, or a moderate-sized city, actually.
You could think that the logistics would be a lot more straightforward, but anyways.
Okay, well, so that's actually a preview to some degree of what we're going to talk about when we get to conscientiousness, but you do need to know these things statistically, and you have to, you know, you have to understand what the statistics are representing.
Okay, so people, I mentioned that there are gender differences in personality, and, you know, that's a very controversial claim, weirdly enough.
It's something that's always rather shocked me that it is controversial.
This is from the Gender Equity Resource Center at Berkeley.
Gender is a socially constructed system of classification that ascribes qualities of masculinity and femininity to people.
Gender characteristics can change over time and are different between cultures.
Well, the number of things that are wrong with those two sentences is almost—it would take about three hours to actually point them out.
First of all, the fact that gender characteristics can change over time and are different between cultures in no way implies that those things are socially constructed.
It implies they are partly socially constructed at best, but it also indicates that some of the reasons that things might change over time and are different between cultures could be biological.
Like, there's no saying any—there's no a priori demonstration that that's impossible, and it's not impossible.
And gender is a socially constructed system of classification.
Well, actually, no, that isn't what the data seem to indicate.
And so the best data that I know on that are the Scandinavian studies on personality and we'll take a look at them Oh, this is a good one this is a good one So this is interactions with rhesus monkeys and toys.
We compared the interactions of 34 rhesus monkeys living within a 135 monkey troop with human wheeled toys and plush toys.
Male monkeys, like boys, showed consistent and strong preferences for wheeled toys, while female monkeys, like girls, showed greater variability and preferences.
Thus the magnitude of preference for wheeled over plush toys differed significantly between males and females.
The similarities to human findings demonstrate that such preferences can develop without explicit gendered socialization.
So, exposure to prenatal life events stress is associated with masculinized play behavior in girls.
So, and that was an analysis of in utero exposure to hormones, because one thing that seems to happen, this is, you know, this is one of the many things that contribute to the differences between males and females, is that the basic human body The phenotype is feminine.
So if you have XY chromosomes or XX chromosomes and you're not exposed to testosterone in utero, you'll come out with a female physiology.
So what happens is that in utero the male embryo is masculinized by testosterone.
Now, there's also testosterone production for women, you know, but there's more for the male babies.
And there's some evidence that suggests that the more testosterone that a fetus is exposed to in utero, the more masculinized their cognitive styles and toy preferences and behaviors are.
But it's also the case for females.
Like, the more they're exposed to testosterone in utero, the more that's also the case.
And that's what this particular study showed.
This is, yes, this is Simon Baron Cohen's work.
He did the work with fetal development and he showed that fetal testosterone is inversely correlated with social behavior such as eye contact in infancy, peer relations in preschoolers, and mentalistic interpretations of animate motion.
Male fetuses are exposed to higher levels of testosterone than are female fetuses.
So, his theory actually is that autism is the extreme end of Masculinized cognitive development, because it's all thing-oriented.
No people orientation at all.
And then the The opposite end of the distribution.
He's associated with predisposition to psychosis, although I find that part of the theory weaker.
But, you know, who knows?
It's certainly a possibility.
So, yeah, and eye contact is one of the things that's really lacking in people who are autistic.
You know, you get an awful lot of social information from observing the face, and you have specialized circuits for pulling in emotional information from face observation.
So, yeah.
UN Indices of gender equality and economic development are associated with larger gender differences in agreeableness, but not in extroversion or neuroticism.
So, what's happened in a Scandinavian country, so imagine that any given trait is a combination of environmental variables and genetic, biological variables.
Okay, now, you tend to think of those things as isolated, but they're not.
Weirdly enough, the relationship between biological determination and cultural determination is determined by the culture, which is a very strange thing.
So, what I mean by that is that if you are two years old and I threw you in a box and did nothing but beat you every day for ten years, the probability that you would come out agreeable is very low.
Right?
So, and the point I'm making is that you can take an individual, and if you put them in a radical enough environment, you can pretty much shift them where you're going to shift them.
Now, the harder you want to shift them, the more force it's going to take.
So, you know, like if you took a really agreeable person, you'd have to be pretty malevolent to set up the circumstances that would really make them self-centered and predatory.
But I suspect you could do it.
So, what happens in the Scandinavian countries is that there's been a lot of attempt to flatten out the contribution of society on gender differences, and so all that's happened is that the biological differences have maximized.
See, because what you're really looking for is contribution, and for society to have a contribution there has to be different treatment for men and women, because otherwise society has no effect on the differences between men and women, obviously.
And then there's nothing left but biological differences.
Now, there could be no biological differences.
You know, that's one possibility, and the strict social constructionists wouldn't predict that.
In fact, they still teach that at universities all the time, which I truly believe is appalling.
I think the data is already in on that.
There are consequences of this, too.
So that still, the differences between men and women, say, with regards to agreeableness, still aren't that big, even in the Scandinavian countries, but they're a lot more consistent and larger there than they are in any other societies that have been studied.
So that's pretty weird.
And these are big samples.
These are samples of tens of thousands of people.
They're not trivial studies.
This is a cool one, because It turns out, you know, there were a lot of reasons, there were a lot of, there has been a lot of discussion about why the genders segregate in terms of occupation.
And, you know, sometimes that's taken the form of an IQ argument.
So, I don't know if you guys remember this because maybe it's too long ago, but this president of Harvard University, whose name was Larry Summers, he also served in, whose cabinet?
I don't remember at the moment.
It's probably Obama's, but I'm afraid I don't remember.
Anyways, Larry Summers is a very high, powerful person in the United States, and he was giving a talk at Harvard at one point, and he was, when the Americans started to get concerned about science, technology, engineering, and mathematics, the STEM subjects, because they're kind of thinking we need more people in the STEM Subjects in order to kickstart the economy, which may or may not be true, but anyways, that was the idea.
And one of the problems that was being dealt with was the relative dearth of women in the STEM disciplines.
And Summers made reference to a body of research that suggested that So take that normal distribution there, okay?
You see that one on the screen.
Now imagine you put another one right on top of that, but you flattened it.
You just pushed it down right in the middle.
And so what would happen is, it's a little lower in the middle, but it goes out a little farther on the sides.
And so then what happens, which is analogous to what I told you happened with agreeableness, is that if you go out four standard deviations above the mean, so let's say to the 99 What is it?
85, 95, 99, to the 99.9th percentile.
So one person in a thousand.
Assume one person in a thousand becomes a genius level, is capable of genius level accomplishment in the STEM Areas okay, so it's one of maybe it's more than that, but let's say one in a thousand you're going to get a pretty decent person at that rate They're all going to be men if the male curve is flatter But if you go down the other side of the distribution and you look for the person who's one in a thousand most Intellectually impaired they're also going to be men and so that idea was that the mean levels of IQ between men and women are the same but the standard deviation
is different and the underlying biological Justification for that, roughly speaking, is there often is more variability in male behavior across animal species because males are actually more expendable than females.
And so—and there's a much—there's a differential reproduction rate among males that's high enough so that half of your—you have twice as many female ancestors as male ancestors.
Now you think, well, that's impossible.
But it's not.
If the average woman had one child, Sorry, if the average woman had one child throughout history and the average man who had children had two, then that's what you'd get.
But what it would mean is that an equal number of men would have had zero.
And the distribution for men in fathering is a lot more like that.
It's a pretty high probability that a woman will have at least one child.
Where it's a relatively high probability that a man won't.
And so that's all you need.
And so, given that difference in reproductive value in some sense, it's not like the men don't have reproductive value.
It's that the reproductive value can be fulfilled by a relatively small number of men.
So, men aren't the limiting factor in reproduction.
Women are.
And so, that's across species.
And so what happens is the males seem to get more variable in their behavioral display because there's more advantage to winning and not—and once you lose, it doesn't matter how much you lose by, in some sense.
So, anyways, he got harassed to death for that.
I think they actually—I don't remember what happened to him, but I think he had to stop being president of Harvard University.
But he didn't even say that that was true.
He just said that it was one of the possibilities.
But, and you know, there is debate about that.
There's no debate, ritually no debate, about the average IQ. There is some debate about the standard deviations.
And I think the strongest evidence is sort of in line with the testosterone, the fetal testosterone exposure, is that men have a small edge in spatial reasoning.
And that's mental rotation, for example.
And that seems to be associated with higher levels of fetal testosterone.
Now you do also see sometimes that women have a small edge in verbal intelligence and verbal fluency.
But that might be more associated with trait openness, because trait openness, the creativity part of trait openness is higher among women than it is among men.
But regardless of all that, what really seems to make the difference with regards to the way that the sexes distribute themselves in the In the career landscape is interest.
And the biggest differences between men and women that are normally recorded are recorded in terms of interest.
And the basic distribution seems to be people versus things.
Which is quite cool because that was derived as an independent dimension before Simon Baron-Cohen started to do his work on fetal testosterone exposure.
And those things just happened to map onto each other.
Like his empathizing versus systematizing is a lot like people versus things.
And it also looks a lot like agreeableness.
Simon Baron Cohen's questionnaire and mapped it onto the big five, and the empathizing dimension is, you know, indistinguishable from agreeableness.
Systematizing looks a bit more complex.
We haven't quite sorted that out.
So, men prefer working with things and women with people, and the effect size is almost one standard deviation, which is Well, it's a remarkably powerful effect size.
You rarely see an effect size of that magnitude in psychology, or in the social sciences.
It's a very big determinant.
So, men show stronger—people have categorized jobs into six categories, using this thing they call Ryasek—realistic, investigative, artistic, social, and conventional.
Realistic, investigative, Artistic, social, conventional.
No difference in enterprising.
Yeah, the middle one is enterprising.
And that's kind of a factor analysis-derived categorization system too, and it is related in intelligible ways to the big five.
So, anyways, men show stronger realistic and investigative interests, and women show stronger artistic, social, and conventional interests.
So, and there's no difference in entrepreneurial interest, essentially.
So, I don't know what you think about that, but see one of the things that's happened—oh yes, that's actually what this next slide talks about, so that's very good. so that's very good.
Difference between men and women, interest in engineering, science, and math.
So the men are much, much more interested in engineering.
It's a big, big effect.
They're somewhat more interested in science, and that'd be the harder ends of the science that aren't social, you know.
And they're more interested in math.
So one of the things that you see happens, for example, if you take High math achievers at grade 11 or grade 10, there's not a huge difference in numbers between girls and boys in the United States, but if you track them across time, the proportion of the high ability People who go into mathematics or an allied discipline is way higher among the boys than it is among the girls.
You can make a case that there's some social—you know, maybe there's some social conditioning that's associated with that, except that it's hard to make that case when all that you're—the only people you're picking are people who are already equally good at mathematics, because if it was cultural you'd think that you wouldn't be able to pull them out to begin with.
You have to make the case that all the cultural difference in terms of ability is taking place after the The sorting has occurred.
That just doesn't seem right.
But what seems to be the case is the women who are very, very advanced in mathematical ability aren't that interested in pursuing it as a career.
So it's interest.
So, women underrepresented in STEM—science, technology, engineering, and mathematics—well, women are whoppingly overrepresented in lots of disciplines, though.
So, for example, they're becoming increasingly dominant in In medicine.
So, you know, and that's a real switch because, of course, that wasn't the case fifty years ago.
So, high-end, cognitively complex jobs that involve a lot of social interaction and a lot of care for people are overwhelmingly becoming dominated by women.
So, but math, physical sciences, computer science, and engineering don't seem to be, at least at the moment, in that group.
So, and there's There's, you know, occupations where women are unbelievably underrepresented.
So why do you think that is?
I mean, if you looked at this list, what would you say?
Why would that be?
What's that?
Things?
Okay.
Anything else?
Well, it's physical, a lot of that, right?
Construction, forestry, mining.
I mean, those are very, very physically demanding jobs, so they require a fair bit of strength.
Generally, you have to be isolated somewhere, especially for forestry and mining.
You know, and they're dangerous jobs.
Men are way over-represented in dangerous occupations.
So almost all the exceedingly dangerous occupations are done by men.
It's actually part of the reason that men make more money than women.
There's a bunch of reasons.
It's not pure arbitrary social prejudice by any stretch of the imagination.
You need a multivariate equation in order to account for the differences.
There's lots of different factors.
One of them is that male-run small businesses make more money than female-run small businesses.
And I think the reason for that is that females often do that part-time.
When they're having kids.
So they're not devoted entirely to the small business but it's a way that they can keep in the economic game while they're also pursuing their family.
Men are more likely to move to work.
And they're more likely to do dangerous jobs.
And they're also more likely to work longer hours.
And so all of those account for some of the reason that men are paid more than women.
It's not pure prejudice.
So there's a good example of the differences in male versus female dominated occupations.
Brick masons, block masons, and stone masons.
There's virtually no women.
Cement masons, concrete finishers and terrazzo workers, electrical power line installers, carpet floor and tile installers, heating, air conditioning, refrigeration mechanics and installers, structural iron and rebar workers, bus and truck mechanics and diesel engine specialists, miscellaneous vehicle and mobile equipment mechanics, tool and die makers, and roofers.
All of those are 99% or more male dominated.
Female dominated occupations in the U.S. Number one, secretaries and administrative assistants.
You know, that's the most common job category for women.
That's unchanged since the middle 1950s.
And that's partly because those are actually pretty good jobs.
They pay well.
They're regular.
They're secure.
They're not too demanding.
They're predictable.
Like, if you have to have a job rather than a career, that's—you know, because a career is something, I suppose, that pays you outside of the money that you're making for the job.
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