Respectively, most people, most people, most people, most people and most people.

If woman hypothetically had an average IQ of 103 with a standard deviation of 15 points and men's IQ averaged 100 with a standard deviation of 16 points, most super geniuses would be men.

But most highly intelligent people would be woman. Put another way, not only would the average woman be smarter than the average man, the average highly intelligent woman would be more intelligent than the average highly intelligent man.

The bottom line is that it is silly for people on the street to extrapolate from extreme tail values to any kind of general statement, especially given that those tiny tails may be totally due to slight differences in standard deviations.

It is silly for anyone to extrapolate to the individual from group characteristics.

What about extrapolating to the group from group characteristics? Is that stupid too?

We all say this because it PC and it sounds good rolling off the tongue, but in reality it isn't. You can actually see how effective and powerful using stereotypical group differences can be with jury selection, a type of discrimination that leftists are ok with because it is convenient for them.

In criminal trials especially if you knew nothing but the demographic breakdown of the jury (race/sex/education) and not much else you could set a pretty accurate probability of conviction or not.

That is the real reason stereotypes (good and bad) persist despite efforts to remove them. Most people aren't inherently racist or bigoted, or whatever pejorative term is the flavor of the day. People just intuitively know the most effective way to evaluate a situation/person with the information given, and this intuition has been hardwired into us through millions of years of evolution and isn't going away anytime soon.

Obviously as you get new information besides the basic stuff about a person, then it would be foolish to not use that information accordingly, but the starting point is always assigning someone to a group and making assumptions and going from there. And this isn't conscious, it is very subconscious and hardwired.

For example, lets say there was an assault, and the alleged perpetrator and victim were different races. Obviously the first thing the defense is going to do is try to get as many persons on the jury as possible that match the defendant's race, but if you dig deeper and discover further information (i.e. the potential juror is a retired police officer or a victim of an assault themselves) which indicates they are less likely to follow group norms, then you adjust your individual profile accordingly.

Is this supposed to be a joke? Leftists complain about peremptory challenges and the weakness of the Batson challenge all the time. It is the direct opposite of true that minorities have a greater chance of being chosen to sit on a jury than majorities.

I'm fairly sure that you don't need to extrapolate from something to itself.

You are actually supporting my point. If racial profiling in juror dismissal didn't work so well, leftists wouldn't see a need to protect against it.

Of course if there is a black defendant the last thing the defense wants is an all white jury, because knowing exactly nothing else about the case or jurors this stereotype holds up. It is also true getting a couple black jurors dramatically increases the chance for an acquittal, again knowing absolutely nothing else about the specifics.

These facts support my argument. They don't refute it.

If you're going to go ahead and be prejudicial regardless of whether the stereotypes are true or not, what was the point of worrying about the science behind the stereotypes?

A subset of a group containing more than one person is still a group. For example, the subset of female coding applicants among females.

Why are you often obfuscatory rather than truth-seeking? That's the real question on these topics. Do you think you know what the truth is? That's an increasingly hard to shake delusion as you get older. Do you want to separate yourself from the rednecks, for your own self esteem?

You've actually made completely false statements in furtherance of your politics/prejudices, for example on the scientific evidence around homosexual behavior and inheritance. Why?

You just happened to have the facts 100% backwards. Also, having a diverse jury reduces the chance of conviction (not the same thing as acquital) for both black AND WHITE defendants. Good job! You got one fact almost 30% correct!

It is sometimes helpful to actually know some facts.

Yes, similarly your upcoming fact that women and people with a college degree are more likely to vote Republican will also support it despite having the facts incorrect.

However, it doesn't work backwards. Sally is female. Did Sally vote for Trump? What job does Sally have? Sue is white. How many kids does Sue have?

Surely the world would look different if this were the case.

Look at Jews. They run almost anything of note in the US; they are a controlling upper class. Purely from 5-10 IQ points, and probably with a helping hand from their often xenophobic/anti-miseageny culture.

Asians, another minority culture, crush desirable/intellectual professions from maybe an extra 5 points. This despite supposed/claimed racism (Asian names get the same callbacks as black names, for example).

If women had 5 points on men, do you doubt that most desirable or intellectual professions would be women?

I agree with the role standard deviation plays in the argument but your example actually doesnt give them any significant edge to be fair.

These numbers suggest only about 5-10% more super smart a bit below genius level say 140-160 or 145-160 145-155 etc type ranges.

Really highly intelligent people are 1 in 1000 or 1 in 500 say at the beginning of interval. Otherwise 125 and 130 is not that big of a deal.

The genius levels say 160+ (although again many various levels of that) is about 1 in 100000 or better.


The reality of our world is that genius level men outnumber women geniuses by easily >3-1 margin.

The olympics example i offer is not to be left unnoticed. It is very telling. The reason it is important is because it spans many decades and the ratio remains the same almost. This suggests its not a cultural issue for the most part. It is something else. You cannot stop a genius. You can prevent many smart women from reaching their potential due to bad design at large bias but not the genius women. They are a different kind of animal! You may still lose 50% of them but the other 50% will be there precisely because a very smart woman is super difficult to ignore and will get assistance by many men around her in her early youth even if for the wrong reasons. My point is a 160 girl will get a lot more help than a 160 guy in a top university.

It is 10-1 in the olympics or 8-9 to 1 reliably. You do not get 9-1 with differences like in the above example.

You probably need very similar IQ for the averages 100 and 16 vs 100 and 14 to explain what is going on out there.

You definitely want a woman in your super smart team for many reasons these days. A problem appears in my experience when the woman is very aggressive (but not any more than with men that are equally aggressive and insecure). Some of them are very smart but very insecure that men will be after them and they are there to prove a point by topping every guy they ever met in anything constantly and offering permanent attitude that is irritating. The really super top ones are a lot more intriguing and cool about it though. Now there we are talking! The Iranian mathematician that recently died was like that. Those are the most amazing gift in a team because they are not as arrogant as men can be, they are peaceful, cooperating and are still women meaning you get also a different perspective on things that is very important. They are super confident but not in your face confident. They are the perfect smart women! They will remain eternally charming also regardless of age. It is absolutely a joy to interact with them or to listen to them explain their ideas or make presentations. There is something very comforting and calming, uplifting about them, always very creative, friendly and optimistic. They win by the pure value of their ideas not the aggressive overbearing attitude of the other kind. And they win a lot more.

You mean lesbians?

Joking aside, I imagine that anyone who obtains the qualifications for a nontraditional* job will generally be above average in that job.

It is purely a distaste for strong conclusions reached from weak (or nonexistent) data. This is especially true for "we should" statements. Most of the arguments I disparaged were nothing more than the equivalent of "African Americans people have 270 times more risk of sickle cell disease than other groups, therefore we should encourage the use of skin lighteners and discourage people from adopting an African American lifestyle." I also fairly frequently disparage the conflation of environment and choice.

Maybe you should ask me what I think of mentorship programs to see how consistent I am.

*nontraditional for their gender

Black coders as a group underperform so badly that big tech companies - which are as non-racist and pro PC/diversity as you can get - are unable to hire them.

https://www.bloomberg.com/features/2...ersity-coders/

This is despite their desperation to do so.

Reread the article. People who don't start coding before college are unprepared to get a job as a coder at a top-tier company.

I'm going to go out on a limb and say that maybe someone should have hypothesized that the least intensive learning environment ever invented by mankind (college) isn't particularly well-suited to teaching hands-on technical work to people getting a late start at it. I know I was surprised that I was not hired by the Department of State as the Ambassador to Ecuador after taking a few semesters of Spanish. I mean, I had some of the basics down pat!

The article is full of a bunch of dopey left-wing excuses (they have to be, or else they're called racist). I posted it for the stats. And again, this myth is easily debunked. How many dirt-poor Asians grew up with computers, who are now high end coders?

Heck, there are bunches of older guys who never grew up with computers, nor studied it in college, who self learned and now work in the industry. Coding isn't hard if you're bright.
It was you who (stupidly) claimed this:

Now when you find a hiliariously contrary data point, you're saying the opposite? If you wish to walk the above quote back, no problem, I say silly things too sometimes.

When will you ever learn that some people will actually check the sources you cite?

How many dirt-poor Asian people grew up WITH computers but didn't start coding until college and are now high end coders? Three. None are in the US.

As I've repeatedly stated, making strong conclusions from weak or nonexistent data is silly.

The old guys aren't writing code anymore. Someone, of course, had to be the first coder. I didn't start programming until 1982.

Writing machine-learning code is easy?

I didn't see your data point on gender.

When will you ever learn to look at the data rather than the (made-up, make-excuses-otherwise-racist) commentary?

Look at the data on black coders, and tell me that this:
Is not hilariously contradicted by the data.

In fact, I think the exact opposite is true for most things that come to mind.

As soon as everyone stops jumping to strong conclusions based on only weakly-related or unrelated data.

I missed the data on black coders. I saw some data on black people who aren't coders.

Get a male phlebotomist or hairdresser at your next opportunity

I did. I also read the rather interesting article that does a decent job explaining some of the context behind the numbers and the cultural soft barriers that create these kinds of disparities even without deliberate racial biases.

Really, you're better off just making up **** out of whole cloth like that German village where they **** goats in public. That way you avoid making these silly, unsupported claims that the data are accurate but the rest of the article is made up.

ITT, people who don't know the difference between hard data and ad hoc explanation - informed by a political bent, no less. Amazing.

So entrenched is the racism in the US, that's they're hiring Asians in huge numbers:
Or maybe it's that hirings are race-blind, and Asians are simply outstandingly competent at coding? Which do you think is the most reasonable explain for why Asians are 18 times more likely to be coders generally than black people? Racism?

And is it a pure coincidence that the same people who crushed black people 40 years ago on tests of spatial analysis, and somewhat beat whites, are now crushing blacks in an occupation where spatial analysis is a big part of the general skill area, and somewhat beating whites?

Racism though. It's all racism. The white man keeping themselves down to hire Asians instead. Oh wait.