Just positing that these things _might_ be true and should be investigated was a key factor in Larry Summers getting drummed out of his position as President of Harvard.
The world at large isn't ready to hear these statistics, and overall that is probably a good thing. We shouldn't accept these disparities as driven by natural forces until we've tried everything we can imagine to try to bring the differences in line.
Over the course of history, far more bad has been wrought by assuming differences were innate than assuming they were the result of bias. Given that, we should assume and act as though differences are due to bias long after the differences are well proven to be natural. It is a case where being wrong in one direction is not very costly, but being wrong in the other direction (and thus institutionalizing bias) is disastrous.
>The world at large isn't ready to hear these statistics
Not the "world at large". Just (provincial) middle/upper class America.
>We shouldn't accept these disparities as driven by natural forces until we've tried everything we can imagine to try to bring the differences in line.
Shouldn't we in fact try to understand what's going on, instead of trying to change it because of a priori notion that there shouldn't be disparities (which, if disparities exist due to natural forces will be unatural and unjust).
Disparity (e.g less women in Tech) is NOT a problem in itself.
Obstacles to access is a problem (e.g a woman not being let to work Tech -- eg not being hired because she is a woman).
Also, why is IT somewhat different? I don't see much push for more female fishermen or male nurses, to name two random professions with similar disparities.
IT's white-collar whereas the jobs you're talking about aren't. Apparently there's never been a huge amount of feminist interest in getting women into male-dominated blue-collar jobs or in working-class women in general; it's an old and fairly well documented issue.
It's money more than status. In the early 1990s, programming was still white collar but paid about the same as accounting, and nobody cared how few women were doing it.
Except it doesn't seem like people are saying "lets get this measurement right so we know what needs to be done". Instead it sounds a lot more like a self-righteous group determining what isn't and isn't the correct way to do things so that we can begin getting noise free measurements.
But all of that self righteousness is driving in the direction of lets try to fix the disparity through social change. I'm saying that even if we believe they're going to be wrong, we should try what they propose (in a structured and measurable way).
So you want me to agree that it's a problem that the male to female ratio isn't equal before you've proven that the inequality is brought about by a bad reason as opposed to a natural and just reason? That greatly reduces my frustration as to why I'm not on board with any of this.
edit: "lets try to fix the disparity through social change" ...as soon as you do the due diligence and convince me it's broken first. Evidence of disparity in no way tells me there is a problem in need of being fixed. It's a lazy way to try and get people behind a misguided white-knighting movement.
> Disparity (e.g less women in Tech) is NOT a problem in itself.
Sure it is. Lack of diversity means lack of understanding about other uses. It also means that biases can go unchecked, and can develop into accepted wisdom.
> Also, why is IT somewhat different?
Because the (false) reasons given for other occupations don't apply at all for tech. "Men are stronger, that's why you don't get women in construction"; "women are nurturing, that's why they make good nurses".
> I don't see much push for more female fishermen or male nurses, to name two random professions with similar disparities.
Have you looked? I'm not sure about fishermen, but there are many programmes to increase the number of men in nursing, or women in construction.
>Sure it is. Lack of diversity means lack of understanding about other uses. It also means that biases can go unchecked, and can develop into accepted wisdom.
But if "lack of diversity" in the ratio of men/women working on IT is an issue _for the reasons you mention_, it means that you accept that men and women have different interests/thinking (uses/biases), and can bring different perspectives.
In which case you should also entertain the idea that women might just not like IT style jobs and the kind of problem solving people do in programming. That's a different bias/perspective too, after all.
>Have you looked? I'm not sure about fishermen, but there are many programmes to increase the number of men in nursing, or women in construction.
> A successful initiative set up to support women working in the construction sector, has been granted £420,750 further funding to continue.
> The government-funded Women and Work: Sector Pathways Initiative is led by Construction Skills and aims to help get women into construction work and supports women already working in the sector to get further training.
> The Women in Civil Construction Initiative will directly address the skills required for entry to the civil infrastructure sector of the industry. The Civil Contractors Federation (CCF), in collaboration with their funding partners Construction Skills Queensland, is delivering a flexible based program designed to deliver the entry level skills required to participants who wish to pursue a career in the Civil infrastructure sector. The WIC program is already underway within Queensland.
> Sure it is. Lack of diversity means lack of understanding about other uses. It also means that biases can go unchecked, and can develop into accepted wisdom.
I wonder if that would explain why all the faculty treated me like garbage in K-12.
Nursing is a well-paid profession that offers flexibility and good benefits.
Fishing can also be a very well paid profession (look at Deadliest Catch for example) but the challenges, hardships, and stress are extreme for those challenging fishing crew jobs.
> The world at large isn't ready to hear these statistics, and overall that is probably a good thing.
I agree. Research and data might make people feel bad, and not making people feel bad is obviously way more important than increasing knowledge.
> We shouldn't accept these disparities as driven by natural forces until we've tried everything we can imagine to try to bring the differences in line.
I agree. Personally I think we should withhold all math education to males until they are 21. We can discontinue this policy when there is a 50/50 gender split among all STEM workers, educators, and investors.
> we should assume and act as though differences are due to bias long after the differences are well proven to be natural
Yep. 1+1=3. Doesn't matter if you can prove that 1+1=2.
> It is a case where being wrong in one direction is not very costly, but being wrong in the other direction (and thus institutionalizing bias) is disastrous.
You're responding almost entirely to things I didn't say.
> Research and data might make people feel bad, and not making people feel bad is obviously way more important than increasing knowledge.
Not what I said at all, I said the standard for proof should be extremely high. High standards for proof != don't do research (though I admit I should have said so more clearly as I used the example of Summers without condemning what happened to him. He shouldn't have been drummed out for asking the questions.)
> We can discontinue this policy when there is a 50/50 gender split among all STEM workers, educators, and investors.
I assumed that the word "reasonable" was implied in what I was saying. But you're right, some people might propose absurd attempts to bring things in line.
> 1+1=3. Doesn't matter if you can prove that 1+1=2.
First of all, I was commenting on the standard by which we should accept 1+1=3, and which of the two (1+1=3 or 1+1=2) should be our acting hypothesis until we know.
Secondly, I said we should act as if differences are due to bias _until long after_. I was arguing for the default standard, and when it would be acceptable to change the standard. I never said never.
> Yep, unimaginable catastrophes.
Are you actually ignorant of the human history of genocide, dismissal of female person-hood, and racially driven slavery?
While it is a good point, I don't think that's directly analogous: I was talking about population statistics and biases that lead to different outcomes in different groups.
Two similar but not identical dichotomies:
* A population difference is due to innate differences vs a difference is due to systemic biases
* An individual difference is due to innate makeup vs a difference is due to individual choices
The question: Why is the % of people with X characteristic in Y profession lower than the average. Applying my proposed standard above to that question, assume differences are due to biases until sumarily proven, we still aren't encouraging or abiding discrimination when X characteristic is sexual orientation.
Looking bad over History, many groups have been denied the right to vote, denied basic human rights, and killed, because it was decided they were different, and therefore this treatment was reasonable.
I am unaware of any reasonable comparisons of where trying to ignore natural differences has caused anything resembling the same level of suffering. I would be interested in some examples you could provide.
Nope, just the biggest one (Holocaust), the second biggest being Holodomor, an Stalin's attack to Ukranian Nationalism. Genocides in Nigeria and similar ones are ethnic ones for political power, without justification over biological differences.
No, I would argue the holocaust and more are confusing cultural disagreements with racial stereotyping which have more to do with (surprise!) culture than race. I think it's much more believable that a large group of people grew angry with a culture of racial inclusion in financial matters leading toward the ease of hatred of a racial stereotype than the actual genes involved. Race is the identifier, not the cause.
If it wasn't race, it would family names or family colors/flags, gender, buck-teeth or what-have-you, as shown throughout history. Bickering and bigotry aren't reason for arbitrarily changing things.
It's really simple. The more gender equality there is in a country, the more women and men revert to stereotypical occupation choices. That is, there are more female engineers in India or Eastern Europe than in Scandinavia.
The countries where the percentage of women pursuing STEM is the highest, are the countries where STEM careers are disproportionately lucrative.
These findings have been confirmed by multiple studies with enormous sample sizes (e.g. Richard Lippa's n=200,000 survey of 53 countries).
Feminists will spend the next couple of years staunchly denying these findings, while the number of women in STEM has flatlined, and the percentage of students that are female only rises because men are systematically discriminated against.
The world at large isn't ready to hear these statistics, and overall that is probably a good thing. We shouldn't accept these disparities as driven by natural forces until we've tried everything we can imagine to try to bring the differences in line.
Over the course of history, far more bad has been wrought by assuming differences were innate than assuming they were the result of bias. Given that, we should assume and act as though differences are due to bias long after the differences are well proven to be natural. It is a case where being wrong in one direction is not very costly, but being wrong in the other direction (and thus institutionalizing bias) is disastrous.
Tldr: we should err on the side of caution.