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Comment by chc | Hacker News Reader

> This is what happens when you aim for equality of outcome instead of equality of opportunity.

People throw this accusation around all the time, but it doesn't make much sense. Outcomes are the only holistic way to measure opportunity.

If you're seeing one group getting lesser outcomes, there are only two possibilities: Their opportunities are being artificially limited somewhere, or one of the groups is simply better than the other. So if you really believe this is a meaningful distinction to draw — that measuring outcomes can't tell us about opportunity — what you're really saying is, "The groups who haven't traditionally been in power are in that position because they are innately less capable."

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There's a third possibility: men and women really do have different interests. Further evidence for this comes from the observation that:

The More Gender Equality, the Fewer Women in STEM

https://www.theatlantic.com/science/archive/2018/02/the-more...

That doesn't seem like a third possibility — it sounds like the same thing as "The groups who haven't traditionally been in power are in that position because they are innately less capable."

It's theoretically possible that women just generally suck at computers, but if that's someone's argument, I'd prefer they come out and actually make the argument instead of throwing around smokescreens about "equality of outcomes vs. equality of opportunity."

Capable isn't the same thing as interested. I know many smart people who have no interest in programming (and wonder why I enjoy it). As The Atlantic said:

> Then again, it could just be that, feeling financially secure and on equal footing with men, some women will always choose to follow their passions, rather than whatever labor economists recommend. And those passions don’t always lie within science [or technology].

I know many smart people who have no interest in programming (and wonder why I enjoy it)

I had an ex-girlfriend who could code, but had no interest in doing that for a job. I'm currently married to a woman with 3 degrees, one of which is a PhD, and she also can code, but says she feels sorry for me, because it's my job.

It is when we're talking about outcomes within a field. Either you think women deserve to be paid less or not — there isn't really a third possibility there. If they do deserve worse outcomes, then either they suck innately or they suck because they're not interested, but either way you're saying they suck.

Don't try to put words in my mouth with that false dichotomy.

If someone isn't interested in programming, they don't "suck" at it. They just don't do it.

I'm talking about outcomes for female programmers here. You're saying that female programmers don't program, and therefore they deserve to be paid less than male programmers, who presumably do program? Or what? Who are these female programmers who don't program that you're apparently so interested in talking about?

Women who achieve the same things as men deserve the same compensation. I don't think anyone on this thread disagrees with that.

This article is about a comprehensive review of salaries at Google that concluded that overall, women who achieved the same job levels as men were being paid more.

The opportunity vs. outcome question is applied to the question of representation. How many women should we expect to see at Google, across job levels, if the process for selecting and promoting people is fair?

You're saying that female programmers don't program, and therefore they deserve to be paid less

This is weird. That's not how I read what leereeves wrote at all. Yet you repeatedly insist that's what he's saying. Are you perhaps projecting an opinion onto leereeves? Preferences can very much influence the outcomes of a training pipeline for a field. (I say this as someone who taught a class attended by Chic Tech students.) That's just common sense.

I'm trying to get leereeves to actually explain what he means. What sort of difference do people think exists between men and women that makes them deserve to, for example, be paid less for the same work (i.e. worse outcome) without being worse at the job?

You're asking me to explain something that may not even be true. According to the article, your scenario is not reality:

> When Google conducted a study recently to determine whether the company was underpaying women and members of minority groups, it found, to the surprise of just about everyone, that men were paid less money than women for doing similar work.

men were paid less money than women for doing similar work.

My room mate works fewer hours than me and doesn't have oncall rotations. He makes less money accordingly.

Are you willing to walk up to his face and tell him that he "sucks" because he doesn't work as hard and doesn't have the same TC as I do?

To be frank, your posts are pretty denigrating to people who choose to have better work life balance. Not everyone sees their self worth in terms of dollars.

It's interesting that you still don't understand the third possibility. I wonder if it has something to do with why many hard-leaning leftists also only consider the first two as possibilities.

OK, let me give you an example outcome and maybe you can explain to me how the third possibility applies in a way that is meaningfully distinct from the first two.

Outcome: The women working as programmers at FooSoft make on average 10% less than the men working there.

Possible reasons:

1. Lack of opportunity (e.g. people in power at FooSoft have bias against them makes it harder for them to have their contributions valued)

2. They just aren't as good as the men

3. They...have different interests in some way that apparently doesn't make them worse but does make them deserve to be paid less?

Let's be specific and replace FooSoft with Google.

A quick search suggests that only 20% of programmers in general are female, but 30% of Google programmers are female. I'm not certain these numbers are accurate, but if they are, female programmers are over represented at Google.

That would mean Google hired a greater percentage of female programmers than male programmers. That is, if Google hired the top 0.1% of male programmers, they hired the top 0.15% of female programmers.

If we assume two groups have identical distribution of qualifications, the female programmers hired would have lower qualifications, as an obvious consequence of a hiring policy that favors women. That's not saying women are less qualified, it's saying that Google hires women who are less qualified because they want to hire more women than the 20% that sex-blind hiring would result in.

Going by the "logic" of outcomes being the "only holistic measure" this would indicate that Google is biased against male programmers within the context of the pool of available candidates. Yet if we change the scope of our consideration to that of the general population, Google would be biased against females.

Seems like the "only holistic measure" has some kind of issue with logical consistency. One has to be careful with how the population sample relates to the specific pipeline of available candidates. If one isn't careful, then the interpretation of the numbers might as well be fiction. You can't just stop at, "Does it match the general population? No? Then BIAS!"

> Yet if we change the scope of our consideration to that of the general population, Google would be biased against females.

That would be expecting Google to hire untrained people as programmers, which would be absurd.

If we compare with the general population, any bias found wouldn't be at Google, but in the school system, children's entertainment, parenting, or some other group that influences people long before they apply to Google.

> A quick search suggests that only 20% of programmers in general are female, but 30% of Google programmers are female. I'm not certain these numbers are accurate, but if they are, female programmers are over represented at Google.

The pool of programmers "In general" is not relevant for Google. They don't hire programmers in general, but are focused on a specific subset (usually from some big universities).

What's the gender distribution of graduates from those big universities?

Let me get this straight: When women are hired less, it's because they're simply not interested. But when men are hired less, it's because they're being discriminated against?

I think my hypothesis is simpler:

- Women are discriminated against in the industry as a whole

- Google actively discriminates in favor of women

It's discrimination both times.

What makes you think women are hired less?

When Google (and other top tech companies) actively discriminate in favor of women, that causes the appearance of discrimination elsewhere in the industry, because the top tech companies have taken more of the best female programmers and those who weren't hired by Google et al are, on average, worse than the men who weren't hired by Google et al.

And when I spoke about interests, I was discussing why few women choose to study computer science.

Women are discriminated against in the industry as a whole

I would expect in 2019, that the industry as a whole discriminates in favor of women, but I'm just a layperson when it comes to that. Do you have citations?

- Google actively discriminates in favor of women

It's discrimination both times.

I agree.

It may be that it has changed very recently, but a few years ago there were quite a few studies that showed an anti-women bias in evaluating employees. For example, here's a quickly Googled cite that talks about a preference for resumes with male names over female: https://www.aauw.org/2015/06/11/john-or-jennifer/

This could even still be true at Google, though I don't have insight into whether or not it is. It seems at least plausible that Google has put systemic biases in place to balance out more diffuse bias among individual humans, but has done too thorough a job.

When orchestras started using blinds for auditions, the population of women hired shot up. Have there been attempts to do blind hiring? If so, what were the results?

Excellent question. There was an article a few years ago about an interviewing platform that tried using voice modulation to play with the gender of candidates:

"Contrary to what we expected (and probably contrary to what you expected as well!), masking gender had no effect on interview performance with respect to any of the scoring criteria (would advance to next round, technical ability, problem solving ability). If anything, we started to notice some trends in the opposite direction of what we expected: for technical ability, it appeared that men who were modulated to sound like women did a bit better than unmodulated men and that women who were modulated to sound like men did a bit worse than unmodulated women. Though these trends weren’t statistically significant, I am mentioning them because they were unexpected and definitely something to watch for as we collect more data." http://blog.interviewing.io/we-built-voice-modulation-to-mas...

I'd had that study in my mental lexicon of "gender bias studies that aren't total bullshit" for a long time until recently. Seemed like a pretty black and white way to isolate gender discrimination. Turns out it - or rather the reporting on it - is also bullshit[1].

[1] https://medium.com/@jsmp/orchestrating-false-beliefs-about-g...

You've jumped into a discussion about the ratio of men to women in STEM and started talking about equal pay, when none of the parent comments were taking about pay, and the article we are discussing is a study that found women at Google get paid more than their male peers. I'm not sure what's going on here.

Yeah, this isn't what we're talking about at all.

Outcome: Women working as programmers at FooSoft comprise 10% less of the workforce than men working there.

Possible reasons

1. Hiring bias

2. Not as qualified

3. Less applicants due to disinterest in programming as a vocation

Outcomes are the only holistic way to measure opportunity.

I'm sorry, but that's "not even wrong" as Pauli would say.

what you're really saying is, "The groups who haven't traditionally been in power are in that position because they are innately less capable."

Group cultures/subcultures can pass on knowledge, which can then provide advantages and then be transmitted to different groups. No racial or innate superiority or inferiority is needed for such an explanation. This is well corroborated by history. (See Thomas Sowell's Migrations And Cultures: A World View) An example of this is found in the German influences in Mexico, and the part of Monterrey one of my old hackerspace colleagues is from. He's quite proud of the progressive schooling he had and of the engineering culture there. (The story of German emigration has its stories of misfortune as well, including examples of German ethnic disadvantage as well.)

20th century hacker culture has its roots in the model railway building scene, which was largely a male space. There's nothing inherently male about model railway building or hacking itself, but there was something about the subculture which was. If we're to change this, then it shouldn't be done from the punitive and negative standpoint of blame, but from a positive view of transmission. No "inherent" or identitarian notions are needed at all.

> Outcomes are the only holistic way to measure opportunity.

Additionally, this is also affected by Simpson's paradox. Without conditioning on the correct causal effects, you may end up at exactly the opposite conclusion to the truth.

What you're describing here is a disparity of outcomes reflecting a disparity of opportunity, isn't it? I agree with everything you said here, but you're presenting it as a disagreement, so I'm a little bit confused.

What you're describing here is a disparity of outcomes reflecting a disparity of opportunity, isn't it?

What I'm talking about is a kind of "grassroots" disparity of opportunity. It's not necessarily the same as a "systemic" disparity of opportunity. The former can often be available to people who are literally poorer than the poor. (As has been the case for Chinese immigrants at times.) Irish Traditional music contains another example of the former.

Often, disparities can be a mix of these two things.

I agree with everything you said here, but you're presenting it as a disagreement, so I'm a little bit confused

I'm glad you're feeling a little bit confused. Often, this can be a good sign!

The problem with how such disparities are talked about and acted upon, is that the complexity of the situation is often downplayed or drastically underestimated, then combined with a punitive attitude of blame and compensation. This isn't how these things are known to work. The best way to transmit cultural knowledge is through some form of competition. (Friendly and peaceful are best, of course.)

I don't think anyone here is arguing for punishment or blame, though — I certainly wasn't. All I said was that if you look at a group getting much worse outcomes and declare that their opportunities were at least as good as the group getting better outcomes, it logically follows that the members of the group are simply not capable. If you wouldn't feel confident saying that explicitly, then comments about "outcomes vs. opportunity" are misguided and there's probably some kind of opportunity disparity that you've missed but which is reflected in the outcome.

I don't think anyone here is arguing for punishment or blame, though

An old schoolmate of mine who was at Google before the James Damore thing happened, was saying stuff just afterwards like, maybe it's time that males got stuff taken away from them.

All I said was that if you look at a group getting much worse outcomes and declare that their opportunities were at least as good as the group getting better outcomes, it logically follows that the members of the group are simply not capable.

Sorry, but it doesn't follow logically. I've dated two women who can code, and who can outperform students I've taught in that, but who don't like doing it at all. Their employment outcomes as programmers would be nil, because that's not what they want to do. People keep explaining this to you, and yet you keep coming out with, "it logically follows that the members of the group are simply not capable." I got a group of two who are capable, but have an outcome of zero. Proof by example, your logical assertion is wrong. (No guff about anecdotes vs. data. You're the one who said, "it logically follows," and even a group of two is enough to refute "logic.")

Your problem is that you're measuring outcomes only in terms of money. Maybe women value time & family more than money & success?!

Women do yoga. Men do martial arts. Which is "better"? Which is the "lesser outcome"? None. It's just a difference (in preferences and therefore outcome).

Seems like an extremely reductive view to take: you can't use time and family to buy food.

Gender roles aren't so cut and dry any more. Given that, maybe outcomes should be considered independent of gender?

> you can't use time and family to buy food.

Yes, but you also don't need millions. Any measures of pay inequality will be skewed by extreme outcomes (as the distribution is floored), so people who decide they earn enough and prioritize time/family over further career progress will appear in statistics as "inequality" (edit: even though it's actually good that our society is so wealthy and productive that some people can afford to do that).

> so people who decide they earn enough and prioritize time/family over further career progress will appear in statistics as "inequality"

It's even worse than that. According to the same statistics, a person who bought a ticket for their favourite band's performance last night is worse off than a day before, whereas their favourite band are better off. In fact, the statistics would show that inequality increased dramatically last night, the band was famous and there were 10k+ people giving away their money, whereas - let's say, five - random guys got "significantly richer" at the same time.

The value of the emotional uplifting and sense of life after the gig? Nah, not an asset to rely upon in "strict" statistics.

I know a man who does yoga and martial arts.

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