[coldtea]

>I'm of the opinion that the very act of trying to artificially create equal outcome, is itself sexism.

The predominant view (with enough dominance to get someone fired from Google for challenging it) is that there are no differences between the sexes that can be considered legitimate at all (cultural, in preferences, evolutionary tendencies, etc.), and thus any non-equal outcome much inevitably be the result of suppression.

I don't doubt oppression against women existed and exists (in various forms).

I doubt:

a) that it is an one way street (women have immense power over their children, including male children, and a particular role later in sexual selection, which is hardly a male-dominated "sport") that are not questioned at all in modern societies (e.g. not in the era of arranged marriages). It's assumed that "patriarchy" is bad, but not that "matriarchy" can be bad as well.

b) that there are no legitimate, at least in the context of evolution and culture, differences in preferences between sexes that are not attributable to downright oppression or some "anti-woman" notion.

Women are men, in essence, that just happen to lack penises, and men are women, in essence, that just happen to lack vaginas. Differences in development, body types, capabilities, evolutionary roles, hormonal content, etc., are not to be considered beyond this a priori fact.

[pluma]

The argument I think generally goes like this:

Either women and men as groups are fundamentally equal and there are no intrinsic differences between the two groups, neither in the averages nor distribution. In that case women should not need any special treatment to advance in the same careers. Any imbalance is either the result of bigotry within the field of work or prior to that at the gatekeepers (i.e. college, K12, family).

Or women and men as groups are different, either in the averages (i.e. on average, X are better at Y than Z) or in distribution (i.e. men and women are equally good at or interested in X but one group has more outliers on both ends of the scale). In this case gender parity can only be gained and maintained artificially because a perfectly fair unbiased selection would always result in a skewed balance.

Some studies seem to suggest the latter. We know this to true in sports (which is why e.g. the Olympics are strictly segregated by gender). It just becomes a political problem as soon as we try to propose that this hold true outside the pure physicality of competitive sports.

It's en vogue to treat humans as brains in a vat as soon as we discuss these issues but I'm not convinced this isn't the same fallacy as economists assuming pure rational actors and physicists assuming spherical cows in a vacuum.

EDIT: Obligatory note: gender discrimination is a thing, not just in tech. Corrective measures may help with that. But if we don't know which one of the two premises holds true (or rather to which extent each one is true in this specific case) we don't know whether we can reach both gender parity AND close the gender pay gap, at the same time.

[breuleux]

I think part of the problem is that there is no easy way to tell apart the two possibilities you describe, and corrective measures are not uniquely warranted when the "correct" ratio is 50/50. In fact (perhaps counter-intuitively) corrective measures are probably most warranted when one gender is better than the other. I don't mean what you might think I mean: I don't say that because the ratio ought to be brought to 50/50. What I mean is that if the "correct" ratio is, say, 60/40, you need corrective measures to make sure it does not increase.

The reason why is that this is not a problem with stable dynamics. If you know that Xs are better at Y than Zs, then upon meeting an X you will mentally assign a higher prior "competence" to them than to Z. As you evaluate them, the prior will eventually be replaced by a fair assessment of their skill, but it will never disappear completely. The end result is that at equal competence, you will hire more Xs than Zs.

Now, if, at equal competence, you hired as many Xs as Zs, you would have a ratio of 60/40. But your knowledge of this ratio gives you a prior that favors X, which means you do not do that. Instead, you will get a more skewed ratio, like 65/35. Seeing the discrepancy, Zs will believe that they are being discriminated against, and this will disincentivize them a little from pursuing Y. The Z applicants' quality will decrease, and the gap will widen. So the only way to really get the 60/40 ratio, paradoxically, would be to make sure that evaluators believe that it is 50/50... but then they might feel compelled to compensate for what they believe must be their own bias!

Anyway, it's a really complicated problem, and every side seems to be hoarding their own spherical cows about it.

[pluma]

Interesting. But that would still mean you need to determine the "correct" ratio and adjust the corrective measures to make sure they don't accidentally hypercorrect.

Additionally there's still the problem that we're talking about spherical cows. Hiring policies don't exist in a vacuum. I'll talk about squares and triangles to keep it abstract.

Hiring only "the best of the best" is a quite popular strategy. Let's say the "shared average" model is correct and squares are overrepresented near the average of the applicant pool while underrepresented at the top and bottom. The "correct" ratio might be 60/40. The actual ratio for the top (and bottom) percentile might end up being closer to 90/10.

Now, depending on the size of the pool those 10% squares of the top percentile might be enough for one company to maintain its ratio while only hiring "the best of the best", or even several companies. But at some point companies will have to either sacrifice its ratio and hire more triangles or sacrifice its standards and hire squares who are weaker than some of the triangle candidates.

Note that so far I haven't even been talking about discrimination or perceived biases. This is what happens if we have perfectly rational actors with perfect knowledge of the market simply enacting the policy "only hire the best of the best" with the restriction of "try to maintain a ratio of 60/40".

You could argue sometimes going for the weaker candidate is worth it to combat the chilling effects of perceived biases. But it should be obvious why it's naive to expect any company to choose so voluntarily when it means the competition that doesn't follow the rule will get more better candidates.

And so far we're talking about a single property that is split pretty evenly across the greater population (even if the hiring pool might be unbalanced). What if 60% of the population is yellow, 30% are blue, 9% are green and 1% are red? Diversity programmes often aim for equal representation of minorities, not just for proportional representation. So that means you want 25% red. But you also want this for both sets of polygons, so at a 50/50 ratio you need to try to hire 12.5% red squares, 12.5% red triangles and so on for all colors. Next imagine 20% of squares and triangles also have rounded corners. And 1% changed their number of corners at some point in their lives.

This is clearly a field that needs unexcited empirical studies. Yet gender studies are seething with ideological bias, taking the conclusions a priori as self-evident. And critics are lumped in with those who are ideologically opposed.

I have no idea what the actual distributions look like. I don't know what the correct ratio would be. I know sexism exists. I also know plenty of women are put off by far more benign aspects of the field. I also know plenty of men are put off as well.

For all its flaws the Google Memo got one thing right: appealing to emotion (what he mistakenly called "empathy") is not the way to further our understanding of the situation. Personal anecdotes are heartwarming or gut-wrenching but anecdotes are not data. When scientific results don't match up with anecdotes that shouldn't mean the science is wrong. It just means "this warrants further study". Maybe the science is wrong, then we can find out how that happened and do more science while preventing the same mistakes. But maybe the anecdotes as important as they may feel are outliers. Or maybe both are true and there are problems we need to address but they distract from the actual cause.

It's not like climate change. With climate change if climate change is wrong, by addressing it we just end up wasting a lot of resource to make the world better nevertheless. With identity politics (assuming companies actually "lower the bar" for minorities to "fix" their ratios), if we're wrong, we've ended up treating a lot of people unfairly just to end up with numbers that look fairer.

I think we should continue encouraging women and minorities to get into tech. I also think we should combat sexism and bigotry in the industry. But I also think we should not forestall the conclusion when trying to understand the root cause of these disparities.

[foldr]

No, the predominant view is that there is no evidence that women are genetically predisposed to be worse at programming (on average) than men.

The idea that women might be worse at programming for biological reasons is an entirely post-hoc hypothesis deriving from the current gender distribution in the field. As lots of other STEM fields have seen a sharp increase in the number of women over the past decades, while computer science and software engineering have not, the grounds for thinking that biological differences between men and women are relevant are extremely shaky, and really are nothing more than pseudoscientific rationalizations of the status quo.

Please lets not have any more of this absurd straw man argument that men and women must be equally good at programming because men and women are exactly the same. No-one thinks this.

[deecewan]

I have no real knowledge on this, but what if women just don't, as a generalistic point of view, find programming as interesting? There are plenty of things I don't find that interesting, or enthralling enough to pursue a career in. Midwifery, primary-school teaching, gardening.

Now, I'm not sure if that's just society having pushed me in that direction, or if I, as a human, just don't enjoy those. If it's the former, maybe it needs some work. If it's the latter, does 'equal outcome' really work?

I don't see as big a push to equal out the playing fields in things such as janitorial work. This may be due to the fact that it's not as cognitive, which I understand. I think we need more women in tech to expand our (currently male) viewpoint. But I'm not sure that aggressively targetting people who may not be as interested, from either gender, is the way to do it.

[foldr]

>I have no real knowledge on this, but what if women just don't, as a generalistic point of view, find programming as interesting?

If you have no reason to think that this is true, what is the point of speculating about it?

[coldtea]

The same goes for the opposite notion.

[foldr]

Not really. Men and women are both human, and you'd expect them to be the same in any given respect absent evidence to the contrary.

[coldtea]

>No, the predominant view is that there is no evidence that women are genetically predisposed to be worse at programming (on average) than men.

That might or might not be so -- they might even be better than men.

But note that programming is not just the act of programming. When we talk about "programming jobs" we also talk about specific management structures, deadlines, pressure, long hours, etc. which women might not care about, while men, idiotic as they are, might find "cool" or "macho". After all, men are the idiots that companies lure with free sodas and fussball tables -- I don't think many women would fall for that kind of crap.

[astine]

"Please lets not have any more of this absurd straw man argument that men and women must be equally good at programming because men and women are exactly the same. No-one thinks this."

Sure, but you seem to be implying another straw man that women have to be functionally worse at some task for a difference in outcome to be genetic. People talk much more often about a difference in interest, which could very much be partially genetic.

[foldr]

Exactly the same considerations apply to differences in interest. Men and women don't have to have the same interests to find programming equally interesting, since there are a great many different respects in which someone might find programming interesting and rewarding.

[astine]

"Men and women don't have to have the same interests to find programming equally interesting, since there are a great many different respects in which someone might find programming interesting and rewarding."

This just doesn't make any sense. Just because a hypothesis hasn't been proven doesn't mean that it isn't the case. People don't argue that, "Men and women are different in some respects therefor we presume that they won't have the same performance in this particular field." They argue that, "There is a marked difference in outcome in this particular field and that difference may have something to due with the differences between men and women."

You are trying to argue (it seems) that the difference in outcome in tech is due entirely or primarily to social factors. If that's the case, the burden of proof is on you to show that alternative hypotheses don't apply. If it's not the case, then we need to evaluate how we pursue quotas and other diversity initiatives.

For myself, I've seen arguments that a pretty convincing case (from statistics and known biological factors) for the "interest" hypothesis. It certainly applies to the men and women in my personal life. (I've never worked in the Valley.) It could, I suppose still be largely wrong, but that's not a-priori obvious.

[foldr]

>They argue that, "There is a marked difference in outcome in this particular field and that difference may have something to due with the differences between men and women."

That is not an argument. It's speculation.

>You are trying to argue (it seems) that the difference in outcome in tech is due entirely or primarily to social factors. If that's the case, the burden of proof is on you to show that alternative hypotheses don't apply

The burden of proof is on anyone who claims to know why there are fewer women than men in tech. It doesn't apply exclusively to people with one particular opinion on the matter, as you seem to think it does.

If you look at other fields, radical shifts in gender balance have occurred quite frequently over the past few decades. And women keep telling us about sexism in tech and how it dissuades them from participating in it. And there are far more women in equally geeky fields like, say, mathematics. So it's not really that hard to figure out what's going on.

>For myself, I've seen arguments that a pretty convincing case (from statistics and known biological factors) for the "interest" hypothesis

Then please reveal these arguments so that they can be evaluated.

[astine]

"That is not an argument. It's speculation."

So is the stance that there are fewer women primarily because of social factors. Regardless, when attempting to establish a statistical effect, you have to rule out alternative explanations, even those based on speculation.

"The burden of proof is on anyone who claims to know why there are fewer women than men in tech. It doesn't apply exclusively to people with one particular opinion on the matter, as you seem to think it does."

No, I do not think it does. The burden of proof is on anyone who advocates for one reason over another. I haven't actually argued for stance over another, only corrected your attempts to frame the debate a certain way.

"Then please reveal these arguments so that they can be evaluated."

The SSC post shared multiple times in this thread is one example and I don't see any attempts to rebut this on your part.

"If you look at other fields, radical shifts in gender balance have occurred quite frequently over the past few decades. And women keep telling us about sexism in tech and how it dissuades them from participating in it. And there are far more women in equally geeky fields like, say, mathematics. So it's not really that hard to figure out what's going on."

Sure 'women keep telling us about sexism in tech'. I've read some of those anecdotes. But there is and was also sexism in those other fields you mention. And there are anecdotes such as the one that this thread is on that suggest that sexism in tech can have the opposite effect. So your argument isn't any more clear cut than the reverse argument. It certainly depends on a lot of anecdotes and assumptions about the direction of causation.

I want to be clear here. My intent isn't to argue that there isn't sexism in tech, or that it isn't a problem. (Again, I don't work in the Valley and wouldn't know) My intent is to argue that there are potentially other factors at play and if you don't consider them in your policy decisions, you will have a hard time correcting the problem.

[coldtea]

Not all aspects might be important enough to have somebody consider it such a career. And most important might be just 1-2 aspects that men happen to care about more (or vise versa, but we don't see that).

[BearGoesChirp]

>The predominant view (with enough dominance to get someone fired from Google for challenging it) is that there are no differences between the sexes that can be considered legitimate at all (cultural, in preferences, evolutionary tendencies, etc.), and thus any non-equal outcome much inevitably be the result of suppression.

While I'm not sure how common the view is, one I've seen often enough is even worse because it limits itself to only cases where women are seen as losing out. So any case where women are worse is due to discrimination. Cases where men are worse might be due to discrimination, but might also be biological. At the least, there seems the view that men are biologically worse in some way seems far more socially acceptable than the opposite.