[wonnage]

You can't use statistics without a model. The problem is that you have a shitty model and it's annoying when you keep parroting it like you're so logical. Your model as inferred from this comment is that there's some way to quantify the current applicants, and that applicants below a certain value are always rejected. The remaining applicants are "above the bar" and could be hired. The current "above the bar" group is not 50/50, therefore changing it means accepting people below the bar.

The problem is that none of your assumptions hold water. Technical interviews are about as accurate as flipping a coin. Mundane factors like whether or not the interview is after lunch have a major impact on pass rates. Performance on the interview has little to no predictive value for future job performance.

You can't brush this off as social ignorance, this is simply ignorance of the facts.

[unscrupulous_sw]

Yes! This is the kind of response I would like to have from my coworkers. Attack my models, my assumptions, my arguments. Don't just silently disagree and then label me a sexist afterwards.

Your presumption that I have some agenda and it wasn't social ignorance is a little offensive but whatever. "Ignorance of facts" should not be used as an insult but an opportunity to educate. The social fact that I am guilty of not knowing is that this a commonly parroted argument instead of the first logical model you come up with.

I do think you represented the argument I had at the time very well. The difference is that I used competitive programming as my example for something more controlled (plenty of stats going all the way back to high school level and on the internet no one knows if you're a man/woman/dog). Your counterargument that it isn't predictive is still valid.

Regardless, my current stance is that the question of "whether it lowers the bar or not" is not a relevant question to ask.

The only point I was trying to make with my story is that you can evoke very passionate attacks just for talking about the topic.

[mike00632]

>Don't just silently disagree and then label me a sexist afterwards.

Why can't you criticize your own model, though? Your assertion that hiring more women will lower standards is premised on a belief that men are inherently better. Isn't that embarrassingly obvious to deduce from what you say?

Why isn't it the case that the bar is already lowered for straight, white men or people who otherwise fit tech stereotypes?

Or why does the value of diversity have to manifest in every individual? Maybe being in a diverse work force makes the cis, straight, white men and the company as a whole perform better.

And even if everything I'm saying is just flowery rhetoric with no rational basis, it's still a respectful way to view and treat other people, and your model that suggests women are generally inferior to men takes a big shit all over the aspiration of living in an inclusive, harmonious society.

[unscrupulous_sw]

> Why can't you criticize your own model, though?

I do but lunchtime only lasted so long before it imploded

> Your assertion that hiring more women will lower standards is premised on a belief that men are inherently better. Isn't that embarrassingly obvious to deduce from what you say?

If you're making "embarrassingly obvious deductions" you might be pattern matching me into your favorite straw man and not really deducing anything at all.

I never said women are inferior to men and it's not possible to logically deduce that from what I said. The only premise I assumed is that there are currently more men than women at the top (e.g., pipeline problem). You can even have the average women be way superior to men and still have the problem of hiring more women leading to lower standards, if the few top women are all happily employed elsewhere. I am not even saying this reflects reality, just that your logic sucks.

Why does everything have to be a dog whistle to fit people into hate groups? Some assholes like me are merely technical correctness assholes.

[mike00632]

> ...pattern matching me into your favorite straw man...

So you were just trying to make a nuanced point about women's general engineering skills based on their biology and don't want to be lumped in with all those unsavory people who give lesser consideration to women engineers based on sexist beliefs about women. Noted.

>I never said women are inferior to men and it's not possible to logically deduce that from what I said.

Didn't you imply that hiring women would be 'lowering the bar'?

[Lewton]

Are you so blinded by your pattern matching of what you think he’s saying that you can’t even read the second half of his post??

If there are significantly less women applying for software development jobs then statistically, assuming women are equally good software developers as men, aiming for 50/50 representation necessitates lowering the bar

This does not mean that it’s not a worthwhile pursuit to aim for equal representation

It’s an argument for working towards more women in STEM (we want bigger application pools!)

[umvi]

> Your assertion that hiring more women will lower standards is premised on a belief that men are inherently better. Isn't that embarrassingly obvious to deduce from what you say?

Not at all. Consider:

- You have a pool of 100 men to choose from

- You have a pool of 10 women to choose from.

- You need to hire 20 people.

So, you choose the top 10% of the men and 100% of the women in order to achieve gender parity.

There is no premise that men are inherently better, only that the talent pool is so much larger that you can more easily distill high quality candidates.

[mike00632]

>There is no premise that men are inherently better...

Well, you explicitly contrived a premise that suggests women are excluded from hiring for some other reason. Why are you only choosing from 10 women? And did you not consider the point about the benefits of diversity not needing to manifest in every individual?

[umvi]

> Why are you only choosing from 10 women?

Because only 10 women applied. Meanwhile 100 men applied.

So then you say: "Your recruiting efforts need to target more women".

How? If you go to a college STEM fair to recruit, the same thing will happen. 10 men will stop by your booth for every 1 woman.

[Lewton]

> Why can't you criticize your own model, though? Your assertion that hiring more women will lower standards is premised on a belief that men are inherently better

Why couldn’t you criticize your own model of what you assumed the guy you were replying to was talking about?

He said nothing about women being inferior to men

The fact that you seem to think that challenging your own assumptions is so easy while at the same time being fully incapable of doing so is pretty damned rich

[mike00632]

>He said nothing about women being inferior to men

No, he just clearly implied it.

[onecool]

"Anybody can create a cryptosystem that they themselves cannot break" -- it's easy to not see something wrong with what you're proposing for a variety of reason, this is why level-headed discussion is necessary and valuable. Nobody has the same background or viewpoint, and it's oftentimes harder to criticize others than it is to criticize yourself.

[mike00632]

But it's difficult. Nobody likes to confront people and tell them that their views on women's biology affecting their engineering skills are sexist. It also causes strife in the workplace.

What I suggest is to just be polite to your coworkers and let HR worry about the hiring process. Don't say anything to your coworkers that could suggest they are somehow inferior or have "bad" genetic traits. This seems like basic human civility that gets tossed out the window when someone has a right-wing view about a minority or women.

[eadmund]

> Your assertion that hiring more women will lower standards is premised on a belief that men are inherently better.

You are incorrect. Let's imagine a group of ten men and ten women: we want to hire four in total. Let's assume that we can reduce a potential employee's worth down to a single number from 1 to 10, in order to simplify the example. The men are rated [1, 2, 2, 4, 5, 6, 7, 9, 9, 10]; the women are rated [3, 4, 5, 5, 6, 6, 7, 7, 8, 10]. In this example the women are better on average (5.6) than the men (5.5) — but hiring the top four candidates results in hiring three men [9, 9 & 10] and one woman [10].

This is because while the mean woman is better than the mean man, the standard deviation of skills is more widely distributed across men than women in the example: more men are excellent, but also more men are terrible (in the example, the lowest three candidates are men!).

[mike00632]

If we're going to contrive an instance that will result in a gender gap then why not just say we hire only 3 people? That would be a perfectly contrived example that would illustrate what you're trying to say.

Beyond your contrivances, I take issue with you suggesting that employees can (or should) be rated on a linear scale. Companies have very specific needs and maybe a candidate who is a "2" on your scale is a "10" at fulfilling what the company needs.

I'll say again too that the value of diversity doesn't need to manifest itself in every individual.

[TeMPOraL]

> Mundane factors like whether or not the interview is after lunch have a major impact on pass rates.

[citation needed]

If this is just inferred based on that observation about judges and meal breaks, then keep in mind that this is just a factoid, and a one that fails the sniff test. C.f. http://nautil.us/blog/impossibly-hungry-judges.

[ambien_]

Regardless of the model, how can optimizing two metrics ever yield an improvement in the first compared to just optimizing it alone?

Or is the idea that, because the old model sucks, we need to optimize this intermediary metric (diversity) in the interests of the ultimate goal of raising-the-bar?

[lazyasciiart]

It could work better because we are so bad at actually optimizing for the first variable that we would get better results by not optimizing for it.

[xyzzyz]

This is the standard model used in education, military, and industry. Millions of people go through processes designed according to this model every year, and probably tens of thousands of scientific papers have been written in context of this model. Your complaints are mostly utterly false (eg. “technical interviews are about as accurate as flipping a coin“ is in contrary of the established consensus in literature, and so is “ Performance on the interview has little to no predictive value for future job performance“).

If this was indeed a shitty model, it would have been pointed out to grandparent when he brought it up, but since this model is commonly used and extremely useful, what he got instead was silencing and penalizing through anonymous back door channels.

[blub]

You don't need statistical models to figure out that if you're desperate to hire certain people and there's very few of them in your hiring pipeline, you'll turn a blind eye towards certain interview mistakes where you would normally disqualify candidates.

[jariel]

You did not actually refute any of his claims or demonstrate in any way that his argument 'does not hold water'.

If you truly believe that 'interviewing is completely random' then I have some other, far deeper concerns you might want to address before we even remotely broach the subject of gender disparity.

Moreover - you're totally missing the point: it's not sexist to merely make the argument that 50/50 hiring can lower the bar. It's just intellectual rhetoric. Maybe it's good maybe it's bad, but it's not inherently sexist.

Ergo: if you don't agree with the PC, even if you make a reasonable argument (or even one that's very good) you're put out to pasture.

This is just one example of PC insane enforcement, there are many.

Which is why it's probably better to avoid such subjects because even intelligent people seem to have difficulty being tolerant, or even navigating the issues.