Comment by kromem | Hacker News Reader

Comment by kromem | Hacker News Reader

An interesting anecdote regarding gender bias and tech.

In the very early stage of my company, we wanted to outsource some UX work. After an exhausting review of applicants on one of the freelance sites out there, we finally settled on a Pakistani woman who had the best balance of portfolio vs cost.

At the initial Skype call, there was no video. And it turned out to be a guy speaking in a very high voice. We didn't really care and just went along with it (after a call or two he dropped his octave significantly, but everything continued with the original female name). But it was curious that this enterprising individual decided that the best way to stand out from the countless other developers with similar demographics he was competing against was to pretend to be a woman.

I do suspect that the presumed bias that women aren't actually as skilled and got where they are because of gender preference, while an uncomfortable bias for women, does make it so that a woman with equal skill to a male candidate is perceived as a greater rarity/find because "oh wow, this one is legit." (Not saying women are actually less likely to be legit, just saying the perception that is true can work to board in the opposite direction). I'd be extremely curious to see the classic "attach picture to resume/work sample" experiment done for tech with actual hiring managers. I'd be very surprised if the work with the female photo has a lower net score than the male photo across the experimental groups.

That experiment was done in STEM academia recently, and showed a 2:1 hiring advantage for women.

http://www.pnas.org/content/112/17/5360.abstract

It should also be noted that the earlier study, which showed a smaller effect and only if the resumes were calibrated to be (a) mediocre and (b) precisely calibrated to be the same, was done in Psychology. Which is, of course, a field dominated by women and maybe not the typical "STEM" that we think about when we talk about the underrepresentation of women in tech.

Those two findings in turn gel with a recent French study that showed bias in grading in favor of the underrepresented gender in a particular field (though the bias was stronger in favor of women than in favor of men).

http://www.the-scientist.com/?articles.view/articleNo/46681/...

And of course there was the recent trial (not an experiment AFAICT) in Australia to reduce gender bias:

http://www.abc.net.au/news/2017-06-30/bilnd-recruitment-tria...

"The trial found assigning a male name to a candidate made them 3.2 per cent less likely to get a job interview. Adding a woman's name to a CV made the candidate 2.9 per cent more likely to get a foot in the door."

UPDATE: I was looking for one more thing, and finally found it. Despite the fact that the study showing bias against women is much weaker, it has been cited several times more often than the study showing bias for women (table near the bottom). https://www.psychologytoday.com/blog/rabble-rouser/201707/wh...

>That experiment was done in STEM academia recently, and showed a 2:1 hiring advantage for women.

Back when I was still at university I was on a hiring panel for a new prof.

In a first step we ranked all the applicants using qualitative and quantitative metrics (the rankings across qualitative/quantitative and people on the panel was very similar when we compared rankings at the end) and then we handed in a shortlist with the best male applicant and best female applicant. We did this to make the Gleichstellungsbeauftragte (="diversity officer") shut up and thought that since the ability gap was really noticeable it'd be a no contest. How wrong we were. Despite being in the upper part of the bottom half of our ranking, she got the job.

That was the day I found out that I wasn't at a meritocratic institution as I had previously thought and left a few months later. That sort of thing really isn't good for your self confidence.

When you say the ranking was quantitative, what sort of quantities did you measure? Did you ever evaluate the quality of your metrics, and how predictive they were for future success?

IIRC, Google did the same thing and concluded their hiring metrics had very little predictive value beyond setting a certain bar. Once you rose to that level, most discriminatory power of the metric evaporated.

If that was the case where you were, then is probably very little predictive value between "top scores" and "median scores".

The Internet: where men are men, women are men, and children are FBI agents

hate when that happens.

When I applied to colleges, I put that I was Native American, because, you know, I was born here.

There is a very probable & simple explanation you have missed.

It is common to use a "competent" person to impersonate the actual candidate for remote and/or contract positions, especially in H1B scenarios. I used to insist on a video with a whiteboard or a follow up in-person interview.

In this case they just couldn't find a female in quick time.

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