Y Combinator’s lady problems, in three charts | Hacker News Reader

Y Combinator’s lady problems, in three charts

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12 pointsepeus8 comments

Is the problem that VCs are ignoring startups with female founders, or is it that women are not becoming startup founders in general? For the first one, that's a problem that VCs need to fix. For the second, if there's something systemically keeping women out of tech startups, that's a problem the world needs to fix.

Assuming that VCs always pick the most promising startup founders without discrimination, the next question is would everyone rather VCs fund unprepared or unqualified founders in order to be more inclusive and look better from a PC standpoint, or pick the best founders that come in front of them and accept that there may not be a diverse mix of people at the company?

It's really easy to prove that they're not funding female founders. It's just as easy to shame them for it in the media. It's a lot harder to prove that this is done out of bias or malice. It's even harder to make the business decision to fund more female founders if you're fairly certain that the female founders that approach you for funding are not prepared to be startup founders.

So what can we do? Women leaders in tech aren't exactly uncommon, nor do they necessarily make the news more than male leaders. I'm sure there are fewer female tech leaders than there are men, but that brings us back to the question of is there actually a problem, and if so is it for the tech companies to solve, or is it for the world to solve?

some commentray here on the YC Female Founders conference this weekend: http://blog.ellenchisa.com/2014/03/04/yc-female-founders-con...

The other possibility is that women just aren't as interested in tech as men. The same is true of other professions like pilots and car mechanics.

https://en.wikipedia.org/wiki/Women_in_computing#Female_and_...

Men and women's brains are wired slightly differently, so this shouldn't really be a surprise. We just need to make sure that women are given sufficient opportunity to enter the tech industry.

I'm not sure that there is a difference between the world and tech companies solving the problem. Furthermore, this is a matter YC, a VC firm looking for the best investments, should solve. If not only for their own benefit.

The assumption that VCs always pick the most promising start-ups is a flawed place to start. If we were to break down the graph further and look for black male co-founders or foreign born co-founders with accents (nod to PG's comments on the matter) we'd find even less more than likely.

Many male startup founders are 'not prepared to be startup founders' this can be seen in any series of stories of poor PR, presentation of selves, and ideas like the 'dating ring'. Nothing about 'women' as the other half of the population makes them statistically less likely to be prepared to be startup founders. In fact, considering the young age of many YC applicants, whatever science there is indicates women would be better able to handle the stress and themselves.

It would be a fallacy to ignore bias simply because it hasn't been admitted. I would be interested to see how many women have applied as well, but as a woman in tech, I can say the bias is real.

I'd like to see these normalized by number of applications per category, but I suppose that's a graph only YC could provide.

If YC want to put more figures in the spreadsheet I'll remake the graph. https://docs.google.com/spreadsheets/d/1tZVHgKnNS5ghjkQou4QO...

That second chart is most telling: https://twitter.com/shanley/status/440591732283961344/photo/...

Sure it took them 10 years... but they did finally get to the point that they pretty much match the BLS number. So what is their problem exactly? They didn't get there fast enough? This just strikes me as one of those never enough issues. They got there... late... but there. But damn them anyway.

And as others have mentioned, we would need to compare this to a plot of all applicants for each year. More important than "percentage of funded companies that had 1+ female" would be "percentage of companies with 1+ female that got funded." Those are two totally different data points.

Two things prevent this from being a cogent narrative, in my opinion:

- How do these figures compare to the overall population of applicants?

- How do these figures compare to the entirety of VC-backed startups?

Without that knowledge, this is just extrapolation around a set of isolated data points.

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