I'm suggesting that you are inviting selection bias. That does not provide any grounds to question the median aptitude of the population. It just says that anything you infer from your sample data is most-likely skewed.
Now, a skew is discriminantory (by definition it is bias). Whether or not it is <sexist> is simply a question of distribution of the mechanism responsible.
Is a program of 3.5 years of self-study (lets assume, in social isolation) an equally attractive proposition? Probably not, given that women consider doing anything in isolation to somewhat socially demeaning. We know that women, for example, self-select mates based on quite the opposite: high social standing. A long self-enforced period of social isolation is thus <rationally> counter-productive from the perspective of evolutionary biology. So, if we use this as a gating function, yes we will get biased results.
Fairness is a question of expected value. A fair bet is one where the ratio of cost/benefit is equal. So, in this case where there is an asymmetric cost, the result is uneven fairness (in this sense).
Whether or not it is right or wrong depends upon your criterion for value. By one standard - maximizing the potential peformance - it would be inefficient. This is beacaus you have mean XY and below mean XX performance represented (~regardless of proportionality -- as XX is biased down in both quality and quantity). Whether or not this inefficiency is wrong or acceptable is on the whole, just re-phrasing whether or not gender bias is (or is not) wrong.
The original recommendation was phrased in a somewhat harsh manner. And while I could be wrong, I really don't think it was meant to be taken completely literally.
I think the literal intention of it was: "if you want to join this field, all you need to do is put in the time and effort to get really good at it". Not that you should literally lock yourself away in social isolation and speak to no other human beings for several years.
"Put in the time and effort" could also involve networking with other hackers, finding collaborators for open source project or startups, communicating on IRC channels, and learning from peers in person. Yes, there will be hours of solo grinding out code and debugging - but that's not the only thing that a programmer does.
Actually, look at what is written..."go read the book"...and "don't talk to me until its done", are both clearly implied. It is a dick attitude, sorry.
Some people may respond to this, and some may not. Statistically, without question you will get adverse selection. So, yeah you can now start to make assumptions on how to avoid this fate, or not, but otherwise people with real options will do other things.
Now, a skew is discriminantory (by definition it is bias). Whether or not it is <sexist> is simply a question of distribution of the mechanism responsible.
Is a program of 3.5 years of self-study (lets assume, in social isolation) an equally attractive proposition? Probably not, given that women consider doing anything in isolation to somewhat socially demeaning. We know that women, for example, self-select mates based on quite the opposite: high social standing. A long self-enforced period of social isolation is thus <rationally> counter-productive from the perspective of evolutionary biology. So, if we use this as a gating function, yes we will get biased results.
Fairness is a question of expected value. A fair bet is one where the ratio of cost/benefit is equal. So, in this case where there is an asymmetric cost, the result is uneven fairness (in this sense).
Whether or not it is right or wrong depends upon your criterion for value. By one standard - maximizing the potential peformance - it would be inefficient. This is beacaus you have mean XY and below mean XX performance represented (~regardless of proportionality -- as XX is biased down in both quality and quantity). Whether or not this inefficiency is wrong or acceptable is on the whole, just re-phrasing whether or not gender bias is (or is not) wrong.
That is beyond the scope of my commentary here.