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> God forbid that someone make an argument and try to support it with data That's well and fine, but the author stated an opinion based on anecdotal evidence.

> God forbid that someone make an argument and try to support it with data That's well and fine, but the author stated an opinion based on anecdotal evidence. On its own though, I think it's a really stupid thing to say but I think it fits fine given the tone of his rant. While I do agree with your central point, I don't think there's any value in exploring whether or not women might make better programmers on average. If I were to hire someone, I'd base it on their past experience and how well the interview(s) went, not their race or sex. There's no harm in speculating and even doing the research if it interests one that much though, just like there's no harm in researching whether or not painting red stripes on your car will make it go faster.

tjic 17y ago
> If I were to hire someone, I'd base it on their past experience and how well the interview(s) went, not their race or sex. Absolutely. I agree 100%. OTOH, discussing things in aggregates also makes sense. If 4 out of 1,000 women would make excellent engineers, and 1 out of 1,000 men would make excellent engineers, and yet we see that the distribution of actual engineers is something other than 4:1, we should investigate. If, OTOH, the numbers are 1 out of 1,000 and 10 out of 1,000 respectively, and the ratio of actual engineers is 1:10, then we might choose to spend less time and energy on the investigation.
- ilitirit 17y ago
  Maybe it's because you're using a contrived example, but I don't quite agree. These sort of studies are usually undertaken at a higher, more abstract level. eg. How do various cognitive abilities differ between sexes? With the resulting data, we might be able to explain certain phenomena, or dispel certain stereotypes. But I don't think we're anywhere close to being in a position we can say x out y men/women would make excellent engineers. That kind of information is usually extracted from trend analyses (eg. studying the proportion of males/female engineers who are highly successful at their career vs those who aren't), and they're inherently skewed because of the nature of the society we live in.
- randallsquared 17y ago
  If 4 out of 1,000 women would make excellent engineers, and 1 out of 1,000 men would make excellent engineers, and yet we see that the distribution of actual engineers is something other than 4:1, we should investigate. We might want to investigate, but "should" is a strong word. There are all kinds of reasons why this could happen, and some of them might not need fixing. It could be that the total number of people who would make excellent engineers is too low for the number needed, and that men (in your example) are more likely to make adequate or good engineers than women, even though women are more likely to make excellent ones. It could be that women in general, in spite of being four times as likely to make excellent engineers, tend not to enjoy engineering for cultural or other reasons. It could be that the women who would be excellent engineers are in the group that would be pretty good CEOs, and they all become CEOs because there's more money in it. But you get my point: the failure of actual people to conform to the occupations that they would be best at is not, in and of itself, evidence of a problem.

tjic 17y ago

> If I were to hire someone, I'd base it on their past experience and how well the interview(s) went, not their race or sex. Absolutely. I agree 100%. OTOH, discussing things in aggregates also makes sense. If 4 out of 1,000 women would make excellent engineers, and 1 out of 1,000 men would make excellent engineers, and yet we see that the distribution of actual engineers is something other than 4:1, we should investigate. If, OTOH, the numbers are 1 out of 1,000 and 10 out of 1,000 respectively, and the ratio of actual engineers is 1:10, then we might choose to spend less time and energy on the investigation.

ilitirit 17y ago
Maybe it's because you're using a contrived example, but I don't quite agree. These sort of studies are usually undertaken at a higher, more abstract level. eg. How do various cognitive abilities differ between sexes? With the resulting data, we might be able to explain certain phenomena, or dispel certain stereotypes. But I don't think we're anywhere close to being in a position we can say x out y men/women would make excellent engineers. That kind of information is usually extracted from trend analyses (eg. studying the proportion of males/female engineers who are highly successful at their career vs those who aren't), and they're inherently skewed because of the nature of the society we live in.
randallsquared 17y ago
If 4 out of 1,000 women would make excellent engineers, and 1 out of 1,000 men would make excellent engineers, and yet we see that the distribution of actual engineers is something other than 4:1, we should investigate. We might want to investigate, but "should" is a strong word. There are all kinds of reasons why this could happen, and some of them might not need fixing. It could be that the total number of people who would make excellent engineers is too low for the number needed, and that men (in your example) are more likely to make adequate or good engineers than women, even though women are more likely to make excellent ones. It could be that women in general, in spite of being four times as likely to make excellent engineers, tend not to enjoy engineering for cultural or other reasons. It could be that the women who would be excellent engineers are in the group that would be pretty good CEOs, and they all become CEOs because there's more money in it. But you get my point: the failure of actual people to conform to the occupations that they would be best at is not, in and of itself, evidence of a problem.