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Tony Critiques Feminism's avatar

It's a bit different here in Australia.

I only have (very!) incomplete data but it shows (suggests?) a big fast shift from approximate equality to a large difference in results between girls & boys. I have a graph for one state & I have seen data for another but lost it. In both cases the shift coincided with moving from exams set & marked externally to marks being given by one's teacher. However this is ancient history now - 1970s in one case & 1990s in another.

I understand something similar occured in the UK: http://empathygap.uk/?p=3810

In more recent times (since 2008) the proportion of boys failing to achieve minimum standards has continued to get worse compared to girls. (Australia's education system is in a bit of a mess. Standards for both boys & girls decline but more so for boys.)

Similarly entry to Tertiary education.

The number of boys being punished, suspended and expelled are also grounds for concern here.

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Ian [redacted]'s avatar

A) I feel like I'm coming in half way through a movie, this is the first article of yours I've read :)

B) I somewhat understand the purpose of comparing men and women using the standard deviation, and I like the illustrative use of the blue/green group and asking which group is 0.8 inches taller, but I'm still not sure why it *doesn't* matter that women are 0.8 Anecdotal Inches taller.

C) Is it possible that women are very lightly (1/3 Standard Deviation) ahead of men in important aspects of "being good at school" and that this has a large effect on the college aspirations in your algorithm? If that's the case, in my mind it discounts your argument that boys and girls are neck-and-neck by some percentage. I think it matters if there is a 1% difference at T=0 and a 30% difference at T=10. The importance of T=1 to 9.

C) You are acknowledging a higher graduation rate in women (70:100, men-to-women) and I think that tells a significant, explanation-generating story for why society is weirdly skewed. To me, this is the 30% effect at T=10

D) I think that things which we do/should care about are invisible to these chosen metrics. For example, the broke English major trope or the gender studies/masters of education working at Starbucks kind of highlights that graduation rates don't really mean anything to prosperity. I know a decent number of people with a lot of useless masters and PhDs working $50-60k/year jobs, and most of the people I know making >$100k don't have masters degrees (My group is probably a statistical anomaly).

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