(From the article)
> CS departments and CS education in general have a longer history and are much more established in the United States than in China or India especially.
> A lot more is spent per student in the U.S. than in the other three countries.
(From the paper)
> United States have likely similar math and science levels as students in Russia (Implying the difference in CS scores comes from somewhere else)
But the line you quoted was the only "discussion" on the differences in gender in the article. I think there has to be at least something to discuss.Why is the gender gap smallest in China? Why is there a gap at all for people sitting in the same classes? Are there any other metrics (like age?) that had similar differences? Did the size of the gap change when looking at elite institutions?
To be completely fair, there was some discussion in the last paragraph in the paper, but the only hint at what might be causing the difference was that the women in CS aren't high achieving enough. I wouldn't count that as in depth discussion on the cause.
> The gender gap in skills does indicate that more effort is needed to attract higher-achieving female students into CS [...]
Just putting a chart at stating results the end of a paper and an article isn't a discussion. There is a gap between genders about half as large as the gap between countries. Having questions about that doesn't imply a narrative.
Just come out and say it, instead of having this proxy argument over gender.
If it isn't clear: this study can not be used to draw conclusions about racial or gender predispositions. This can only be used to show the status of education on this particular test and for people graduating right now. It doesn't control for how those people got there. If you want to twist it in some other way, that's your prerogative, but you're doing shoddy science.
I am agnostic to the cause of the gender difference, and clearly this study didn't have enough information to give any insights. That's why I find it so unsatisfying that they would put up a chart and mention gender differences if they weren't interested or capable of expanding on the results beyond "[...] more effort is needed to attract higher-achieving female students into CS."
This feels really disingenuous. The questions they brought up are perfectly fine, it's you who seems to be intent on poisoning the discussion by attacking them instead of discussing the issue.
> you'll have to first say that you think that whites are genetically superior to non-white in the world of computer science. After all, doesn't the study show the gap is even greater for nationality?
Nationality is not the same thing as race/ethnicity. At the very least, in the US, a substantial percentage of CS majors are of Asian descent, not European.
Just because they measured the data, does not imply they were trying to explain it. To explain a result would need a very different experimental setup. Every scientist knows this. It's not a conspiracy if a scientist declines to throw darts at a wall on the cause of something. In fact, they specifically say the cause is likely not explainable by the test differences, which were too small.
"The within-country gender gaps in skills are small enough, however, that they may explain little about gender gaps in CS graduates’ labor market outcomes".
In fact, the poster is not "just asking questions". They have a clear opinion, and ignored the researcher's own statements to the contrary.
I'd also then go on to say in my experience the student who went into a CS program for the stability and potential money "CS-curious" over passion for it might do better on scholastic tests of computer science while being less capable of actually programming well.
>In every country, the men came out ahead; the gap overall was smallest in China, and biggest in the U.S.
But if you are looking at a difference of between gender (0.4) and thinking you'd rather hear them talk about that than the difference between nationality (double that at 0.8) then you clearly are coming to the conversation with a narrative already in mind and are not looking at the data.