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>While only 22% of CS PhDs were given to women, they made up an even more minuscule 14% of CS faculty. Not everyone who obtains a degree later chooses to enter

by Nadya 11y ago

>While only 22% of CS PhDs were given to women, they made up an even more minuscule 14% of CS faculty. Not everyone who obtains a degree later chooses to enter their field of study. A degree also does not guarantee a job. This is yet another example of trying to misuse statistics as a form of confirmation bias. Looking at statistics from this Slate article [0], since 2003 only <50%~ of Engineer PHD's are employed. What that means is that of those 22% CS PhDs roughly 11% would be the the number who are employed in the end assuming no gender discrimination beyond obtaining the degree. Given the data is 3 years out of date, it's possible employment rate has jumped to 63% (the highest its been since 1998!) and that 14% is exactly on-par for the course for having no gender discrimination (against or in favor of) women. A more realistic estimate is that the employment rate is still at 50% or below and 14% is actually discrimination in favor of hiring women given less than 11% should be hired at current employment rates. >First, to your (horribly sexist) implication that women opt out of the workforce by studying "Gender or Women's Studies": it isn't even in the top 10 majors for women. It was one example of a major dominated by women that is useless for holding any of the jobs listed as "liked". They also "opt out of the Engineering work force" by majoring in Biology, Business, and Psychology and not Engineering if you feel that using Gender Studies was somehow sexist. [0] http://www.slate.com/articles/business/moneybox/2014/07/employment_rates_for_stem_ph_d_s_it_s_a_stagnant_job_market_for_young_scientists.html http://www.slate.com/articles/business/moneybox/2014/07/empl...

rcoder 11y ago
I know I'm feeding the trolls here, but this just demands an answer: "Given the data is 3 years out of date, it's possible employment rate has jumped to 63% (the highest its been since 1998!) and that 14% is exactly on-par for the course for having no gender discrimination (against or in favor of) women." This is basically middle-school level math and you're doing it wrong. Whatever percentage of newly-minted CS PhDs go on to teach, the ratios of men and women working as professions should be roughly the same as those earning degrees: 78% and 22%, respectively. Instead, it appears that a disproportionate number of women are "somehow" not ending up in teaching positions. In a truly fair world those numbers would be much closer to 50/50, but that's a separate discussion.
- Nadya 11y ago
  Wow, I had a mental failure there (way to add up to 50% instead of 100% Nadya!) I apologize for that and thank you for pointing out that bullshit. Juggling work and a few convos and did indeed make a major blunder in my math there. (Embarrassingly so...) >In a truly fair world those numbers would be much closer to 50/50, but that's a separate discussion. This completely disregards any and all preference for genders when it comes to these positions. There are personal preference for jobs and only in a truly unfair and heavily regulated world that does not account for human factors and gender preferences would it ever be 50/50.
- oldmanjay 11y ago
  Sighing in text and accusing people of trolling make me assume your point needs bolstering by emotional resonance. Your hypothesis of naive proportions may well be correct, but you certainly didn't make much an argument beyond stating the premise. I personally see no particular reason that interest in engineering has a need to be distributed equally across any human grouping. Fairness as a concept aside, there are clear differences in humans that are driven by gender. Desiring to assume these differences can't affect interests is fine, but it's far from proven by any empirical data. In fact, this article potentially contradicts that notion with actual numbers - although it's impossible to draw a line between inbuilt differences and external influence here.

by Nadya 11y ago

rcoder 11y ago

I know I'm feeding the trolls here, but this just demands an answer: "Given the data is 3 years out of date, it's possible employment rate has jumped to 63% (the highest its been since 1998!) and that 14% is exactly on-par for the course for having no gender discrimination (against or in favor of) women." This is basically middle-school level math and you're doing it wrong. Whatever percentage of newly-minted CS PhDs go on to teach, the ratios of men and women working as professions should be roughly the same as those earning degrees: 78% and 22%, respectively. Instead, it appears that a disproportionate number of women are "somehow" not ending up in teaching positions. In a truly fair world those numbers would be much closer to 50/50, but that's a separate discussion.

Nadya 11y ago
Wow, I had a mental failure there (way to add up to 50% instead of 100% Nadya!) I apologize for that and thank you for pointing out that bullshit. Juggling work and a few convos and did indeed make a major blunder in my math there. (Embarrassingly so...) >In a truly fair world those numbers would be much closer to 50/50, but that's a separate discussion. This completely disregards any and all preference for genders when it comes to these positions. There are personal preference for jobs and only in a truly unfair and heavily regulated world that does not account for human factors and gender preferences would it ever be 50/50.
oldmanjay 11y ago
Sighing in text and accusing people of trolling make me assume your point needs bolstering by emotional resonance. Your hypothesis of naive proportions may well be correct, but you certainly didn't make much an argument beyond stating the premise. I personally see no particular reason that interest in engineering has a need to be distributed equally across any human grouping. Fairness as a concept aside, there are clear differences in humans that are driven by gender. Desiring to assume these differences can't affect interests is fine, but it's far from proven by any empirical data. In fact, this article potentially contradicts that notion with actual numbers - although it's impossible to draw a line between inbuilt differences and external influence here.