SAT Math by race [1] :
- Asian/Pacific Islander = 598
- White = 534
- Mexican American = 461
- Black = 429
SAT Math by gender [2] :
- Men = 537
- Women = 503
This is not the way to an open-minded and open-hearted discussion about the truth; it's a tangent to yet another generic ideological flamewar. That violates the HN guidelines.
Since you've done this repeatedly before and don't appear to have any other purpose in commenting here, we've banned your account. Please stop creating new accounts to break the HN guidelines with.
And banning for a post that provides evidence is ridiculous. You should apply for a government job in Turkey.
Racism implies an overarching ideology. A true racist would say something like, "White employees are better than black employees."
Y Combinator has never suggested that minorities are categorically better employees. Preferring to hire from minority groups has many benefits unrelated to race: increased diversity boosts profits[1], for starters. There's a huge difference between racism (trying to keep minorities out of your office) than what you're calling "reverse racism" (trying to have a diverse office).
1. https://www.sciencedaily.com/releases/2009/03/090331091252.h...
The claim that race doesn't exist is simply false. We can talk about whether or not it's useful to make policy decisions based on race, but if we're respecting the data, we can't say that there are no coherent human population groupings smaller than homo sapiens or that these groups do not align with traditionally-understood "race".
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1196372/
It's incredibly frustrating to see well-intentioned people just flatly deny facts about the world. The mistrust and resentment this denial causes makes it much more difficult to get useful messages across.
My assertion is that everyone is a mixture, which is true. People exist on a continuum of race without discrete borders[2].
1. http://www.scientificamerican.com/article/race-is-a-social-c...
2. http://www.nature.com/ng/journal/v36/n11s/full/ng1435.html
The issue 'race is correlated with X' is not materially affected by how exactly race (especially its borders) is defined and taxonomical problems - it's important in it's own regard, but in this regard, it's not the core problem, it's a red herring distracting from the core question of "does race affect X'; and that question is the same, with the same answers, no matter if in your analysis you choose to model race as discrete borders or as a continuum.
If your test can accurately group "Hispanics" which no-one actually claims is a race, then it doesn't prove that any other grouping it finds is a "race", however that is defined.
The SAT scores provided by the parent comment is official data. It is not "data" as you connote it to be. Just follow the Government stats linked he published.
The conclusion of the parent comment is not unwarranted. Tech companies pride themselves in hiring only the best and there is strong statistical correlation between SAT scores or any other standardization test vs academic/professional performance.
Tech companies want the best now, it doesn't matter if some group of people are best due to inherent awesomeness or lot of privilege or both or neither. Similarly it doesn't matter if some group of people are not among the best due to financial hardship in their families, racial biases against them.
In the current paradigm, tech companies should either hire the best or hire for diversity. They cannot do both until the underlying society has already changed.
Is pointing out racial/gender differences in SAT scores or IQ tests or in hiring at Facebook/Google/Amazon/Microsoft equivalent to being a racist?
First, you can't simply reslice the data and think you have shown anything valid. Simpson's paradox and all that. It could be that women do better than men in all but one race, for example, and that race "brings the average down" to the point where the overall gender scores look like they do. In fact, if you look at the wikipedia article on simpson's paradox, it gives the great example of .. a gender bias study :)
Whoever is creating these numbers by confounding variables and grouping data from other studies is just making a mess of the original data :(
(This is sadly not uncommon, and happens a ton in race and crime statistics, etc. The folks who make the original data often go to great pains to explain their methodologies, etc, and then some random org just throws it all in excel so they can produce charts that support whatever, and acts like anything they do to the data makes it still valid)
Second, ignoring that serious issue for a second, The only thing this gives you is "a snapshot of the world today". This is a test of actual current performance trying to predict success, not trying to predict potential performance. The SAT gives no data on what innate ability is, nor does it try to. That means it can change, and you can improve the numbers.
[1] i'm pretty sure the main correlation the SAT shoots for, and succeeds at, is predicting whether folks will be "successful the first year of college". There are a number of studies that show this. There are also newer, but less studies, that show other predictors may be just as good.
This list also says nothing about cause/effect. Do the scores represent innate aptitude, or rather the result of a lifetime of societal biases?
Not just societal biases, but simple demographic realities that are not controlled for at all looking solely at scores on a test.
And there's more too it, of course. I chose this link primarily because I found another observation very interesting: "In many studies, [the] mother’s education [level] had a more significant effect on children’s scores than income."
Equating inborn aptitude to SAT scores alone seems very short-sighted.
However, stereotype threat is not the only mechanism that fits the poster's description. Most Americans, upon hearing that I'm a mathematician, say, "I hate math! and I suck at it." Then they stare at me hostilely or say, "You must be really smart." There's a little subset of 40-65 year old women, though, who say wistfully, "I loved math and it was my best subject... but... in high school they said I wouldn't need it so I couldn't take the calculus class, I had to take typing instead..." Tracking in high school is used extensively and dissuades people tracked into crappy high school STEM classes from pursuing STEM degrees in college (or getting in at all).
You are also ignoring the effects of changing environment which those numbers disregard. For example, we know blacks disproportionately come from low income backgrounds with higher crime and a "rough" home life, which can affect a childs ability to effectively study and learn. That's not because they're genetically black as you allude, that's because they grew up in that environment. Your data does not capture or ignores this crucial variable and you should stop pushing it.
Also, aptitude for mathematics and aptitude for tech aren't directly correlated, though there is likely to be some overlap.
- Asian/Pacific Islander = 29.6%
- White = 26.4%
- Mexican American = 22.8%
- Black = 22.1%
- Men = 51.6%
- Women = 48.4%
In other words, roughly equal numbers of all of the demographics (specifically _not_ an overwhelming majority of White Men).
So even if your argument were valid it seriously undermines your point.
My calculations are completely garbage, and I would withdraw the comment but it looks like I can't at this point.
My calculations are completely garbage, and I would withdraw the comment but it looks like I can't at this point.