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by Mangalor 4402 days ago
> a company that is clearly not actively discriminating based on race

1. There's no way to tell whether they are or aren't just from exposing this data.

2. Racism/Sexism is discussed a lot in American culture, but I fail to see how "ignoring" actual data (which Google is proactively choosing to share) would somehow fix these issues.

2 comments

Forgot to mention that these questionnaires themselves are at fault - they perpetuate the concept of "race" while we should know better in the 21st century that races are an invention of the 18-19th Century. Look at actual genetic differences between people, and while you may certainly define subgroups here and there, it's certainly not as simple as having a dozen of groups defined mostly by the color of your skin and your appearance.

Races are BS, period. So these questionnaire make the BS go on and on.

2. The problem when you talk about the data is that you fix yourself on numbers, you try to set objectives and you end up with quota, instead of actually understanding that's the underlying problem.

You don't and you shouldn't start addressing these issues with numbers.

Numbers allow us to identify problems. Without numbers, there are no problems, so there are no issues to address; I see how that would solve the problem!
> Numbers allow us to identify problems.

The problem is in these sorts of cases the numbers are generally useless. Even if we eliminated 100% of all racial discrimination from society, fewer African Americans would attend college because fewer of their parents can afford to send them, and those type of consequences would carry down for generations completely regardless of continuing racism.

So you say you want to stick with the numbers anyway and try to account for income level. OK boss, that will reduce your confidence interval by a good bit but we can do it. The trouble is poverty is not the only issue. The fertility rates are different. African Americans on average have more children than whites and Asians according to the most recent census (2.1 vs. 1.8), so for the same parental income level the money is split between more children, as is parental time and attention. African Americans are also significantly more likely to grow up in single parent families. That one's 65% for African Americans vs. 23% white and 16% Asian. Ouch. So we have to account for that stuff too. And those all interact. If you have three children being raised by one parent making $30,000/year as compared with two children being raised by two parents each making $50,000/year, expecting to get anything resembling the same results is bonkers.

> Even if we eliminated 100% of all racial discrimination from society, fewer African Americans would attend college because fewer of their parents can afford to send them, and those type of consequences would carry down for generations completely regardless of continuing racism.

Precisely. The issue with numbers is that people will focus on numbers and make the conclusions that "as long as it's not 50/50, it means there is some RACISM at work somewhere" without understanding the underlying causes.

It's ALWAYS the same issue with numbers and statistics: used in the wrong context, you can manipulate them to say what you want to say, instead of using numbers to explain the truth.

That's pseudo science at best.

Experiments through data are by no means impossible when it comes to race or gender. That's the lifeblood of social science. Throwing your hands up and saying "too many numbers! no conclusions could ever be possibly found!" would be completely unacceptable in any other discipline. You're now picking and choosing which fields can even use basic statistics.
> Experiments through data are by no means impossible when it comes to race or gender. That's the lifeblood of social science.

It's also why hard science majors make fun of them.

> Throwing your hands up and saying "too many numbers! no conclusions could ever be possibly found!" would be completely unacceptable in any other discipline.

That's because just about any other discipline is capable of conducting a controlled experiment. The problem with statistics in social sciences is that you don't control anything. You can't just order families of a particular race to stop having more or less children than other races so that you can get a good control group, so you have no control group. You only have data from something you hope is a reasonable approximation of a control group, without even any good way to tell when it isn't.

> It's also why hard science majors make fun of them.

Hard science recognizes social science work when solid data is used and the methodology is well understood and effective. You're generalizing.

> That's because just about any other discipline is capable of conducting a controlled experiment

> You can't just order families of a particular race to stop having more or less children than other races so that you can get a good control group, so you have no control group.

You look at families of a race that had less children and compare them to families of the same race with more children. That would be a data experiment controlled for race. Read Freakonomics if you want to understand data experiments better.

> That's because just about any other discipline is capable of conducting a controlled experiment. The problem with statistics in social sciences is that you don't control anything.

Statistical controls are real controls, and are frequently used not only in social sciences, but in so-called "hard" sciences for large, complex, or distant systems that can't be conveniently be set up in a laboratory. Laboratory-style control is one particularly convenient mechanism for isolating particular independent variables, but its not a defining requirement of empirical science.

> Without numbers, there are no problems

Who said that? Of course you can identify problems without having any number. That's called qualitative understanding.

How does unbiased qualitative reasoning work if counting isn't allowed. Genuinely curious, citations would be helpful.

In science, we call out qualitative reasoning as being biased and unscientific.

> In science, we call out qualitative reasoning as being biased and unscientific.

Ha! I'm a scientist by training, and your claim makes me smile. Most of Science starts by qualitative reasoning and observation. It's because you notice phenomena that you emit hypotheses as to why they occur, and then you design experiments to generate data and verify your hypothesis (i.e. whether your qualitative understanding is correct or not).

Right, we use qualitative reasoning at the beginning and try to temper our biases separately, but how can you do unbiased evaluation without numbers? Even the social sciences has to rely at numbers and statistics eventually.