Around half of the US population has hypertension.
I’m guessing you wouldn’t want your doctor just assuming you have it and start treating it though.
The reason why stereotypes are bad is because even if there’s aggregate data trends on a broad population basis, that doesn’t necessarily translate to individualized specifics.
In my high school, I was in Calculus BC in my senior year, along with most of the other smartest kids in my grade.
One of the few black students at my prep school had been in that class in his junior year and for his senior year just sat one on one with the math teacher because he was a full year ahead of us. He was also the student that I used to get the most competitive with playing chess in the student lounge (because he was legit better than me and the few victories I’d eek out were actual accomplishments), and was the one of my friends to go off to Stanford.
It’d be a real shame if someone looking at him decided that based on broad statistics relating to the melanin in his skin that he wasn’t as good at math as someone with less melanin.
And personally, I’d think anyone making that leap of logic was a goddamn moron.
(Also, pro tip - it’s worth thinking about the differences between averages and distributions around those averages if you are going to make an argument for there being merit in extrapolating from statistics. For example, you are more likely to be told by a mother with a child that the father is not in the picture by a white mother than a black mother if you ask the question of every mother you see.)
Around half of the US population has hypertension.
I’m guessing you wouldn’t want your doctor just assuming you have it and start treating it though.
I have to disagree with a reply to this before me because I think this example doesn’t do the comment about statistics mentioned above justice.
You don’t want your doctor to treat you for hypertension, but you want him to check you for it to catch it early if you have it if you fall into a category that makes it more likely you have hypertension. This does not mean he should ignore the possibility of a disease in a non-high-risk group either.
Equally, black students being statistically speaking worse at math does not mean you should look at a black student and assume he is bad in math. But it can mean that funding for programs targeted at helping minority students going to math tutoring can be better justified.
I will not argue that based on statistics you should make assumptions about people, hell no. This is obviously racist. But assuming statistics (and being aware of them) are first and foremost racist would just be equally wrong.
The phrasings in the meme can be described as racist. But the structural problems that racism created and that lead to these assumptions cannot be fought by ignoring them.
But it can mean that funding for programs targeted at helping minority students going to math tutoring can be better justified.
But this ignores the issue of frequency I hint at in the bottom parenthetical.
Let’s say for the sake of argument black students are 2x as likely as white students to fail a math class and need to retake it.
Breaking it out by racial cross tabs may well suggest a policy of adding a math support program exclusively for black students.
The problem is that at a frequency basis, (0.616 times X) > (0.121 times 2X). So your well intentioned program just excluded a greater number of students that are going to fail math than the number of students you are going to include.
A better approach would be to identify what students are struggling with math irrespective of their melanin, and ensure adequate resources are tailored to them.
The only way a melanin specific math program makes sense is if the specific factors relating to why a given student is struggling with math is unique to their melanin such that a broader program focused on math won’t address those issues.
But even in terms of unique causes or factors, my guess is that the melanin specific crosstab is a poor metric selection, as it simply correlates with multiple other factors which more closely track with performance, such as household income levels, parent availability at home, parent education levels, etc.
So a program that was focused instead on things like “math support for kids who don’t have a parent who has high school math level competency at home” is going to be much more successful for many more students than one focused on “students with a lot of melanin who are struggling with math.”
It’s a shitty metric that persists because it’s easy to classify and because for some things it is a causative factor in and of itself (such as criminal injustice).
Around half of the US population has hypertension.
I’m guessing you wouldn’t want your doctor just assuming you have it and start treating it though.
The reason why stereotypes are bad is because even if there’s aggregate data trends on a broad population basis, that doesn’t necessarily translate to individualized specifics.
Statistically, black math scores are worse than white.
In my high school, I was in Calculus BC in my senior year, along with most of the other smartest kids in my grade.
One of the few black students at my prep school had been in that class in his junior year and for his senior year just sat one on one with the math teacher because he was a full year ahead of us. He was also the student that I used to get the most competitive with playing chess in the student lounge (because he was legit better than me and the few victories I’d eek out were actual accomplishments), and was the one of my friends to go off to Stanford.
It’d be a real shame if someone looking at him decided that based on broad statistics relating to the melanin in his skin that he wasn’t as good at math as someone with less melanin.
And personally, I’d think anyone making that leap of logic was a goddamn moron.
(Also, pro tip - it’s worth thinking about the differences between averages and distributions around those averages if you are going to make an argument for there being merit in extrapolating from statistics. For example, you are more likely to be told by a mother with a child that the father is not in the picture by a white mother than a black mother if you ask the question of every mother you see.)
I have to disagree with a reply to this before me because I think this example doesn’t do the comment about statistics mentioned above justice.
You don’t want your doctor to treat you for hypertension, but you want him to check you for it to catch it early if you have it if you fall into a category that makes it more likely you have hypertension. This does not mean he should ignore the possibility of a disease in a non-high-risk group either.
Equally, black students being statistically speaking worse at math does not mean you should look at a black student and assume he is bad in math. But it can mean that funding for programs targeted at helping minority students going to math tutoring can be better justified.
I will not argue that based on statistics you should make assumptions about people, hell no. This is obviously racist. But assuming statistics (and being aware of them) are first and foremost racist would just be equally wrong.
The phrasings in the meme can be described as racist. But the structural problems that racism created and that lead to these assumptions cannot be fought by ignoring them.
But this ignores the issue of frequency I hint at in the bottom parenthetical.
Let’s say for the sake of argument black students are 2x as likely as white students to fail a math class and need to retake it.
Breaking it out by racial cross tabs may well suggest a policy of adding a math support program exclusively for black students.
The problem is that at a frequency basis, (0.616 times X) > (0.121 times 2X). So your well intentioned program just excluded a greater number of students that are going to fail math than the number of students you are going to include.
A better approach would be to identify what students are struggling with math irrespective of their melanin, and ensure adequate resources are tailored to them.
The only way a melanin specific math program makes sense is if the specific factors relating to why a given student is struggling with math is unique to their melanin such that a broader program focused on math won’t address those issues.
But even in terms of unique causes or factors, my guess is that the melanin specific crosstab is a poor metric selection, as it simply correlates with multiple other factors which more closely track with performance, such as household income levels, parent availability at home, parent education levels, etc.
So a program that was focused instead on things like “math support for kids who don’t have a parent who has high school math level competency at home” is going to be much more successful for many more students than one focused on “students with a lot of melanin who are struggling with math.”
It’s a shitty metric that persists because it’s easy to classify and because for some things it is a causative factor in and of itself (such as criminal injustice).
I really like your hypertension/doctor example, it’s a useful way to frame things. Thanks for sharing.