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Not accounting for race comes up in scary ways. I was part of a program that used a totally neutral database (race/gender were not in the database). People wer

Not accounting for race comes up in scary ways. I was part of a program that used a totally neutral database (race/gender were not in the database). People were selected by criteria and then emailed asking them to attend an introduction meeting online. Only when the webcams were turned on did we realize nearly every volunteer was none-white female. It was a very bad look. It seemed that we had selected them based on race/gender when in reality that data wasnt availible until the first video call. By ignoring race/gender we had somehow made it the most obvious selector. (The program involved having children who were in regular contact with the criminal justice system.)

_heimdall 2y ago
Did it turn out that the selection process actually didn't represent the makeup of the target audience? If the participants did represent a subset of the target audience, I don't really see what the problem is if that audience happens to be heavily weighted towards a particular race, sex, etc. It seems like you'd be doing a disservice to the program to purposely control for those factors and end up with a population that physically looks more diverse at the cost of missing people who actually most need the program.
- pessimizer 2y ago
  A lot of people have gotten into a weird place where they think that acknowledging that the descendants of slaves in the US are in a dire situation is a form of racism. Acknowledging that being injured has caused an injury has become either extreme right-wing bigotry (if you're a liberal who demands that every subset of people be a racially representative mix), or "the soft bigotry of low expectations" (if you're a conservative who can't admit to yourself that you inherited hundreds of thousands of dollars from a parent who also paid for your private school, car, and rent, then found you your first job.)
  - _heimdall 2y ago
    Sure, there are a lot of interesting and compelling angles to consider why these kinds of things happen. In such a specific case as the parent comment here, it really is more interesting in my opinion to see what was found. For example, it stood out to the team that they group of people that were on the call paint a certain picture when considering how similar they were (specifically by surface-level factors like race or sex). Is that response justified when they dug in and found that the group didn't represent a similar makeup of the total population despite having completely ignore sex and race? Or did it turn out that the population is actually that homogenous? If it is that homogenous there are great questions to dig deeper on, like why that happened and what may be done to help correct that.
- godelski 2y ago
  It's not racist show, point out, or claim that data racially skews in one direction. If that were true, then you couldn't even claim that minorities are under privileged. Right? Then how could you help them if you aren't able to recognize the areas that the biggest challenges? You're right when interpreting this way. But the thing you do care when you want to attribute causality. In part this is an issue because people naturally associate correlation with causation (there is good reason but that's a long discussion. See Judea Pearl's The Book of Why). At the end of the day, we really are always after causal relationships, because we want to do things with the data (somewhere along the chain). So it's not that you want to remove race from data, but rather that you want to be wary and ensure that your variable is not confounding the real issue. Though this happens outside of race too. And note that at times there where race does play a causal role. (I suspect not likely in the parent's case) For example, different races may be more prone to certain illnesses or genetic disorders. If it helps, maybe it is easier to frame it as it's easy to be lazy, but the pressure around race makes us more likely to revisit our analysis and look for confounding variables. The thing is, this will improve your stats even for the non-minority settings because the truth of what you're (hopefully) doing, is just making better models.
  - _heimdall 2y ago
    I think we're getting at roughly the same idea here, I don't actually think its about racism at all though. The parent commenter clearly didn't select a population based in their race or sex. This may be an unpopular opinion, but I have always viewed racism as very much linked to the person's intent, something that may unintentionally have a bias isn't racist in my book and really lumping it in would cheapen the argument when the intent really was there. That said, in this case I really am curious if it turned out that there was an unintentional bias somewhere. Say they ended up with 90% black women and in reality that is only say 40% of the total population of kids with regular interactions with the judicial system. There's certainly something there they missed and it'd be interesting data to understand how that happened even when they purposely ignored race and sex. It usually boils down to an otherwise benign detail of the selection process that makes way more of an impact than would have been expected.
    - 2y ago
lapphi 2y ago
I think it’s more reflective of the reality of living in the US than of your company’s selection process. I’m curious what you did after realizing this. Did you pivot away, or create a program designed to be useful for the volunteers? Assuming that the volunteer pool accurately represented the larger group.

_heimdall 2y ago

Did it turn out that the selection process actually didn't represent the makeup of the target audience? If the participants did represent a subset of the target audience, I don't really see what the problem is if that audience happens to be heavily weighted towards a particular race, sex, etc. It seems like you'd be doing a disservice to the program to purposely control for those factors and end up with a population that physically looks more diverse at the cost of missing people who actually most need the program.

pessimizer 2y ago
A lot of people have gotten into a weird place where they think that acknowledging that the descendants of slaves in the US are in a dire situation is a form of racism. Acknowledging that being injured has caused an injury has become either extreme right-wing bigotry (if you're a liberal who demands that every subset of people be a racially representative mix), or "the soft bigotry of low expectations" (if you're a conservative who can't admit to yourself that you inherited hundreds of thousands of dollars from a parent who also paid for your private school, car, and rent, then found you your first job.)
- _heimdall 2y ago
  Sure, there are a lot of interesting and compelling angles to consider why these kinds of things happen. In such a specific case as the parent comment here, it really is more interesting in my opinion to see what was found. For example, it stood out to the team that they group of people that were on the call paint a certain picture when considering how similar they were (specifically by surface-level factors like race or sex). Is that response justified when they dug in and found that the group didn't represent a similar makeup of the total population despite having completely ignore sex and race? Or did it turn out that the population is actually that homogenous? If it is that homogenous there are great questions to dig deeper on, like why that happened and what may be done to help correct that.
godelski 2y ago
It's not racist show, point out, or claim that data racially skews in one direction. If that were true, then you couldn't even claim that minorities are under privileged. Right? Then how could you help them if you aren't able to recognize the areas that the biggest challenges? You're right when interpreting this way. But the thing you do care when you want to attribute causality. In part this is an issue because people naturally associate correlation with causation (there is good reason but that's a long discussion. See Judea Pearl's The Book of Why). At the end of the day, we really are always after causal relationships, because we want to do things with the data (somewhere along the chain). So it's not that you want to remove race from data, but rather that you want to be wary and ensure that your variable is not confounding the real issue. Though this happens outside of race too. And note that at times there where race does play a causal role. (I suspect not likely in the parent's case) For example, different races may be more prone to certain illnesses or genetic disorders. If it helps, maybe it is easier to frame it as it's easy to be lazy, but the pressure around race makes us more likely to revisit our analysis and look for confounding variables. The thing is, this will improve your stats even for the non-minority settings because the truth of what you're (hopefully) doing, is just making better models.
- _heimdall 2y ago
  I think we're getting at roughly the same idea here, I don't actually think its about racism at all though. The parent commenter clearly didn't select a population based in their race or sex. This may be an unpopular opinion, but I have always viewed racism as very much linked to the person's intent, something that may unintentionally have a bias isn't racist in my book and really lumping it in would cheapen the argument when the intent really was there. That said, in this case I really am curious if it turned out that there was an unintentional bias somewhere. Say they ended up with 90% black women and in reality that is only say 40% of the total population of kids with regular interactions with the judicial system. There's certainly something there they missed and it'd be interesting data to understand how that happened even when they purposely ignored race and sex. It usually boils down to an otherwise benign detail of the selection process that makes way more of an impact than would have been expected.
  - 2y ago

lapphi 2y ago

I think it’s more reflective of the reality of living in the US than of your company’s selection process. I’m curious what you did after realizing this. Did you pivot away, or create a program designed to be useful for the volunteers? Assuming that the volunteer pool accurately represented the larger group.