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With my current understanding, I believe I can answer this one. It's #2. Specifically, your parenthetical comment in #2. Bias exists and is a problem. It is wo
by sfink 7y ago
With my current understanding, I believe I can answer this one. It's #2. Specifically, your parenthetical comment in #2.
Bias exists and is a problem. It is worth spending additional resources to draw additional samples from the underrepresented population in order to offset that bias. With more samples from that population than the previous pipeline stage would provide if you sampled evenly, you can counter some of the bias without adjusting any standards of quality (capability) based on the population being sampled.
If you are a member of the overrepresented population, you will have a smaller chance of being hired with this intervention. But for someone who is hired, their skill level will be independent of what population they belong to. (Women will not be given an easier interview. They will be more likely to be offered an interview in the first place.)
Whether that is "fair" depends entirely on how you define fairness. This procedure stacks the odds against a man. Our current overall system stacks the odds against a woman. Both can legitimately complain about unfairness.
Thus, it's largely irrelevant that the percentages in earlier stages of the pipeline mean that there's no way for the overall balance can reach 50/50 through only later-stage interventions. Where did this magic 50% figure come from? The only point is to improve the percentage from where it is now. The issues that prevent achieving 50% are real, but don't prevent progress anywhere in the pipeline.
I imagine the additional costs of sampling more from a smaller population would rise dramatically the closer you try to push the outcome towards 50%. So companies will have to decide how much they're willing to invest. Fortunately, there is still real value in pushing beyond the status quo even if you don't get to 50%.
(More generally, the magic number is not always 50%. It's the proportion of the URM in the overall population. 50% is roughly the female part of the population in areas advanced enough to have these sorts of jobs available.)
- drdeca 7y agothank you, that seems like a plausible idea to me. It also seems possible to me that such an intervention might reduce feedback loops which cause the bias in the input anyway. Like, if women who are aware that a smaller proportion of the people employed in a field are women than the proportion of people in the population, maybe they might see that as a factor weighing against picking that field as one to go into? (of course, some might find it a reason to pick that field. I just mean that it seems possible that there is such an effect on average), and so, the #2 intervention might reduce such a feedback loop problem, if such feedback loops do exist.
- sfink 7y agoRight. And those feedback loops do very much exist -- you can find plenty of women sharing their experiences of what it feels like to be the only woman in a room full of men. Over and over again. Being an "only" is rough. I'd imagine that going from 2 to 3 in a group is a much, much smaller change. It also means that success often requires acting like a man, even when that is neither natural nor optimal for the situation. That's one reason why more than minimal diversity helps -- if there is a benefit to be had from diversity, you may not get it from having an "only" who is pressured to fit in.