5 ms·

This reminds me of an interesting Harvard study I read a few years ago titled 'Are Emily and Greg More Employable than Lakisha and Jamal'. It can be found here

This reminds me of an interesting Harvard study I read a few years ago titled 'Are Emily and Greg More Employable than Lakisha and Jamal'. It can be found here: https://scholar.harvard.edu/files/sendhil/files/are_emily_and_greg_more_employable_than_lakisha_and_jamal.pdf https://scholar.harvard.edu/files/sendhil/files/are_emily_an...

eli 8y ago
There's another famous study where tenure committees members ranked CVs with traditionally male names on them better than ones with traditionally female names. https://link.springer.com/article/10.1023%2FA%3A1018839203698 https://link.springer.com/article/10.1023%2FA%3A101883920369...
iguy 8y ago
IIRC this was one of the studies whose name list was criticised for having a lot of class differences as well as claimed race differences: when the authors sat down to invent white- and black-sounding names, they picked high-class and low-class names, thus injecting their own stereotypes into their data.
- VikingCoder 8y ago
  I saw another study where they found phone numbers for mental health professionals, and they called and left a message, asking someone to call them back to set up a first appointment. The had other people rate the voices as "sounds black" / "sounds white," and "sounds white-collar" / "sounds blue-collar." That way, they measured the correlation between "sounds black" and "doesn't get call backs." As you can imagine, "white" sounding people got more call backs. And "white-collar" sounding people got more call backs. I don't know if they reported which was more beneficial, sounding white, or white-collar. My point being, if you have a large enough collection of names, and you measure how the candidate appears to them, you can then correlate the appearance with the outcome, showing the bias against that appearance. You don't need to have the researchers generate their own candidates.

eli 8y ago

There's another famous study where tenure committees members ranked CVs with traditionally male names on them better than ones with traditionally female names. https://link.springer.com/article/10.1023%2FA%3A1018839203698 https://link.springer.com/article/10.1023%2FA%3A101883920369...

iguy 8y ago

IIRC this was one of the studies whose name list was criticised for having a lot of class differences as well as claimed race differences: when the authors sat down to invent white- and black-sounding names, they picked high-class and low-class names, thus injecting their own stereotypes into their data.

VikingCoder 8y ago
I saw another study where they found phone numbers for mental health professionals, and they called and left a message, asking someone to call them back to set up a first appointment. The had other people rate the voices as "sounds black" / "sounds white," and "sounds white-collar" / "sounds blue-collar." That way, they measured the correlation between "sounds black" and "doesn't get call backs." As you can imagine, "white" sounding people got more call backs. And "white-collar" sounding people got more call backs. I don't know if they reported which was more beneficial, sounding white, or white-collar. My point being, if you have a large enough collection of names, and you measure how the candidate appears to them, you can then correlate the appearance with the outcome, showing the bias against that appearance. You don't need to have the researchers generate their own candidates.