I think what GP said was logical. Imagine Harvard has 3 entrance criteria, and the criteria a student receives depends on the first letter of their first name:
* A name: must be in top 1% of test scores
* B name: must be in top 5% of test scores
* C name: must be in top 10% of test scores
The following 3 students are admitted:
* Allison (is in top 1%)
* Brian (is in top 4%)
* Caitlin (is in top 1%)
We can only safely assume that Allison is in the top 1% because her criteria certifies it. Even though Caitlin in actuality is in the top 1%, because her entrance criteria is more lax, we are not sure.
I think this is one downside of affirmative action, people are unsure if a person passes based on affirmative action or purely on merit. Now we consider the upsides and downsides of affirmative action, and decide whether it should be implemented.
Yes, I understand that affirmative action can have this consequence. I am not arguing for or against affirmative action. I am pointing out that it should not matter whether someone has an A, B, or C name when applications are being triaged. Because Allison, Brian and Caitlin all have the same credentials, they should be viewed as equally likely candidates.
Making assumptions about them based on probabilities is exactly the problem here, and it is one that we can easily avoid.
* A name: must be in top 1% of test scores
* B name: must be in top 5% of test scores
* C name: must be in top 10% of test scores
The following 3 students are admitted:
* Allison (is in top 1%)
* Brian (is in top 4%)
* Caitlin (is in top 1%)
We can only safely assume that Allison is in the top 1% because her criteria certifies it. Even though Caitlin in actuality is in the top 1%, because her entrance criteria is more lax, we are not sure.
I think this is one downside of affirmative action, people are unsure if a person passes based on affirmative action or purely on merit. Now we consider the upsides and downsides of affirmative action, and decide whether it should be implemented.