I do not think standardized tests or even grades are the "sole valid metric". But I think weird secondary essays are virtually useless other than as a figleaf for adcoms to give a boost to whomever they like.
It seems like you are focusing on just a few medical schools out of many, and along the way, assuming your conclusion. Your observation began by pointing out differences in means across racial demographics, and you effectively said, "Aha, that proves discrimination!" For discrimination to be the prevalent cause, it would have to encompass the vast majority of the variance in the data. Yet you consistently handwave away any discussion of legitimate variance. You rinse and repeat: assume your conclusion as the only explanation for the differences. There doesn't seem to be a serious attempt to discuss the data or test alternative hypotheses; you just repeat your assumption.
To test this mathematically, I ran a simulation of a medical school similar to the Medical College of Georgia (MCG). Interestingly, this school accepts very few non-residents (~98% are in-state), which underscores the point again about geographic enrollment constraints. Using recent data, we have about 1,821 in-state US citizen and permanent resident applicants competing for roughly 304 enrollment spots.
Even assuming every medical school applicant in Georgia applies to this school, we can use the national MCAT and GPA means and standard deviations for each racial cohort to accurately represent the baseline applicant pool.
Then, I ran a holistic admissions committee scoring algorithm on that simulated pool. I made it 100% race-blind, and to your favor, I completely excluded any "mission fitness" variables or simulated questions about SES/economic adversity. The algorithm simply uses MCAT and GPA (accounting for the fact that the two are correlated, so they aren't completely independent) and adds three other completely race-blind metrics--it doesn't matter if they represent transcripts, recommendations, clinical work, community service, secondary essays, or interviews. That is 5 metrics weighted equally. ZERO "mission fitness," meaning no evaluations about where someone's career might take them (which would naturally give a fair aggregate advantage to Black and Hispanic applicants over White and Asian applicants). Just a pure, strictly race-blind holistic score.
The result? Black applicants still get accepted. Hispanic applicants still get accepted. And a significant gap between their MCAT means still naturally emerges. For example,
Asian matriculants can still have a 7.0+ higher MCAT mean over Black matriculants even under a strictly race-blind admissions algorithm.
This experiment isn't about whether or not I have found the exact proprietary weighting parameters that Georgia uses--I probably haven't. It's about mathematically proving that
multi-variate admissions packages are a major driver of the statistical differences you claimed are absolute proof of widespread discrimination.
Finally, this once again goes back to what
Jimmy Higgins wrote: broadly speaking, acceptance rates correlate with the MCAT means for the national demographics. Explaining the remaining variance is simply a matter of statistics skill, not assuming a national conspiracy.