MCATs, Affirmative Action, and DEI, Oh My

[Don2 (Don1 Revised)]

I don’t see how you can actually know that is in fact an accurate statement.

Asked and answered. In brief: statistically, it is pretty much impossible for it to be due to chance. So it's either discrimination or some other factor that is relevant to admissions and where blacks and Hispanics best whites and Asians. Nobody here has even attempted to identify such a a factor, much less provide any evidence for it. So, discrimination is a logical conclusion.

I actually did and mentioned this plausible factor several times. I even did so recently in a post to you. You did not reply. Perhaps you missed it. It happens.

I shared earlier about who actually works in underserved areas (which includes rural areas): Asians and Whites were at the bottom. Native Americans were the highest in all underserved locations, followed by Blacks and Hispanics. So theoretically, if a demographic's acceptance rate is tied to fulfilling a public good, the formula isn't just about scores. It looks more like: Acceptance rate = f(MCAT, GPA, Mission Fitness)

Of course, admissions committees look at far more than just this, but I am bringing it up because it is a significant explanatory variable that behaves roughly in an opposing direction to the MCAT mean differences across your division of groups.

Emphasis added. "earlier" is in reference to another post.

This blurb comes from the second study I linked, which looks at practice patterns nationally:

There are also significant difference in geographic distribution across primary care specialties with family physicians and general practitioners overall having higher proportion practicing in HPSA, MUA/P, and rural areas in the study cohort (see Figures 2 through 4). Among primary care physicians as a whole, substantial racial/ethnic differences exist in how they distribute geographically (p < .0001). Black, Native American, and Hispanic groups have higher proportions practicing in HPSA, MUA/P, and rural areas compared with White primary care physicians and the Asian group, who have smaller proportions practicing in these areas. Within each primary care specialty, significant differences by race and ethnicity (p < .0001) also exist across the geographies. Black, Native Americans, and Hispanic groups have higher proportions practicing in HPSA and MUA/P than their White peers in all three primary care specialties. Native American primary care physicians have the highest proportion practicing in rural areas, whereas White primary care physicians have higher proportions practicing in rural areas compared with Black or Hispanic primary care physicians. In particular, the Native American primary care physicians have high proportions practicing in all three underserved areas. The Asian primary care physicians also have a substantial number practicing in these areas, but their proportions practicing in these areas are much smaller compared with any other racial/ethnic group.

Let's parse the findings from that paragraph to see how the demographic groups actually rank in fulfilling this public good.

First, looking at the overall distribution across all underserved areas in aggregate, the study establishes a clear baseline:

"Black, Native American, and Hispanic groups have higher proportions practicing in HPSA, MUA/P, and rural areas compared with White primary care physicians and the Asian group..."

Next, it breaks this down into three specific geographic categories (HPSA, MUA/P, and Rural) to reveal the hierarchy:

• HPSA & MUA/P (2 of the 3 categories): Native American, Black, and Hispanic physicians practice here at higher rates than White physicians.
• Rural (1 of the 3 categories): Native Americans still practice here at the highest rate, but White physicians practice in rural areas at higher rates than Black and Hispanic physicians.

Finally, the study summarizes the extremes: Native Americans have the highest proportions across all three areas, while Asians have the lowest proportions across all three.

If we score these groups based on their aggregate propensity to fill needed positions in underserved areas, the ordinal ranking is undeniable:

1. Native Americans: Highest in 3 out of 3 categories.
2. Blacks & Hispanics: Higher than Whites in 2 out of 3 categories (and higher overall).
3. Whites: Higher than Blacks and Hispanics in only 1 out of 3 categories (Rural).
4. Asians: Lowest in all categories.

What does this mean for the topic under discussion--medical school admissions? I wrote before that there is a public good aspect to the medical profession. As such, geographic and practice diversity (i.e., filling underserved areas) is often a core part of an institution's mission. I also noted previously that valuing this metric is not the kind of ideological thinking invoked by terms like "preferred races" or "critical race theory."

Part of an individual applicant's admissions packet includes secondary essays and interviews where the candidate is queried on their willingness and historical commitment to working in these areas. (I most recently submitted an example of some questions to candidates in North Dakota). While this is evaluated on a strictly individual basis, if students are honest about their career trajectories, there will--as a logical consequence--be aggregate differences in this kind of "mission fitness."

To repeat: aggregates are not individuals. But if we look at the aggregates as you have been doing, there is a very real, non-nefarious explanatory variable that operates in the reverse direction to the MCAT averages. In aggregate, Native Americans would score at the top for this mission fitness, Asians would be at the bottom; Blacks and Hispanics would be tied for second, and Whites would be third.

Therefore, let's use this split function as a rough estimate:
f(mission fitness) = { 9 if NA; 7 if Black or Hispanic; 5 if White; 3 if Asian }

We do not have this data for Native Hawaiian (very very rare medical students) nor new categories like Middle Eastern nor multiple ethnicities/races.

We can explore a best fit to deal with here in a simulation of admission criteria:

Acceptance rate = A x MCAT mean of applicants + B x GPA mean of applicants + C x mission fitness

Using the adjusted non-Puerto Rican numbers for the Hispanic cohort alongside the rest of the aggregate applicant data (after also fixing the Black acceptance rate), we have:

• NA: 500.7 MCAT, 3.51 GPA, 9 Mission (Acceptance Rate: 40.74%)
• Black: 498.1 MCAT, 3.43 GPA, 7 Mission (Acceptance Rate: 31.02%)
• Hispanic: 501.5 MCAT, 3.53 GPA, 7 Mission (Acceptance Rate: 36.46%)
• White: 508.0 MCAT, 3.72 GPA, 5 Mission (Acceptance Rate: 47.17%)
• Asian: 508.8 MCAT, 3.72 GPA, 3 Mission (Acceptance Rate: 44.46%)

Running a multiple regression on this system yields the following line of best fit:

Acceptance Rate = -1183.13 + 2.50(MCAT) - 13.27(GPA) + 2.23(Mission Fitness)



The R² is 0.988. This means the model mathematically explains nearly 99% of the variance in acceptance rates between these groups.

Caveat: "With three parameters I can fit an elephant, with one more I can make him wiggle his tail."

We should naturally expect an astronomically high R² here. When you use four parameters (an intercept plus three variables) to model just five aggregate data points, the math will inevitably draw a line that perfectly intersects almost every point. (You can also see the statistical noise of overfitting in the coefficients themselves--the GPA multiplier actually turns negative purely because it is so heavily correlated with the MCAT). With so little aggregate data and so many variables, the model overfits by design.

Therefore, it is important to note this is a test to explore plausibility and confirm that this is a plausible explanation, not to provide a definitive proof. We cannot really see what happens behind the scenes. In reality, perhaps some people are implementing something nefarious. Perhaps others are being lazy and using race as a proxy for these public goods. While others may be doing the rigorous math of using criteria in admissions that includes mission fitness, and we are simply observing the results in the aggregate.

To add--we still do not know how much of the differences are due to matriculating to different schools with different thresholds. We observed how much Puerto Rico can affect the numbers. There isn't much data on the matriculation side of this.

 

[Emily Lake]

Me thinks you’re reading “nobody” much more broadly than I meant it. I’m talking about this discussion and the people making the AA/DEI argument here, not claiming that nobody anywhere complains about nepotism, favoritism or White people benefiting from connections. My point is that here, when people talk about somebody receiving an opportunity they supposedly didn’t earn, the example keeps becoming a Black or Hispanic applicant taking a spot from a White or Asian applicant. Of course people complain about nepotism and favoritism involving White people. That actually reinforces my point. We recognize all kinds of reasons someone might get an advantage over a supposedly “better” candidate without immediately turning it into a demographic grievance. What I’m questioning is why, here, the outrage over AA/DEI preferential treatment has been so specifically attached to Black and Hispanic people as the “spot takers.” Your hypothetical explains why an explicit racial preference could create suspicion. Fine. I’m against that kind of preference too. But it doesn’t really answer the selective framing I was talking about.

This is exactly why I tend to avoid debating you. You seem to have a real problem paying attention to the details of what I actually wrote. Bomb does the same thing, he took my specific point about White women, where race was part of the point, and quietly turned it into an argument about women in general. It’s a silly way to argue. If you don’t want to address the point I actually made, fine. Just don’t address it. I’d much rather that than have you rewrite my argument into something easier for you to respond to and then argue against that instead. It's not like I'm not willing to concede when my argument is flawed or when I’m wrong. But I can’t do that when the argument being criticized isn’t actually the one I made.

Your post was unclear, and did not seem to be limited solely to giving specific posters here a hard time.

Be more clear.

Oh? What part of “this discussion” and “where Derec loses me” suggested I was talking about the entire world? You were so eager to climb onto your high horse that you mistook your mouth for the stirrup.

The part where that's not in what I was responding to.

Reread it yourself:

Post in thread 'MCATs, Affirmative Action, and DEI, Oh My'

Sep 9, 2026

This actually makes me wonder something. If the problem is preferential treatment, then why does the discussion seem so overwhelmingly concerned with preferential treatment when the beneficiary is Black or Hispanic? White applicants lose positions to other White applicants all the damn time, and some of those people absolutely got an advantage that had nothing to do with being the most qualified person in the room. Legacy status, family connections, referrals, who you know, institutional connections, etc.

Someone else loses that seat or job when that happens too. Yet nobody sees a...

• Gospel

• 

 

[Emily Lake]

The R2 is 0.988. This means the model mathematically explains nearly 99% of the variance in acceptance rates between these groups.

The fit is well within a reasonable variation for noise, sample size, etc.

 

[Don2 (Don1 Revised)]

The R2 is 0.988. This means the model mathematically explains nearly 99% of the variance in acceptance rates between these groups.

The fit is well within a reasonable variation for noise, sample size, etc.

Yes. There is a problem with too little data and too many variables. So even if I throw random mission fit numbers it gives good fitness sometimes. So I am going to eliminate GPA since it is correlated with MCAT anyway and retry. I am just using AI to do the multiple regressions but it switched from the pro to a lighter version on me because I ran out of freebies. Now it is saying, "Data. What data?" So now I need a bit of time to see if I can do a little bit better with this.

ETA: Ugh, okay, ....so using the mission fitness as is is better than randomness now after eliminating a variable. That was done so that there is more data to fit to less variables and to remove the multicollinearity issue.

So here is modeling with just the MCAT mean and mission fitness.

Model Summary​

• $R² Value: 0.9883 (explaining roughly 98.8% of the variance)
• Regression Formula: Acceptance Rate = -1031.49 + 2.10 x MCAT + 2.17 x Mission Fitness

AI says there is a p value of 3.16%

 

[Don2 (Don1 Revised)]

"To add--we still do not know how much of the differences are due to matriculating to different schools with different thresholds. We observed how much Puerto Rico can affect the numbers. There isn't much data on the matriculation side of this."

Much of the data is unavailable to do this kind of analysis, especially school-specific. There are some interesting observations to be made, however, at a regional and state level. Some states (like West Virginia) and territories (like Puerto Rico) have acceptance rates higher than there are for the White and Asian cohorts. Compared to a state like California with elite MCAT scores and GPAs, those acceptance rates often shoot past California while those regions' MCATs and GPAs are not as good. These regions generally have small Asian populations, but sometimes large White populations or other demographics. The acceptance rate of California in general, while "high," is less than that of either White or Asian, even though the average scores are comparable. This is suggestive of regional bottlenecking discussed earlier, but I cannot really be certain because of the lack of data on exactly where people matriculate to and those demographic and score statistics for those schools. I kind of think that "mission fitness" or seeking diversity as a "public good" is interactive with regional bottlenecking, magnifying the effect. Still, I do not know how much specific schools with specific charters or merely voluntarily not going to schools with lower thresholds plays a role as well.

I will finish computing and show some numbers later.

 

[Gospel]

Me thinks you’re reading “nobody” much more broadly than I meant it. I’m talking about this discussion and the people making the AA/DEI argument here, not claiming that nobody anywhere complains about nepotism, favoritism or White people benefiting from connections. My point is that here, when people talk about somebody receiving an opportunity they supposedly didn’t earn, the example keeps becoming a Black or Hispanic applicant taking a spot from a White or Asian applicant. Of course people complain about nepotism and favoritism involving White people. That actually reinforces my point. We recognize all kinds of reasons someone might get an advantage over a supposedly “better” candidate without immediately turning it into a demographic grievance. What I’m questioning is why, here, the outrage over AA/DEI preferential treatment has been so specifically attached to Black and Hispanic people as the “spot takers.” Your hypothetical explains why an explicit racial preference could create suspicion. Fine. I’m against that kind of preference too. But it doesn’t really answer the selective framing I was talking about.

This is exactly why I tend to avoid debating you. You seem to have a real problem paying attention to the details of what I actually wrote. Bomb does the same thing, he took my specific point about White women, where race was part of the point, and quietly turned it into an argument about women in general. It’s a silly way to argue. If you don’t want to address the point I actually made, fine. Just don’t address it. I’d much rather that than have you rewrite my argument into something easier for you to respond to and then argue against that instead. It's not like I'm not willing to concede when my argument is flawed or when I’m wrong. But I can’t do that when the argument being criticized isn’t actually the one I made.

Your post was unclear, and did not seem to be limited solely to giving specific posters here a hard time.

Be more clear.

Oh? What part of “this discussion” and “where Derec loses me” suggested I was talking about the entire world? You were so eager to climb onto your high horse that you mistook your mouth for the stirrup.

The part where that's not in what I was responding to.

Reread it yourself:

Post in thread 'MCATs, Affirmative Action, and DEI, Oh My'

Sep 9, 2026

This actually makes me wonder something. If the problem is preferential treatment, then why does the discussion seem so overwhelmingly concerned with preferential treatment when the beneficiary is Black or Hispanic? White applicants lose positions to other White applicants all the damn time, and some of those people absolutely got an advantage that had nothing to do with being the most qualified person in the room. Legacy status, family connections, referrals, who you know, institutional connections, etc.

Someone else loses that seat or job when that happens too. Yet nobody sees a...

• Gospel

• 

So because you showed up late to the discussion, I’m supposed to rewind the whole damn conversation and explain how we got here? Nigga, please.

 

[Jimmy Higgins]

"To add--we still do not know how much of the differences are due to matriculating to different schools with different thresholds. We observed how much Puerto Rico can affect the numbers. There isn't much data on the matriculation side of this."

Much of the data is unavailable to do this kind of analysis, especially school-specific. There are some interesting observations to be made, however, at a regional and state level. Some states (like West Virginia) and territories (like Puerto Rico) have acceptance rates higher than there are for the White and Asian cohorts. Compared to a state like California with elite MCAT scores and GPAs, those acceptance rates often shoot past California while those regions' MCATs and GPAs are not as good. These regions generally have small Asian populations, but sometimes large White populations or other demographics. The acceptance rate of California in general, while "high," is less than that of either White or Asian, even though the average scores are comparable. This is suggestive of regional bottlenecking discussed earlier, but I cannot really be certain because of the lack of data on exactly where people matriculate to and those demographic and score statistics for those schools. I kind of think that "mission fitness" or seeking diversity as a "public good" is interactive with regional bottlenecking, magnifying the effect. Still, I do not know how much specific schools with specific charters or merely voluntarily not going to schools with lower thresholds plays a role as well.

I will finish computing and show some numbers later.

I think the issue here is that you don't want to keep bedding the numbers. The numbers are telling us something that isn't unexpected, and appears reasonable. That better grades mean better acceptance rates. This entire thread has people who are woke beyond belief desperately trying to find data that implies the nation is unfair to whites and Asians. The data broadly says, better students do better. Trying to get SDs to a certain level is merely an exercise in skill at getting the results you want at some point.

 

[Don2 (Don1 Revised)]

"To add--we still do not know how much of the differences are due to matriculating to different schools with different thresholds. We observed how much Puerto Rico can affect the numbers. There isn't much data on the matriculation side of this."

Much of the data is unavailable to do this kind of analysis, especially school-specific. There are some interesting observations to be made, however, at a regional and state level. Some states (like West Virginia) and territories (like Puerto Rico) have acceptance rates higher than there are for the White and Asian cohorts. Compared to a state like California with elite MCAT scores and GPAs, those acceptance rates often shoot past California while those regions' MCATs and GPAs are not as good. These regions generally have small Asian populations, but sometimes large White populations or other demographics. The acceptance rate of California in general, while "high," is less than that of either White or Asian, even though the average scores are comparable. This is suggestive of regional bottlenecking discussed earlier, but I cannot really be certain because of the lack of data on exactly where people matriculate to and those demographic and score statistics for those schools. I kind of think that "mission fitness" or seeking diversity as a "public good" is interactive with regional bottlenecking, magnifying the effect. Still, I do not know how much specific schools with specific charters or merely voluntarily not going to schools with lower thresholds plays a role as well.

I will finish computing and show some numbers later.

I think the issue here is that you don't want to keep bedding the numbers. The numbers are telling us something that isn't unexpected, and appears reasonable. That better grades mean better acceptance rates. This entire thread has people who are woke beyond belief desperately trying to find data that implies the nation is unfair to whites and Asians. The data broadly says, better students do better. Trying to get SDs to a certain level is merely an exercise in skill at getting the results you want at some point.

I get what you are saying and I think you are correct. To clarify, I do not have an active goal in trying to get the SDs to a certain level, but rather to list some (plausible) explanatory variables at play. This coincidentally can explain SD as well. I guess I think it is important to note that reality is beyond ideology which tends to simplify into single variable narratives.

So here, I have computed some numbers and made a visualization. I will just pause here because yeah, I tend to want to do overkill with these types of things.

I took a look at how MCAT applicant means vary across states (and Puerto Rico). The data tables divide up states into broader regions, such as NorthEast. I took the state (or territory) with lowest MCAT mean in each region. The South was also a poor performer compared to all other regions and so I took a number of states that were below some intuitive midpoint I had made. The observation was that the acceptance rates of residents in these states into whatever schools they were matriculating into (unknown, but possibly state schools), were very often higher than would be predicted by their MCAT means. Now that could be state schools giving preference to residents, but there's also an issue that many of the states have rural populations.

California, as discussed, has a mean applicant MCAT similar to Whites and Asian cohorts. But its acceptance rate is less than either. This suggests regional bottlenecking to me.

To visalize this better I have a chart with acceptance rates for these states and races are included for comparison. Both applicant MCAT mean and acceptance rates are displayed. I have subtracted 472 (the minimum) from the MCAT so that the remaining MCAT score is comparable in size to the acceptance rate and the visualization can see some odd things going on.

Across this subset of data of aggregates, there is no correlation between mean applicant MCAT and acceptance rate.

 

[Bomb#20]

I've got to imagine that those who did have lower MCAT scores needed something else to buoy their application.

Often that "something else" is the right skin color and abuelitos who hablaban español.
Sure, sometimes it's something legitimate, like a corpsman in the military with years of experience. But racial preferences also exist, and I am sick of people trying to deny the obvious.

Funny story about that. The guy who got us to where we are, Allan Bakke, was discriminated against not just because the medical school thought he was too white but also because they thought he was too old. The reason he was too old was he spent four years in the Marine Corps.

 

[Emily Lake]

So because you showed up late to the discussion, I’m supposed to rewind the whole damn conversation and explain how we got here? Nigga, please.

No, you don't have to rewind the entire conversation. But it seems reasonable to expect that you refrain from being an asshole for no good reason.

In complete sincerity, and without any intent to mock, have you at least considered that sometimes you're simply not as clear as you think you are? Or that perhaps sometimes you misinterpret other people's posts?

 

[Bomb#20]

I don’t see how you can actually know that is in fact an accurate statement.

Asked and answered. In brief: statistically, it is pretty much impossible for it to be due to chance. So it's either discrimination or some other factor that is relevant to admissions and where blacks and Hispanics best whites and Asians. Nobody here has even attempted to identify such a a factor, much less provide any evidence for it. So, discrimination is a logical conclusion.

I actually did and mentioned this plausible factor several times. I even did so recently in a post to you. You did not reply. Perhaps you missed it. It happens.
...
Let's parse the findings from that paragraph to see how the demographic groups actually rank in fulfilling this public good.
...
f(mission fitness) = { 9 if NA; 7 if Black or Hispanic; 5 if White; 3 if Asian }
...

You understand, don't you, that none of this is an argument that racial discrimination isn't happening? It's an argument that this particular racial discrimination fulfills a public good.

 

[Don2 (Don1 Revised)]

I don’t see how you can actually know that is in fact an accurate statement.

Asked and answered. In brief: statistically, it is pretty much impossible for it to be due to chance. So it's either discrimination or some other factor that is relevant to admissions and where blacks and Hispanics best whites and Asians. Nobody here has even attempted to identify such a a factor, much less provide any evidence for it. So, discrimination is a logical conclusion.

I actually did and mentioned this plausible factor several times. I even did so recently in a post to you. You did not reply. Perhaps you missed it. It happens.
...
Let's parse the findings from that paragraph to see how the demographic groups actually rank in fulfilling this public good.
...
f(mission fitness) = { 9 if NA; 7 if Black or Hispanic; 5 if White; 3 if Asian }
...

You understand, don't you, that none of this is an argument that racial discrimination isn't happening? It's an argument that this particular racial discrimination fulfills a public good.

That is not what I argued in context. If an application packet includes essays and interviews assessing a candidate's commitment to working in underserved areas, the aggregate responses across different demographic groups will naturally stratify along the lines of that split function. I even linked a specific example of these exact criteria from a North Dakota medical school.

You can label that institutional mission discriminatory if you want to, but evaluating candidates on specific public-need criteria is fundamentally different from the claim that schools are simply fudging numbers or relying on a progressive stack of races.

 

[Toni]

I don’t see how you can actually know that is in fact an accurate statement.

Asked and answered. In brief: statistically, it is pretty much impossible for it to be due to chance. So it's either discrimination or some other factor that is relevant to admissions and where blacks and Hispanics best whites and Asians. Nobody here has even attempted to identify such a a factor, much less provide any evidence for it. So, discrimination is a logical conclusion.

I actually did and mentioned this plausible factor several times. I even did so recently in a post to you. You did not reply. Perhaps you missed it. It happens.
...
Let's parse the findings from that paragraph to see how the demographic groups actually rank in fulfilling this public good.
...
f(mission fitness) = { 9 if NA; 7 if Black or Hispanic; 5 if White; 3 if Asian }
...

You understand, don't you, that none of this is an argument that racial discrimination isn't happening? It's an argument that this particular racial discrimination fulfills a public good.

Your post seems to demonstrate that you’re ok with certain people refusing to consider much less commit to providing much needed medtcal services to underserved communities.

 

[Derec]

Also please note: The deviations inGPA and MCAT are quite small.

They are not, as I have repeatedly shown. Repeating mantras does not change reality.

No one can become a physician without passing each part of the USMLE, which is more rigorous than the MCAT.

It's not necessarily more rigorous, it just has a different purpose and different content.
And likelihood of failing Step 1 on your first try and of never passing it at all is associated with both MCAT and undergrad GPA.

 

[Derec]

Not every person with extremely high scores on any test or highest GPA is good at ( set of all qualities requisite in being a good teacher, physician, lawyer, police officer, social worker, astronaut, POTUS, etc.)

That is true, but there is no reason to assume that this ability should be different by race. I.e. there is no reason to think that a black premed with a particular MCAT and GPA would be a better doctor than an Asian premed with the same MCAT/GPA. So why are Asian premeds required to have higher MCATs and GPAs than blacks? Obvious answer is discrimination in furtherance of the goal of "diversity".

 

[Derec]

Derec just doesn't complain about it as much as VP Harris, but he isn't the sole bar on this sort of stuff.

Your Ilk brings it up far more than I ever did. But for the record, it is indisputable that she slept with a guy twice her age and that he put her on two state boards. At the very least, there is an appearance of a quid-pro-sex.

But, to be fair, if this were the 1980s, this thread would have been comparing men's and women's scores on the MCAT.

Racial discrepancies existed back then too. It was not that long after Bakke.

 

[Toni]

Not every person with extremely high scores on any test or highest GPA is good at ( set of all qualities requisite in being a good teacher, physician, lawyer, police officer, social worker, astronaut, POTUS, etc.)

That is true, but there is no reason to assume that this ability should be different by race. I.e. there is no reason to think that a black premed with a particular MCAT and GPA would be a better doctor than an Asian premed with the same MCAT/GPA. So why are Asian premeds required to have higher MCATs and GPAs than blacks? Obvious answer is discrimination in furtherance of the goal of "diversity".

I’m not making that assumption. But you seem unable to d terrain the notion that qualities and intentions beyond achieving high scores are legitimately considered for admissions.

Likewise you seem unwilling or unable to understand or accept that medical schools have missions to produce physicians who have certain skills or who are producing physicians who are committed to serving underserved communities . There is dejection going on on all sides of the equations.

 

[Toni]

Also please note: The deviations inGPA and MCAT are quite small.

They are not, as I have repeatedly shown. Repeating mantras does not change reality.

No one can become a physician without passing each part of the USMLE, which is more rigorous than the MCAT.

It's not necessarily more rigorous, it just has a different purpose and different content.
And likelihood of failing Step 1 on your first try and of never passing it at all is associated with both MCAT and undergrad GPA.

Every description of the USMLE I’ve read describes it as more rigorous, as one would expect it to be. Graduating students should have considerably more mastery of relevant material upon graduation from med school.

 

[Toni]

Related question: this kind of focus is on underrepresented minorities who at least in theory meet a public need at a greater rate (mission fitness). Where is the uproar regarding predominantly non-Asian regions (like WV or White rural areas) from blocking qualified out-of-state (Asian) applicants from applying? It seems like there is a goal here, not by you, by Trump... have you thought about it?

Institutions exist to serve their population. Preference for in-state applicants is often legally required as part of receiving state money.

Thus I have no objection here. It's an entirely relevant basis to decide, openly listed.

So you have no problem when there is discrimination for mostly whites because it is open.

What matters is why, not what the racial distribution is. You're pulling the standard disparate outcome proves discrimination bit.

Post-secondary education tends to be more favorable to in-state residents. Whether that should be the case is a separate issue.

Are you trying to say that in terms of admissions, public universities and colleges favor in state students over those who are applying from other states?

 

[Bomb#20]

You understand, don't you, that none of this is an argument that racial discrimination isn't happening? It's an argument that this particular racial discrimination fulfills a public good.

Your post seems to demonstrate that you’re ok with certain people refusing to consider much less commit to providing much needed medtcal services to underserved communities.

Your post seems to demonstrate that you're from some other planet where language works differently. My post did not contain any value judgments.

Asked and answered. In brief: statistically, it is pretty much impossible for it to be due to chance. So it's either discrimination or some other factor that is relevant to admissions and where blacks and Hispanics best whites and Asians. Nobody here has even attempted to identify such a a factor, much less provide any evidence for it. So, discrimination is a logical conclusion.

I actually did and mentioned this plausible factor several times. I even did so recently in a post to you. You did not reply. Perhaps you missed it. It happens.
...
Let's parse the findings from that paragraph to see how the demographic groups actually rank in fulfilling this public good.
...
f(mission fitness) = { 9 if NA; 7 if Black or Hispanic; 5 if White; 3 if Asian }
...

You understand, don't you, that none of this is an argument that racial discrimination isn't happening? It's an argument that this particular racial discrimination fulfills a public good.

That is not what I argued in context. If an application packet includes essays and interviews assessing a candidate's commitment to working in underserved areas, the aggregate responses across different demographic groups will naturally stratify along the lines of that split function. I even linked a specific example of these exact criteria from a North Dakota medical school.

You can label that institutional mission discriminatory if you want to, but evaluating candidates on specific public-need criteria is fundamentally different from the claim that schools are simply fudging numbers or relying on a progressive stack of races.

You're missing the point. It's not that the institutional mission and/or specific public-need criteria are discriminatory; it's that the schools are not measuring candidates on mission fitness and fulfilling public-need criteria. The schools are not lowering the MCAT standard a student needs to meet because he's going to work in an underserved area. They don't know if he is; this isn't Minority Report and they aren't precogs. They're using a proxy. Ability to do well in school is an important quality in medical students, so what say we check "how the demographic groups actually rank" in that characteristic, observe that it's f(school success) = { 3 if NA; 5 if Black or Hispanic; 7 if White; 9 if Asian }, and then use that to judge applicants instead of, you know, actually looking at their GPAs? You'd agree assuming an Asian has a high GPA and a NA has a lower one, as a proxy, instead of actually measuring, would be racial discrimination, yes?

No doubt you'll argue that "essays and interviews assessing a candidate's commitment to working in underserved areas" isn't a racial proxy, but what evidence is there that that's true? What do those essays and interviews actually measure? Do they measure actual mission fitness, or do they just measure race? That's something that's testable retrospectively. If in fact schools aren't racially discriminating and the MCAT discrepancy results from relying on essays and interviews to forecast mission fitness, and if that allegedly nonracial proxy accurately predicts working in underserved areas, then that implies we could take a random sample of minority doctors who work in underserved areas, and a random control group of minority doctors who don't work in underserved areas, and check what their MCAT scores were back when they were accepted into medical school -- and the control group who don't work in underserved areas should turn out to have had MCAT scores similar to those of Asian and white matriculants. Only the group working in underserved areas would have statistically gotten the benefit of the relaxed MCAT requirements.

As noted upthread, 90+ percent of NA doctors don't work on reservations. If for the sake of getting one mission-fit doctor you rate nine premeds as mission-fit who aren't actually mission-fit, that looks a lot more like measuring race than measuring mission-fitness.