MCATs, Affirmative Action, and DEI, Oh My

[Loren Pechtel]

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.

Calling this equation "mission fitness" doesn't actually provide any reason to believe your inputs map to these numbers. You do not appear to be doing anything beyond quantifying the discrimination.

 

[Loren Pechtel]

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?

Are you not aware there are such things now?

I have repeatedly said that I'm not trying to specify exactly what goes on the scale. I'm saying that only that what goes on the scale should be out in the open and reasonably measurable, no thumbs.

States often say favoring state residents is the price of state funding. You can argue the merits of that but that's a separate issue.

 

[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?

Are you not aware there are such things now?

I’m sorry. I forgot to indicate irony.

 

[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?

Are you not aware there are such things now?

I have repeatedly said that I'm not trying to specify exactly what goes on the scale. I'm saying that only that what goes on the scale should be out in the open and reasonably measurable, no thumbs.

States often say favoring state residents is the price of state funding. You can argue the merits of that but that's a separate issue.

What you are suggesting amounts to expecting every applicant to any medtcal school to waive their requirement gets to privacy and to allow themselves to be subjected to intrusive and ill informed abd often bigoted examination of their academic record, personal information and much more—just to satisfy some people’s fears that unqualified black people are being allowed to become physicians.

I admit that I have run into a few physicians that I felt were incompetent, in a couple of cases, egregiously so.

They were all white and make and I believe, older than me. A couple I know for a fact are dead. Others are retired or dead. Which goes to show just how wonderful our previous system of dejecting physicians was.

We still have work to do: women in general and in particular women of color face a great deal of difficulty in convincing doctors to take their symptoms, especially pain, seriously. Prior to the egregious overturning of Roe, the US had an abysmal rate of maternal death due a so called developed nation. It is now worse as in some states, women are denied life saving care needed related to miscarriage.

 

[Loren Pechtel]

As noted upthread, 90+ percent of NA doctors don't work on reservations.

The statistic about reservations is a red herring. Working on a reservation is merely one specific example of how different demographics might fulfill a public need. The broader and more rigorous data shows that NA doctors proportionally serve across all types of underserved areas at higher rates. Equating "underserved" exclusively with "reservations" artificially shrinks the success rate of the metric and erroneously manufactures an undeserved high failure rate.

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.

First, because NA doctors serve in other underserved areas at higher rates, the premise of a 9-in-10 false prediction rate doesn't hold up to the data.

Look at his numbers. 90% do not serve in underserved areas. That's the 9 in 10 you say isn't there.

More importantly, there seems to be a fundamental disconnect about the mechanism of how mission-fitness is plausibly applied. Let me try to clear that up:

The problem is you're using underwear gnome logic here.

To be clear: I am not claiming this is the absolute, guaranteed mechanism for every school. I am pointing out that this is a mathematically sound, plausible model of how weighted variables work. It explains the aggregate national data without requiring the assumption that committees are simply using race as a blind proxy for academic success.

First, you're saying the wrong thing here. Your parameter is about serving needs, not academics.

And, second, you are not establishing any connection. The simplest explanation is the parameter you found says exactly what you listed. Race. If it's actually derived from something else why has no school said so?? There is no Fifth in the court of public opinion. There's nothing here that requires secrecy. We have one false defense ("personality") and otherwise silence. Why in the world should we not assume guilt?

 

[Loren Pechtel]

My dear: Racial and gender preferences still favor white and male. Sadly enough. And in this country known as the United States, that has been true since colonial times.

And herein lies the problem. You have repeatedly taken a disparate outcome as proof of discrimination. Except when it doesn't say what you want it to say.

Now what is happening is that candidates who are not white or the ‘good’ kind of Asian are no longer automatically chosen, with other candidates moved to the rear of the line, if they are ever allowed in line in the first place.

White people like to make themselves feel better by believing or telling themselves to believe that the only way any person of color or female gets chosen ahead of a white or preferred type Asian is because of Affurnstive Action. It’s comforting to believe that you lost out because of preferences for a demographic you don’t fit.

Continuing to make false allegations doesn't make them true. None of us are asking for only white males allowed.

Especially note that your reasoning somehow makes Asians super-white. There's no reason for this, Asians were heavily discriminated against in the past. If your reasoning was true they should fare on a par with Hispanics, not above whites.

People with expertise have shown over and over again that a great deal of the bias you think you see does not actually exist, except to the extent that t that there is a lot of self selection going on.

Except they haven't. Lots of claims before the court of public opinion, the claims vanish in the courtroom. Same as The Felon's claims of election tampering.

 

[Loren Pechtel]

You can see this clearly by looking at West Virginia, Puerto Rico, and California. For example, roughly 20% of all Hispanic medical students matriculate in Puerto Rico rather than the mainland US. That massive concentration fundamentally alters the national acceptance rate and average stats for that cohort.

Conversely, look at California: it has incredibly high applicant MCAT means, creating severe bottlenecking for in-state admissions. In California, the vast majority of applicants are Asian but there are only so many available seats. Moreover, because a massive portion of Asian applicants reside in California, that geographic bottleneck artificially suppresses their overall acceptance rate and inflates their required scores, driving up the national averages for that cohort.

While the AAMC doesn't publish perfectly cross-tabulated tables of matriculation schools by race, the data we can see makes it explicitly clear: state-level residency requirements and geographic distribution demonstrably warp these national racial averages. These kinds of differences are a subset of the larger superset of different racial demographics attending different schools with different thresholds.

P.S. You are still refusing to talk about West Virginia and the broader pattern it represents.

Showing there could be such factors at work is not the same thing as showing that they are at work. And remember the Supreme Court case was about one school. No possibility of demographic differences between schools causing issues.

Your defense amounts to creating doubt about the certainty of guilt, it does absolutely nothing to address why we should be judging this on beyond a shadow of a doubt vs preponderance of the evidence.

 

[Loren Pechtel]

That’s ridiculous.

Taking anyone from a not great school to a great school should improve performance unless what you mean by a great school is exclusionary.

A great school also has higher standards, a not so great school which is less selective has lower standards.
Take a B student from Clayton State University and put him in Georgia Tech or Emory and he'll probably struggle to even maintain a C in the same classes.

Maybe. But take an A student from (insert mediocre school) and give them a shot at an education at an excellent school and guess what? People rise to the occasion. Not always. I mean: Trump and his entire administration or 'administration.' But yeah.

Leftist fantasy. Doesn't make it work. Dropping students from inferior schools into superior schools doesn't help. Even as early as grade school.

I don't know how we fix early education (because so much of it is parents and community), but that's where any fix has to be. Anything done later is painting over the rust.

 

[Don2 (Don1 Revised)]

Look at his numbers. 90% do not serve in underserved areas. That's the 9 in 10 you say isn't there.

Loren, there is some confusion here. Those initial numbers were mine and do not mean what you think. First, they meant something else and second they were about the Indian Health Service, not the broad concept of underserved areas. Second, within the same post I had also linked a study regarding underserved areas. That study has more relevant numbers to underserved areas. Underserved areas are divided into 3 types: low socio-economic, understaffed, and rural. There are acronyms for the 3 types, but I'll leave that out. There can be overlap between all three. In each of the 3 types across specialties Natives have quite a bit more frequency across specialty types. None of the NA proportions are anywhere near a lowly 10%. For example, for FamilyPractitioners/GeneralPractioners among the 3 types you have for NA proportions: 44.3%, 35.1%, 43.5%. If you add the numbers together you get above 100% and this is because there is some overlap between categories. That is one location can be in 1, 2, or 3 types. There is some dependency between the three and I used AI to answer what that dependency is with sometimes hard data and sometimes reasonable estimates and using the principle of inclusion-exclusion. It gives about 75% or a little less than that for NA working as a doctor at a location in at least 1 category. Now compare this to Asians with data from the same study across the 3 types: 17%, 6.5%, 25% and combined using AIs estimated way of computing the inclusion-exclusion, you get around 30%. Now, 75% is more than twice as much as 30%. If you don't trust the AI computation, there is still the hard data from the study which is still a significant difference.

All that is probably besides the point, because there can be considerable noise here in a discussion of small racial categories like American Indian, Alaska Native, Native Hawaiian, Pacific Islander. For example, there are only 33 matriculants this last cycle that were American Indian/Alaska Native. There were considerably less that were Native Hawaiian/Pacific Islander.

To add--as I mentioned long ago, different groups also apply to different schools at different rates that have different thresholds. For American Indian, there is a certain set of medical schools for which they are very likely to apply to and other demographics much less likely to apply to. Those also have a "fitness" for their stated mission. I will give an example: the Duluth campus medical school in Minnesota. They have a low MCAT threshold for entry. In interviews, essays, engagement, etc, they seek out individuals willing to work in tribal areas and rural areas. They are recognized across many years on special lists for producing doctors who work in rural areas (which are an underserved type). Other campus medical schools in Minnesota do not have the same mission and they also have a higher MCAT minimum. So, you can expect some self-selection going on here: students with a specific interest in the mission will want to attend, i.e. a higher frequency of White people and Native than other campuses. I believe I read somewhere they may have 3 NA this year which would be about 10% of the whole cohort.

Off the top of my head, I believe there are some other schools like this, perhaps in Oklahoma, North Dakota, and New Mexico, sorry New America. So for a good portion of these 33 people we are talking about merely a handful of schools with special missions and low MCAT minima.

 

[Loren Pechtel]

Different schools have different MCAT thresholds or none at all. Different schools have different demographics. Some lower and no threshold schools have significantly more under-represented minorities. There can be self-sorting here, too, where mid and high scorers do not apply to these schools.

But it should all average out when looking at national data. Unless there is a racial bias in admissions for the purposes of increasing "diversity".

Demographics could explain this if both are related to some other factor.

Consider the oft-repeated claim of police shooting blacks more often. Depending on how you measure, yes, you could say that. But you don't find the disparity in any city. The actual relationship is that in blacker cities the police shoot more often.

 

[Loren Pechtel]

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.

We have no power to make data available. Of course we focus on what data is available.

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 is supposed to show something?!?! You introduce a source of noise that will remove some without any basis, of course it hits those with higher scores more.

 

[Toni]

That’s ridiculous.

Taking anyone from a not great school to a great school should improve performance unless what you mean by a great school is exclusionary.

A great school also has higher standards, a not so great school which is less selective has lower standards.
Take a B student from Clayton State University and put him in Georgia Tech or Emory and he'll probably struggle to even maintain a C in the same classes.

Maybe. But take an A student from (insert mediocre school) and give them a shot at an education at an excellent school and guess what? People rise to the occasion. Not always. I mean: Trump and his entire administration or 'administration.' But yeah.

Leftist fantasy. Doesn't make it work. Dropping students from inferior schools into superior schools doesn't help. Even as early as grade school.

I don't know how we fix early education (because so much of it is parents and community), but that's where any fix has to be. Anything done later is painting over the rust.

Really.

I know quite a number of people who attended ‘mediocre schools’ who were National Merit scholars.

 

[Toni]

As noted upthread, 90+ percent of NA doctors don't work on reservations.

The statistic about reservations is a red herring. Working on a reservation is merely one specific example of how different demographics might fulfill a public need. The broader and more rigorous data shows that NA doctors proportionally serve across all types of underserved areas at higher rates. Equating "underserved" exclusively with "reservations" artificially shrinks the success rate of the metric and erroneously manufactures an undeserved high failure rate.

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.

First, because NA doctors serve in other underserved areas at higher rates, the premise of a 9-in-10 false prediction rate doesn't hold up to the data.

Look at his numbers. 90% do not serve in underserved areas. That's the 9 in 10 you say isn't there.

More importantly, there seems to be a fundamental disconnect about the mechanism of how mission-fitness is plausibly applied. Let me try to clear that up:

The problem is you're using underwear gnome logic here.

To be clear: I am not claiming this is the absolute, guaranteed mechanism for every school. I am pointing out that this is a mathematically sound, plausible model of how weighted variables work. It explains the aggregate national data without requiring the assumption that committees are simply using race as a blind proxy for academic success.

First, you're saying the wrong thing here. Your parameter is about serving needs, not academics.

And, second, you are not establishing any connection. The simplest explanation is the parameter you found says exactly what you listed. Race. If it's actually derived from something else why has no school said so?? There is no Fifth in the court of public opinion. There's nothing here that requires secrecy. We have one false defense ("personality") and otherwise silence. Why in the world should we not assume guilt?

You’ve done nothing to show that medical schools are turning out unqualified or incompetent doctors.

Nothing.

Not one damn thing.

You want medical schools to change their admissions selection process to provide the outcome you want which seems to be turning out fewer black and Hispanic doctors. Because you, personally, are convinced they are less competent. You have no data that indicates this. You just want the system to produce results you personally think are fair, with zero evidence that your favored demographic actually make better doctors.

 

[laughing dog]

"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.

Look again at what he's doing. He's finding the bias we are talking about, but making up a mission fitness parameter to balance it--but we have no evidence that it's relevant.

The mission fitness is analogous to your ever present SES explanation of observed bias.

 

[Politesse]

Not only are/were universities using DEI in their admissions process, they used it on students already admitted!:

Stanford R&DE Uses AI to Race Swap Students for Advertising

Stanford University is facing backlash after its Residential & Dining Enterprises used a photograph of students that had been edited by artificial intelligence—including entirely changing one Hispanic, male student into a Black woman—in its advertising.

The photo first came to light in a report by The Stanford Review, the university’s right-leaning student newspaper. The original image shows a female student on the left and two male students to her left, with all three smiling at the camera and posing with their food outside Star Ginger, a food stall in one of Stanford’s dining halls; the AI-edited image removed the rightmost male student and generated a Black woman in his place.

The one thing that's a little baffling is they chose to erase the Hispanic guy, rather than the White guy in the middle. Did Hispanic males drop below even White males on the progressive stack? Or maybe they thought the Hispanic guy was also White?!

Altering the Asian girl's face had to sting a little for her. I guess AI (or the photo editor) wasn't too fond of her chubby cheeks. I kinda liked her better the original way.

How is what you describe "DEI" in any way?

 

[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.

Look again at what he's doing. He's finding the bias we are talking about, but making up a mission fitness parameter to balance it--but we have no evidence that it's relevant.

I am not making this up; rather, I am discussing a highly plausible variable that is implicit in the admissions process. Medical schools have distinct missions, which often include producing doctors who will work in underserved areas. It is entirely reasonable to conclude that this factor influences adcom scoring. Schools actively use interviews, essays, and other metrics to gauge how closely an applicant aligns with their mission. Simultaneously, as I mentioned in my last post, applicants self-select and gravitate toward schools whose missions match their own career goals.

Because different demographic groups historically show different aggregate rates of practicing in underserved areas, this "mission fitness" variable naturally intersects with race. It doesn't come from nowhere; it is a highly relevant reality of the admissions filter.

To put it another way: there is hard data supporting these aggregate demographic differences in career paths, meaning they will inevitably affect admissions outcomes. What remains unknown is the magnitude of that effect. We don't yet know if mission fitness amounts to mere statistical noise, if it is heavily concentrated only at specific schools, or if it acts as the primary confounding variable in the relationship between MCAT scores and acceptance rates.

Ultimately, I have to return to Jimmy Higgins' observation: broadly speaking, acceptance rates do go up with MCAT means. However, since adcoms utilize multi-variate scoring, we should fully expect to see "noise" when examining this direct correlation. My own observation suggests this variance doesn't stem from just one primary confounding variable, but rather a complex multitude of them. Because of this, trying to explain the residual differences beyond that baseline trend becomes an exercise in mapping interrelated confounders--a task that sometimes requires better data, a specific skillset, and considerable time.

 

[Don2 (Don1 Revised)]

Not only are/were universities using DEI in their admissions process, they used it on students already admitted!:

Stanford R&DE Uses AI to Race Swap Students for Advertising

Stanford University is facing backlash after its Residential & Dining Enterprises used a photograph of students that had been edited by artificial intelligence—including entirely changing one Hispanic, male student into a Black woman—in its advertising.

The photo first came to light in a report by The Stanford Review, the university’s right-leaning student newspaper. The original image shows a female student on the left and two male students to her left, with all three smiling at the camera and posing with their food outside Star Ginger, a food stall in one of Stanford’s dining halls; the AI-edited image removed the rightmost male student and generated a Black woman in his place.

The one thing that's a little baffling is they chose to erase the Hispanic guy, rather than the White guy in the middle. Did Hispanic males drop below even White males on the progressive stack? Or maybe they thought the Hispanic guy was also White?!

Altering the Asian girl's face had to sting a little for her. I guess AI (or the photo editor) wasn't too fond of her chubby cheeks. I kinda liked her better the original way.

How is what you describe "DEI" in any way?

These are the kinds of absurd contradictions that develop when one believes there is a critical race theory conspiracy driving everything.

 

[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.

Look again at what he's doing. He's finding the bias we are talking about, but making up a mission fitness parameter to balance it--but we have no evidence that it's relevant.

You mean he is modeling a potential metric or set of metrics that you've assumed was racial bias, and you are complaining that he is calling it something else. A person with very high MCATs and GPAs can rely solely on that. A person with lower values has to work harder at selling themselves as a viable candidate for medical school. That you think this is unreasonable is odd. Don2's look at it is far from unreasonable. Yes, race enters the picture at some point, but the weight it is being given doesn't appear to be anywhere near the Civil Rights violations being claimed. You and your ilk keep claiming you've proven racial bias to the extent that Asians are discriminated against. You keep saying judge the individuals, but damn entire races over average test scores. Your arguments have been more hollow than a cheap chocolate Easter bunny.

 

[Loren Pechtel]

If noting that people engage in tribal thinking - which you 100% know means in-group assumed morally right, out-group cast as bad - is "racist", then you, sir, are not very smart.

Yes. That is exactly what I mean. Using loaded and historically racialized terms as a stand in the general concept of anri-social behavior is racist. Your Colonislism-shaped beliefs about what "tribes" are like is wrong, prejudicial, and speaks volumes about how you see the world. It is also, given the cause you are supposedly championing, incredibly ironic.

I don't think you understand the point.

We are saying what tribe (in this case race) someone is from is irrelevant and should have no basis in decision making. I am sure that's what he's referring to about "tribal" thinking.

 

[Loren Pechtel]

BTW, if you don't think there are at least 2 racial bigots participating in this thread, then you are not very smart.

It's possible that there are some actual racists in here. But I don't think that's the case.

Likewise. I see "racist" being used to describe anyone who doesn't agree with the left wing position on addressing discrimination. Just because our position would be detrimental to blacks doesn't mean our objective is to be bad to blacks.

This comes down to yardsticks. They are aiming for equality of outcome, we are aiming for equality of opportunity.

Is a DUI checkpoint unfair because it doesn't catch any teetotalers? It clearly discriminated against beer!