Better odds for full pay applicants

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:My theory is that need blind schools are need blind in that they don’t look at the applicant’s financial situation individually but they have software that uses statistical analysis to make sure there will be a sufficient percentage of full pay students. The software sets the parameters- pct from private school, pct from this county or that county, etc

What is your evidence for this theory?

AFAIK, not one of the many tell-all books written by adcoms has stated this is true.

NP. I agree with the PP entirely, that algorithms drive decisions but adcoms don't have a role in the algorithms and may not know much about them at all. This is the multi-billion-dollar enrollment management industry.

What is unclear is at what point in the process the algorithms are involved, front, back, all of it, etc., and what of this adcoms can see in Slate, for example. I do believe adcoms at need-blind schools read the apps need-blind. We know for a fact that schools use algorithms to calculate likelihood of yield and we know that most colleges use the Landscape tool from College Board, which includes a lot of data at the level of the applicant's census tract.

Top colleges arrive at roughly the same % of the class getting grants year after year. They must do this by algorithm in the aggregate, like PP was suggesting.

Here is one random articles on the enrollment management industry, though plenty more can be googled:

https://www.marketwatch.com/story/revenue-and-rankings-inside-the-multibillion-dollar-industry-shaping-college-admissions-e9faaabf

Just google something like "higher ed yield algorithm enrollment management" and you'll start to get a sense of the industry. Why this matters is that, ultimately, yield algorithms do play a role in admission decisions, possibly in ways that adcoms are not paying attention to or aren't even aware of. It might boil down to some sort of yield score in Slate.

This goes way back, e.g. from 2015, Student Yield Maximization Using Genetic Algorithm on a Predictive Enrollment Neural Network Model, https://www.researchgate.net/publication/283186686_Student_Yield_Maximization_Using_Genetic_Algorithm_on_a_Predictive_Enrollment_Neural_Network_Model. "The primary objective of this research is to develop a scholarship distribution model that enables academic enrollment offices to maximize student yield through efficient scholarship distribution. This paper presents the design of and tests a multi-layer feed-forward neural network (NN) in modeling the student yield factor. For this model inputs are assumed to be ACT score, GPA/class-rank, EFC, FAFSA, zip code and scholarship award amount and the single output is the student yield, where a one/zero system for accepting/declining the offer in attending the university is considered. The network is trained by applying the back error propagation algorithm, and is tested on holdout samples."

The available data here in 2025 are more detailed. It's all about the data.

I heard that colleges can see when (by date) you added them to your “list” in scoir and who else is on your list. Is this true??

Holy shit.
They explained affinity scores and the algo on the most recent YCBK….its what you’ve been saying about the Algo all along.

Engagement starting in 9th grade!!!!

“I had an institution tell me when someone started having an engagement with us in the 9th grade. Our yield for that kid is really, really high. Now, do you expect everybody to have engagement in 9th?

No. But what if your research shows the longer they've been engaged, the yield is higher? What if your research shows if they're spending a lot of time looking at how you deposit and housing and all these indications that indicate they're probably going to come because you can track your web traffic and you can see who's going to these portions that someone who's serious about you would tend to look at on the website.

Why not have someone build a model out to you that includes some of those factors? That just kind of seems inevitable to me that that kind of stuff is going on. It's not stuff that you can always, you can't reveal the secret sauce because, one, then people will just game it more and it will decrease its efficacy.”

From Your College Bound Kid | Admission Tips, Admission Trends & Admission Interviews: A Debate About Whether ACT/SAT Scores Should Be Mandatory, Apr 9, 2025

There is a LOT built into algorithms by enrollment management consultants. A huge portion of the admission decision is data-driven, ultimately on likelihood of yield. Is it "fair"? No, though nothing about the process is "fair." Beyond fairness, I think there is too much lack of nuance, maybe because it can't be demonstrated by data.

It's frustrating, because my sense is that most regional AOs have no idea what an impact algorithms have. Personally, I think that's what makes decisions seem so random.

--have full pay, high stats kid on five waitlists, admitted to no targets or reaches. Applied to many last-minute and yes, would have attended any of them if admitted.

It’s those last minute apps. Rarely does someone get in RD without some interaction unless very top of class.
This should be a warning to juniors.
My kid got into several high reaches (T20), without the very highest or best stats. A ton of engagement with the schools admitted to….
Regrets about not engaging with a few other reaches.
It mattered.

[Anonymous]

Duke and Northwestern, and most T11-25 are all tracking engagement.
Heavily.

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:My theory is that need blind schools are need blind in that they don’t look at the applicant’s financial situation individually but they have software that uses statistical analysis to make sure there will be a sufficient percentage of full pay students. The software sets the parameters- pct from private school, pct from this county or that county, etc

What is your evidence for this theory?

AFAIK, not one of the many tell-all books written by adcoms has stated this is true.

NP. I agree with the PP entirely, that algorithms drive decisions but adcoms don't have a role in the algorithms and may not know much about them at all. This is the multi-billion-dollar enrollment management industry.

What is unclear is at what point in the process the algorithms are involved, front, back, all of it, etc., and what of this adcoms can see in Slate, for example. I do believe adcoms at need-blind schools read the apps need-blind. We know for a fact that schools use algorithms to calculate likelihood of yield and we know that most colleges use the Landscape tool from College Board, which includes a lot of data at the level of the applicant's census tract.

Top colleges arrive at roughly the same % of the class getting grants year after year. They must do this by algorithm in the aggregate, like PP was suggesting.

Here is one random articles on the enrollment management industry, though plenty more can be googled:

https://www.marketwatch.com/story/revenue-and-rankings-inside-the-multibillion-dollar-industry-shaping-college-admissions-e9faaabf

Just google something like "higher ed yield algorithm enrollment management" and you'll start to get a sense of the industry. Why this matters is that, ultimately, yield algorithms do play a role in admission decisions, possibly in ways that adcoms are not paying attention to or aren't even aware of. It might boil down to some sort of yield score in Slate.

This goes way back, e.g. from 2015, Student Yield Maximization Using Genetic Algorithm on a Predictive Enrollment Neural Network Model, https://www.researchgate.net/publication/283186686_Student_Yield_Maximization_Using_Genetic_Algorithm_on_a_Predictive_Enrollment_Neural_Network_Model. "The primary objective of this research is to develop a scholarship distribution model that enables academic enrollment offices to maximize student yield through efficient scholarship distribution. This paper presents the design of and tests a multi-layer feed-forward neural network (NN) in modeling the student yield factor. For this model inputs are assumed to be ACT score, GPA/class-rank, EFC, FAFSA, zip code and scholarship award amount and the single output is the student yield, where a one/zero system for accepting/declining the offer in attending the university is considered. The network is trained by applying the back error propagation algorithm, and is tested on holdout samples."

The available data here in 2025 are more detailed. It's all about the data.

I heard that colleges can see when (by date) you added them to your “list” in scoir and who else is on your list. Is this true??

Holy shit.
They explained affinity scores and the algo on the most recent YCBK….its what you’ve been saying about the Algo all along.

Engagement starting in 9th grade!!!!

“I had an institution tell me when someone started having an engagement with us in the 9th grade. Our yield for that kid is really, really high. Now, do you expect everybody to have engagement in 9th?

No. But what if your research shows the longer they've been engaged, the yield is higher? What if your research shows if they're spending a lot of time looking at how you deposit and housing and all these indications that indicate they're probably going to come because you can track your web traffic and you can see who's going to these portions that someone who's serious about you would tend to look at on the website.

Why not have someone build a model out to you that includes some of those factors? That just kind of seems inevitable to me that that kind of stuff is going on. It's not stuff that you can always, you can't reveal the secret sauce because, one, then people will just game it more and it will decrease its efficacy.”

From Your College Bound Kid | Admission Tips, Admission Trends & Admission Interviews: A Debate About Whether ACT/SAT Scores Should Be Mandatory, Apr 9, 2025

There is a LOT built into algorithms by enrollment management consultants. A huge portion of the admission decision is data-driven, ultimately on likelihood of yield. Is it "fair"? No, though nothing about the process is "fair." Beyond fairness, I think there is too much lack of nuance, maybe because it can't be demonstrated by data.

It's frustrating, because my sense is that most regional AOs have no idea what an impact algorithms have. Personally, I think that's what makes decisions seem so random.

--have full pay, high stats kid on five waitlists, admitted to no targets or reaches. Applied to many last-minute and yes, would have attended any of them if admitted.

It’s those last minute apps. Rarely does someone get in RD without some interaction unless very top of class.
This should be a warning to juniors.
My kid got into several high reaches (T20), without the very highest or best stats. A ton of engagement with the schools admitted to….
Regrets about not engaging with a few other reaches.
It mattered.

What kind of engagement did your kid have with the admitted schools?

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:My theory is that need blind schools are need blind in that they don’t look at the applicant’s financial situation individually but they have software that uses statistical analysis to make sure there will be a sufficient percentage of full pay students. The software sets the parameters- pct from private school, pct from this county or that county, etc

What is your evidence for this theory?

AFAIK, not one of the many tell-all books written by adcoms has stated this is true.

NP. I agree with the PP entirely, that algorithms drive decisions but adcoms don't have a role in the algorithms and may not know much about them at all. This is the multi-billion-dollar enrollment management industry.

What is unclear is at what point in the process the algorithms are involved, front, back, all of it, etc., and what of this adcoms can see in Slate, for example. I do believe adcoms at need-blind schools read the apps need-blind. We know for a fact that schools use algorithms to calculate likelihood of yield and we know that most colleges use the Landscape tool from College Board, which includes a lot of data at the level of the applicant's census tract.

Top colleges arrive at roughly the same % of the class getting grants year after year. They must do this by algorithm in the aggregate, like PP was suggesting.

Here is one random articles on the enrollment management industry, though plenty more can be googled:

https://www.marketwatch.com/story/revenue-and-rankings-inside-the-multibillion-dollar-industry-shaping-college-admissions-e9faaabf

Just google something like "higher ed yield algorithm enrollment management" and you'll start to get a sense of the industry. Why this matters is that, ultimately, yield algorithms do play a role in admission decisions, possibly in ways that adcoms are not paying attention to or aren't even aware of. It might boil down to some sort of yield score in Slate.

This goes way back, e.g. from 2015, Student Yield Maximization Using Genetic Algorithm on a Predictive Enrollment Neural Network Model, https://www.researchgate.net/publication/283186686_Student_Yield_Maximization_Using_Genetic_Algorithm_on_a_Predictive_Enrollment_Neural_Network_Model. "The primary objective of this research is to develop a scholarship distribution model that enables academic enrollment offices to maximize student yield through efficient scholarship distribution. This paper presents the design of and tests a multi-layer feed-forward neural network (NN) in modeling the student yield factor. For this model inputs are assumed to be ACT score, GPA/class-rank, EFC, FAFSA, zip code and scholarship award amount and the single output is the student yield, where a one/zero system for accepting/declining the offer in attending the university is considered. The network is trained by applying the back error propagation algorithm, and is tested on holdout samples."

The available data here in 2025 are more detailed. It's all about the data.

I heard that colleges can see when (by date) you added them to your “list” in scoir and who else is on your list. Is this true??

Holy shit.
They explained affinity scores and the algo on the most recent YCBK….its what you’ve been saying about the Algo all along.

Engagement starting in 9th grade!!!!

“I had an institution tell me when someone started having an engagement with us in the 9th grade. Our yield for that kid is really, really high. Now, do you expect everybody to have engagement in 9th?

No. But what if your research shows the longer they've been engaged, the yield is higher? What if your research shows if they're spending a lot of time looking at how you deposit and housing and all these indications that indicate they're probably going to come because you can track your web traffic and you can see who's going to these portions that someone who's serious about you would tend to look at on the website.

Why not have someone build a model out to you that includes some of those factors? That just kind of seems inevitable to me that that kind of stuff is going on. It's not stuff that you can always, you can't reveal the secret sauce because, one, then people will just game it more and it will decrease its efficacy.”

From Your College Bound Kid | Admission Tips, Admission Trends & Admission Interviews: A Debate About Whether ACT/SAT Scores Should Be Mandatory, Apr 9, 2025

There is a LOT built into algorithms by enrollment management consultants. A huge portion of the admission decision is data-driven, ultimately on likelihood of yield. Is it "fair"? No, though nothing about the process is "fair." Beyond fairness, I think there is too much lack of nuance, maybe because it can't be demonstrated by data.

It's frustrating, because my sense is that most regional AOs have no idea what an impact algorithms have. Personally, I think that's what makes decisions seem so random.

--have full pay, high stats kid on five waitlists, admitted to no targets or reaches. Applied to many last-minute and yes, would have attended any of them if admitted.

It’s those last minute apps. Rarely does someone get in RD without some interaction unless very top of class.
This should be a warning to juniors.
My kid got into several high reaches (T20), without the very highest or best stats. A ton of engagement with the schools admitted to….
Regrets about not engaging with a few other reaches.
It mattered.

What kind of engagement did your kid have with the admitted schools?

I can answer for my kid:
- interactions with AO at multiple local college fairs (along with interactions with AO when coming to the HS in fall);
- In-person on-campus (late) fall visit and interview with AO (where available);
- Email correspondence with AO;
- Sitting in on a class after ED1 deferral arranged through the admissions office.

Probably only important for schools that mention where "demonstrated interest" is considered. Think that's the case for Duke, Notre Dame, Northwestern, WashU, Middlebury, Rice, Michigan, NYU and Tufts.

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:My theory is that need blind schools are need blind in that they don’t look at the applicant’s financial situation individually but they have software that uses statistical analysis to make sure there will be a sufficient percentage of full pay students. The software sets the parameters- pct from private school, pct from this county or that county, etc

What is your evidence for this theory?

AFAIK, not one of the many tell-all books written by adcoms has stated this is true.

NP. I agree with the PP entirely, that algorithms drive decisions but adcoms don't have a role in the algorithms and may not know much about them at all. This is the multi-billion-dollar enrollment management industry.

What is unclear is at what point in the process the algorithms are involved, front, back, all of it, etc., and what of this adcoms can see in Slate, for example. I do believe adcoms at need-blind schools read the apps need-blind. We know for a fact that schools use algorithms to calculate likelihood of yield and we know that most colleges use the Landscape tool from College Board, which includes a lot of data at the level of the applicant's census tract.

Top colleges arrive at roughly the same % of the class getting grants year after year. They must do this by algorithm in the aggregate, like PP was suggesting.

Here is one random articles on the enrollment management industry, though plenty more can be googled:

https://www.marketwatch.com/story/revenue-and-rankings-inside-the-multibillion-dollar-industry-shaping-college-admissions-e9faaabf

Just google something like "higher ed yield algorithm enrollment management" and you'll start to get a sense of the industry. Why this matters is that, ultimately, yield algorithms do play a role in admission decisions, possibly in ways that adcoms are not paying attention to or aren't even aware of. It might boil down to some sort of yield score in Slate.

This goes way back, e.g. from 2015, Student Yield Maximization Using Genetic Algorithm on a Predictive Enrollment Neural Network Model, https://www.researchgate.net/publication/283186686_Student_Yield_Maximization_Using_Genetic_Algorithm_on_a_Predictive_Enrollment_Neural_Network_Model. "The primary objective of this research is to develop a scholarship distribution model that enables academic enrollment offices to maximize student yield through efficient scholarship distribution. This paper presents the design of and tests a multi-layer feed-forward neural network (NN) in modeling the student yield factor. For this model inputs are assumed to be ACT score, GPA/class-rank, EFC, FAFSA, zip code and scholarship award amount and the single output is the student yield, where a one/zero system for accepting/declining the offer in attending the university is considered. The network is trained by applying the back error propagation algorithm, and is tested on holdout samples."

The available data here in 2025 are more detailed. It's all about the data.

I heard that colleges can see when (by date) you added them to your “list” in scoir and who else is on your list. Is this true??

Holy shit.
They explained affinity scores and the algo on the most recent YCBK….its what you’ve been saying about the Algo all along.

Engagement starting in 9th grade!!!!

“I had an institution tell me when someone started having an engagement with us in the 9th grade. Our yield for that kid is really, really high. Now, do you expect everybody to have engagement in 9th?

No. But what if your research shows the longer they've been engaged, the yield is higher? What if your research shows if they're spending a lot of time looking at how you deposit and housing and all these indications that indicate they're probably going to come because you can track your web traffic and you can see who's going to these portions that someone who's serious about you would tend to look at on the website.

Why not have someone build a model out to you that includes some of those factors? That just kind of seems inevitable to me that that kind of stuff is going on. It's not stuff that you can always, you can't reveal the secret sauce because, one, then people will just game it more and it will decrease its efficacy.”

From Your College Bound Kid | Admission Tips, Admission Trends & Admission Interviews: A Debate About Whether ACT/SAT Scores Should Be Mandatory, Apr 9, 2025

There is a LOT built into algorithms by enrollment management consultants. A huge portion of the admission decision is data-driven, ultimately on likelihood of yield. Is it "fair"? No, though nothing about the process is "fair." Beyond fairness, I think there is too much lack of nuance, maybe because it can't be demonstrated by data.

It's frustrating, because my sense is that most regional AOs have no idea what an impact algorithms have. Personally, I think that's what makes decisions seem so random.

--have full pay, high stats kid on five waitlists, admitted to no targets or reaches. Applied to many last-minute and yes, would have attended any of them if admitted.

Can you say which schools? Curious if they are ones that "consider" demonstrated interest. If so, it may have been a wasted application if the kid didn't visit, sign up for webinars, and engaged with student admissions volunteers through scheduled chats/interviews etc.

[Anonymous]

Listen to today’s YCBK. Full blown attack on Northeastern and the “shady” way they handle their satellite campuses and obvious consideration of need vs full pay.


They also talked about the massive gender gap in quality of applicants this year between male and female:

“ “You know, I see, I see, see usually boys have more selective options than somebody who's female with the same sort of stats. They're obviously not the same person ever, but I was really...

Now, I had a VP of Enrollment who's been in the profession for maybe 25 years, multiple schools. Tell me, we've never seen a gender gap like this. Like, I don't know what's going on out there.

And we were just grappling with each other, like, what was causing that? Was it COVID? How COVID impacted?

You know, we were just speculating together. But he was telling me that they've never seen this disparity in the strength of the girl pool versus the boy pool like to have this year. I don't know if you heard, you might not have heard because I just did it, this episode last Monday, where I went through like 15 different changes that I'm expecting because of all the financial pressure colleges are under.”

From Your College Bound Kid | Admission Tips, Admission Trends & Admission Interviews: An interview with Jim Bock, Dean and VP at Swarthmore College-3 of 3, Apr 23, 2025

[Anonymous]

The more gpa is considered the standard for being "qualified," the greater the proportion of girls will be.

Sure some schools have gone back to requiring scores, but that doesn't necessarily mean gpa weighs less. Admissions may still be overweighting gpa.

[Anonymous]

Anonymous wrote:The more gpa is considered the standard for being "qualified," the greater the proportion of girls will be.

Sure some schools have gone back to requiring scores, but that doesn't necessarily mean gpa weighs less. Admissions may still be overweighting gpa.

Sorry this was a reply to the post above about the ycbk podcast discussion of gender gap.

Or maybe something else is going on with the algorithms involved. My high stats boy was denied at top schools this round.

[Anonymous]

Anonymous wrote:

Anonymous wrote:The more gpa is considered the standard for being "qualified," the greater the proportion of girls will be.

Sure some schools have gone back to requiring scores, but that doesn't necessarily mean gpa weighs less. Admissions may still be overweighting gpa.

Sorry this was a reply to the post above about the ycbk podcast discussion of gender gap.

Or maybe something else is going on with the algorithms involved. My high stats boy was denied at top schools this round.

Which schools?
RD or early? Which major?

[Anonymous]

Anonymous wrote:

Anonymous wrote:The more gpa is considered the standard for being "qualified," the greater the proportion of girls will be.

Sure some schools have gone back to requiring scores, but that doesn't necessarily mean gpa weighs less. Admissions may still be overweighting gpa.

Sorry this was a reply to the post above about the ycbk podcast discussion of gender gap.

Or maybe something else is going on with the algorithms involved. My high stats boy was denied at top schools this round.

Odd results that don't make sense, with regard to a disproportionate number of girls being accepted to highly selective schools than boys? Yes, it's possible that algorithms are at work. Mathematical models may not be the holy grail that the enrollment management industry makes them out to be.

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:The more gpa is considered the standard for being "qualified," the greater the proportion of girls will be.

Sure some schools have gone back to requiring scores, but that doesn't necessarily mean gpa weighs less. Admissions may still be overweighting gpa.

Sorry this was a reply to the post above about the ycbk podcast discussion of gender gap.

Or maybe something else is going on with the algorithms involved. My high stats boy was denied at top schools this round.

Odd results that don't make sense, with regard to a disproportionate number of girls being accepted to highly selective schools than boys? Yes, it's possible that algorithms are at work. Mathematical models may not be the holy grail that the enrollment management industry makes them out to be.

Maybe it's the major the girls are selecting?
But in the podcast, aren't they just saying the girls are "stronger"? Not that they are being accepted at a higher rate.
Or am I missing something?

[Anonymous]

Anonymous wrote:Listen to today’s YCBK. Full blown attack on Northeastern and the “shady” way they handle their satellite campuses and obvious consideration of need vs full pay.


They also talked about the massive gender gap in quality of applicants this year between male and female:

“ “You know, I see, I see, see usually boys have more selective options than somebody who's female with the same sort of stats. They're obviously not the same person ever, but I was really...

Now, I had a VP of Enrollment who's been in the profession for maybe 25 years, multiple schools. Tell me, we've never seen a gender gap like this. Like, I don't know what's going on out there.

And we were just grappling with each other, like, what was causing that? Was it COVID? How COVID impacted?

You know, we were just speculating together. But he was telling me that they've never seen this disparity in the strength of the girl pool versus the boy pool like to have this year. I don't know if you heard, you might not have heard because I just did it, this episode last Monday, where I went through like 15 different changes that I'm expecting because of all the financial pressure colleges are under.”

From Your College Bound Kid | Admission Tips, Admission Trends & Admission Interviews: An interview with Jim Bock, Dean and VP at Swarthmore College-3 of 3, Apr 23, 2025

Girl pool is stronger, but less impressive boys are being admitted to more and more selective schools.
I think the algo is working? This is precisely what they want - more boys admitted for that gender balance. It's just the girl "pool" is stronger.

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:The more gpa is considered the standard for being "qualified," the greater the proportion of girls will be.

Sure some schools have gone back to requiring scores, but that doesn't necessarily mean gpa weighs less. Admissions may still be overweighting gpa.

Sorry this was a reply to the post above about the ycbk podcast discussion of gender gap.

Or maybe something else is going on with the algorithms involved. My high stats boy was denied at top schools this round.

Odd results that don't make sense, with regard to a disproportionate number of girls being accepted to highly selective schools than boys? Yes, it's possible that algorithms are at work. Mathematical models may not be the holy grail that the enrollment management industry makes them out to be.

Maybe it's the major the girls are selecting?
But in the podcast, aren't they just saying the girls are "stronger"? Not that they are being accepted at a higher rate.
Or am I missing something?

I didn't listen yet (maybe later), but the question would then be what makes the girls "stronger" applicants. GPA would be the obvious factor, since that is well known to favor girls on average, but if they meant actual acceptances, then I would wonder if it were something else. I don't know, but the reason that an algorithm result comes to mind is that sometimes algorithms lead to unintentional results, e.g. where a student with a high score relative to the school's average leads to a low yield score that ultimately has them deferred or waitlisted or even denied. My question would be whether the scarcity of "qualified" boys leads to less of them getting admitted because the algorithm has them being less likely to yield under a variable assumption that they are more likely to enroll elsewhere. I know this sounds like tortured logic, but my gut guess is that this is an algorithm issue and it seems to get worse each year (more girls than boys admitted, though that brings in a separate question of going through individual CDSs to determine whether that's a matter of who applies vs who is admitted).

[Anonymous]

Anonymous wrote:

Anonymous wrote:Listen to today’s YCBK. Full blown attack on Northeastern and the “shady” way they handle their satellite campuses and obvious consideration of need vs full pay.


They also talked about the massive gender gap in quality of applicants this year between male and female:

“ “You know, I see, I see, see usually boys have more selective options than somebody who's female with the same sort of stats. They're obviously not the same person ever, but I was really...

Now, I had a VP of Enrollment who's been in the profession for maybe 25 years, multiple schools. Tell me, we've never seen a gender gap like this. Like, I don't know what's going on out there.

And we were just grappling with each other, like, what was causing that? Was it COVID? How COVID impacted?

You know, we were just speculating together. But he was telling me that they've never seen this disparity in the strength of the girl pool versus the boy pool like to have this year. I don't know if you heard, you might not have heard because I just did it, this episode last Monday, where I went through like 15 different changes that I'm expecting because of all the financial pressure colleges are under.”

From Your College Bound Kid | Admission Tips, Admission Trends & Admission Interviews: An interview with Jim Bock, Dean and VP at Swarthmore College-3 of 3, Apr 23, 2025

Girl pool is stronger, but less impressive boys are being admitted to more and more selective schools.
I think the algo is working? This is precisely what they want - more boys admitted for that gender balance. It's just the girl "pool" is stronger.

My son is at all male private (not a big 3) and they are very competitive. High rigor, high test scores, high GPAs. Very competitive admits. Maybe coming from typical schools - not the case from ours.

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:Listen to today’s YCBK. Full blown attack on Northeastern and the “shady” way they handle their satellite campuses and obvious consideration of need vs full pay.


They also talked about the massive gender gap in quality of applicants this year between male and female:

“ “You know, I see, I see, see usually boys have more selective options than somebody who's female with the same sort of stats. They're obviously not the same person ever, but I was really...

Now, I had a VP of Enrollment who's been in the profession for maybe 25 years, multiple schools. Tell me, we've never seen a gender gap like this. Like, I don't know what's going on out there.

And we were just grappling with each other, like, what was causing that? Was it COVID? How COVID impacted?

You know, we were just speculating together. But he was telling me that they've never seen this disparity in the strength of the girl pool versus the boy pool like to have this year. I don't know if you heard, you might not have heard because I just did it, this episode last Monday, where I went through like 15 different changes that I'm expecting because of all the financial pressure colleges are under.”

From Your College Bound Kid | Admission Tips, Admission Trends & Admission Interviews: An interview with Jim Bock, Dean and VP at Swarthmore College-3 of 3, Apr 23, 2025

Girl pool is stronger, but less impressive boys are being admitted to more and more selective schools.
I think the algo is working? This is precisely what they want - more boys admitted for that gender balance. It's just the girl "pool" is stronger.

My son is at all male private (not a big 3) and they are very competitive. High rigor, high test scores, high GPAs. Very competitive admits. Maybe coming from typical schools - not the case from ours.

This is not a judgement or commentary about YOUR specific kid or your SCHOOL. Its a comment made by the podcasters in light of the "national" pool of boys and girls.
The girls are overall stronger in the national pool.
Everyone agrees to this.

No one is discounting individual achievements, including that of your very 'accomplished' kid......