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[quote=Anonymous][quote=Anonymous][quote=Anonymous][quote=Anonymous][quote=Anonymous][quote=Anonymous][quote=Anonymous][quote=Anonymous]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 [/quote]

What is your evidence for this theory?

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

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??[/quote]

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[/quote]
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.[/quote]

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.[/quote]

What kind of engagement did your kid have with the admitted schools? [/quote]

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