The Sorting Machine

What did SFFA reveal about “merit” in college admissions?

A domestic student at a given academic percentile has a far smaller chance of landing a

seat at an elite university, and of paying for it, than an identical student fifty years ago.

Admissions are fundamentally zero-sum, so where did these seats go?

Different doors, wildly different odds.

Every applicant is sorted into a lane before the file is even read, and the gates on those

lanes are not the same size. A recruited athlete walks through an opening five-sixths of the way open. The

unhooked domestic applicant faces a pinhole. Same university, same year, a roughly 17-fold gap

in the odds of getting through.

NBER w26316

full paper

The same file, four different verdicts.

The most-cited number from the Harvard trial comes from a counterfactual. The plaintiffs'

economist modeled one applicant profile and swapped only the race field. The model's predicted probability of

admission moved from 25% to 95%.

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This is a modeled probability rather than a real admit rate, and Harvard's experts disputed the specification.

But no party disputed the direction: at equal academic strength, the personal-rating and race adjustments

did not fall evenly across groups.

A different price for every family.

The published cost of attendance is a fiction almost no one pays. The real price is

computed per household from a federal-and-institutional aid formula. This is textbook first-degree

price discrimination: the same product, the same seat, sold to each family at the maximum the formula

thinks it can extract. Here is the machine that sets your number.

NCES College Navigator

Yale, 2026–27

Why the upper-middle class gets hit hardest. The formula's design does the damage: income above a

modest protection allowance is assessed at steep marginal rates, and the CSS Profile that elite

privates use counts what the federal FAFSA does not: home equity in your primary residence and the

non-custodial parent's income. The 2024 FAFSA overhaul also removed the reduction for having two

children in college at once. Net effect: a $175k household with a house and a 401(k) is judged "full

pay," pays near-sticker from already-taxed income, and receives essentially nothing.

Dept. of Ed (SAI) · CSS Profile.

Dept. of Ed (SAI)

CSS Profile

Demographic comparisons.

Treat this as an accounting question. Follow each group across three

steps: its share of the country's 18-year-olds, its share of all U.S. college students,

and its share of an elite private class. If admission were neutral the three bars would stay

level. They don't. Some groups expand sharply at the elite tier while others contract: Asian students roughly

quadruple, international admits go from zero to a sizable slice, and several domestic groups shrink at every step.

NCES Digest tbl. 101.20

Harvard CDS

The hook paradox.

Here's the counterintuitive part. A group that leans heavily on legacy and recruited

athletics doesn't get those hooked seats for free. They come out of the group's overall footprint. So when you

strip the hooks away and look only at the unhooked "merit" pool, that same group can be crowded out

of it: its own hooked admits have already spent the seats. First, who actually fills each track:

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Harvard Crimson

The merit ratio makes the paradox one number per group: its share of unhooked admits ÷

its share of all admits. Below 1.0 means the group is thinner in the merit pool than on campus overall,

because the hooks did the heavy lifting and its unhooked applicants face the steepest pure-merit climb. Above 1.0, the

group earns its place and would gain seats if hooks were abolished. Split it by race and gender and the

pattern sharpens: men lean harder on the male-skewed athletic and legacy hooks, so every man sits below his female

counterpart on the same scale.

And per head of population? Divide each group's unhooked merit seats by its share of the

country's 18-year-olds, so that 1.0 now means merit seats in exact proportion to that group's youth. The

merit pipeline turns out to be a rounding error for most Americans and a firehose for one group:

NCES tbl. 101.20

Harvard CDS

The hook advantage and the merit disadvantage are the same coin. The more a group is admitted through

legacy and athletics, the more of its overall footprint is already spent, so its unhooked applicants

compete for a shrunken remainder of merit seats, and against the largest unhooked applicant pool. The group that

looks most "privileged" by the hooks is the one whose merit pipeline is squeezed hardest. (This

reads the trial data as schools managing each group's total toward a rough band, which is well-evidenced but a point

critics contest.)

Two quiet thumbs on the scale.

Since 2020, two changes have narrowed the merit door further. Both were sold as fairness. Both

systematically disadvantage the same person: the high-scoring, unhooked applicant who has nothing but a

strong record to stand on.

Harvard Crimson

FairTest

Why "optional" hurts the high scorer. A 1550 used to be a cheap, legible signal that vaulted an unknown

applicant out of the pile. Make the test optional and that signal goes quiet: a top score no longer separates

you, because the reader leans harder on essays, activities, and "context," the soft factors that reward the

polished and the coached. A Dartmouth study found disadvantaged applicants scoring above 1400 were 3× more

likely to be admitted when they submitted scores. The very students test-optional was meant to help are hurt

when they hold a strong score back. NBER Digest, 2025.

NBER Digest, 2025

The big-fish penalty.

Every file is read "in context" of its high school. Reasonable in theory, but it means a strong

student at a strong school is measured against a wall of equally strong peers, while an identical record at a

weaker school stands out. Percent-plans and holistic "context" reward being a big fish in a small pond, and

quietly penalize the applicant who swam in a harder one.

Stack the two together and they point at one person. The applicant with the strongest raw record, a top score

earned at a rigorous school, is exactly the one the test-optional shift de-emphasizes and the context lens

penalizes. Precisely the student the word "merit" was supposed to name.

The same student, three admissions systems.

Here is a hypothetical applicant, call him Daniel R., a strong,

unhooked domestic student. He is not a real person, but a composite built to hold academic strength constant

while we change only the system he applies through. What determines his odds is less his file

than the machine reading it.

Holistic review

Course-based selection

Concours (exam)

Every one of these systems carries its own biases upstream. The deeper point is that "merit" is defined

by the machine that reads the file. Move Daniel across the border and the very traits that make him a

residual in one system make him a front-runner in another.

Same student. Fifty years apart.

Stack the four forces together, the reserved seats, the holistic filter, the per-family

price, and the demographic targets, and they compound. Hold the student constant at a top-decile

academic profile and ask two questions across half a century: can he get in, and can his

family pay for it? On both, the line moved the wrong way.

Fifty years ago a strong domestic student faced a selective but winnable gate, at a price

a middle-class family could absorb. Today the same student faces a lottery, and if he wins it, a bill

indexed to a wealth he doesn't have. The pipeline didn't close. It narrowed to a trickle, and got

expensive.

A note on the numbers.

What's sourced, what's modeled. The core empirical figures (the ALDC admit rates, the Arcidiacono

race model, Harvard's demographics and application counts, the Princeton net-price bands, and the enrollment and

population data) are now linked to primary sources below and in each chart's footer. The merit ratio,

the per-capita index, and the race×gender splits are our own calculations built on those inputs.

The method is transparent, but the specific multipliers remain modeled estimates, not published figures.

Race / admit-probability model (25→36→77→95%) — P. Arcidiacono expert report, SFFA v. Harvard; NBER w27068.

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ALDC admit rates (athletes 86%, faculty 47%, dean's 42%, legacy 34%, non-ALDC <5.5%; 43% of white admits are ALDC) — Arcidiacono, Kinsler & Ransom, NBER w26316.

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Harvard admit rate & applications (3.59%, Class of 2028; 40k→61k apps) — Harvard Crimson.

Harvard Crimson

Demographics — 18–24 population, NCES tbl. 101.20; elite shares & international, Harvard CDS 2023–24.

NCES tbl. 101.20

Harvard CDS 2023–24

Net price & cost of attendance — NCES College Navigator (Princeton); Yale COA; FAFSA/SAI, U.S. Dept. of Education.

NCES College Navigator (Princeton)

Yale COA

U.S. Dept. of Education

Test-optional — FairTest; effect on high scorers, NBER Digest 2025.

FairTest

NBER Digest 2025

Enrollment by gender (men 42%, 2021) — NCES Fast Facts.

NCES Fast Facts

UK / France systems — Oxford & Cambridge undergraduate admissions reports; French Ministère de l'Enseignement supérieur on classes préparatoires & concours.

Editorial note: the counterfactual student Daniel R. is a

composite constructed for illustration and does not depict any real individual.