The case
The owner, at U3: “college sports, where the team composition experiences extremely fast churn, and yet in spite of this real world ship-of-theseus situation, teams often maintain standing on similar timescales as professional teams (if not longer), so we can meaningfully talk about school’s known to be ‘good’ or ‘bad’ at a particuular sport on much longer timescales than a single student’s tenure.”
Held fixed: the school and the sport. Replaced: every athlete, within a few years; coaches, administrators and facilities, more slowly.
What it can show
A3 separated identity without stable constitution (the program is the same historical program) from dispositional stability without stable constitution (it keeps winning). The second is the stronger fact: it needs a mechanism that regenerates the capacity in each new roster, and A3 named one, a loop from success through prestige and resources to recruiting and back. “The particular roster is an output of the program as well as one of its temporary constituents.”
It is CLAIM-280’s product and producer again, with the producer more nearly observable: the roster is replaced on a schedule and the recruiting, coaching and money that make the next one are not. It also bears on CLAIM-194: a program’s capacity may be held by an institution that selects and trains the players, which is a boundary imposed on the roster as much as produced by it. Bourrat’s ecological scaffold (LIT-005, NOTE-027, criterion C2) is the same question asked of evolutionary transitions.
Given its standing, it cannot show that any program’s persistence is caused by its organization rather than by money, conference or schedule. A3’s test: estimate Corr(Y_t, Y_{t+k} | roster overlap ≈ 0) with resources, schedule strength and league structure controlled, then repeat across coaching and administrative turnover. A5 §8 sharpened it: compare a historically dominant program with one that bought an equally good roster recently, and ask which reconstitutes itself after both rosters and coaches leave. A5 also named the negative result: once resources and recruiting are modelled explicitly, the program may add nothing. A11 §4 added a horizon profile: different variables (roster, recruiting, alumni, reputation) may keep their predictive information over different lags (CLAIM-331).
Note of 2026-10-29: functional information measures the rarity, not the mechanism
A10 named Hazen, Griffin, Carothers and Szostak’s functional information, LIT-1148, for this case’s repeated production of good teams, and read it as function-relative and silent on whether successive teams are one individual. The work is now read (NOTE-1402), and both points hold. It adds a third. The measure is taken over all configurations under a uniform weighting, explicitly not over what a selective process produces. So it can say how rare a good roster is among all rosters, but not why one program keeps drawing from the rare region. That is the mechanism this case asks about, and functional information leaves it untouched. A slow variable the members read, such as a program’s standing (CLAIM-327), is the kind of thing that would. The case is unchanged.