The user wants me to revise all the notes into one consolidated Markdown note — the current best statement of what is established about whether US universities grow or shrink due to AI over the next 20 years, with regional dependence.

The final instruction is: "Revise the notes as a set: keep every claim that still holds, drop repetition, sharpen wording. Output one Markdown note that is the current best statement of what is established. Start with a # title, then short paragraphs, then: What would change this: … Keep sources or Unverified: tags. Do not mention tools, sessions, or that you are revising."

This is a "revise as a set" instruction, which means I should synthesize ALL the durable claims across all the notes into one comprehensive note. This is different from the single-facet claim instructions in some of the earlier notes.

Let me inventory all the durable claims from the filed notes:

**Core answer:**
- Bifurcation, not uniform growth or shrinkage. The split is region- AND stratum-specific.
- By ~2045: top ~100 grow, middle hollows into teaching-only, bottom third of four-year schools merge or close.
- "Grow or shrink" resolves as "both" — the system thins rather than shrinks uniformly.

**Demography (load-bearing wall):**
- Births fell from ~4.32M (2007) to ~3.59M (2023), ~17% decline (CDC/NCHS)
- HS grads peak ~3.9M/yr around 2025 (WICHE "Knocking at the College Door")
- Post-2008 birth dearth hits college age 2029–2037
- Northeast/Midwest/Plains lose 10–20% of college-age population
- TX/FL/TN/GA/Carolinas grow

**AI's role:**
- Accelerant/sorter, not primary cause
- Two-front squeeze: fewer 18-year-olds AND degree-as-signal weakened (skills directly verifiable)

**Signaling / enrollment demand:**
- Degrees lose signaling value asymmetrically by enforcement mechanism: licensed fields (state-gated) and super-selectives (prestige) hold; mid-tier unlicensed BA premiums compress 30–50% real by mid-2030s
- Fastest collapse in generalist white-collar fields (business, communications, generic liberal arts) where AI enables direct output verification; slowest where statute enforces the credential (nursing, law, accounting, teaching) or failure costs are catastrophic (engineering, medicine)
- Degree replaced as screening instrument, not as positional good; by 2035 median degree is a luxury positional marker
- Two brakes: AI application floods push employers back to crude degree filters; elite alumni-network/trust effects
- Degree survives as insurance, not instruction: commodity BA premium collapses; selective degree demand rises as hedge (sorting, licensure, networks)
- Enrollment bifurcates by tier before it bifurcates by region
- Total enrollment drifts from ~19M toward ~14–15M by 2045, mid-tier absorbs the whole loss (Unverified forecast)
- Demand migrates to "protected degree + AI skill stack"
- Bimodal BA returns by mid-2030s: licensed-profession and top-30 premiums hold near current levels; mid-tier unlicensed compress 30–50% real

**Program mix × region (mechanism):**
- Program mix (licensed vs unlicensed share of credit hours) is the dominant predictor of institutional direction; region governs whether the winning mix is reachable
- Licensed expansion (nursing, engineering, allied health) takes 7–10 years (clinical placements, faculty pipelines, facilities, state approvals) — longer than declining-region enrollment runway → decline locks in
- SEC/Sunbelt publics: +10–25% seats through ~2040 as legislatures fund them as economic development
- Northeast small privates without licensed core: −30–50% by 2040
- Surviving Northeast exceptions: licensed-core with hospital-system or land-grant ties
- "Program mix picks the winners, regional demography picks which losers can still switch"

**Regional variation (three stacked currents):**
- (1) Demographic cliff falls hardest on Northeast/Midwest
- (2) Net domestic migration relocates college-relevant households to Sun Belt/SEC footprint (Census Bureau)
- (3) AI's first-mover disruption lands on white-collar task clusters concentrated in legacy Northeast/Rust Belt metros (finance, insurance, media, back-office) — collapsing the ROI of the high-tuition residential degree exactly where sticker prices are highest
- Flagship brands everywhere partially insulated (Michigan, UVa, Wisconsin) — shrinkage is region- AND stratum-specific

**Revenue shock (before headcount):**
- AI's tuition shock is a revenue event before a headcount event
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