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· Private foundation

The Katalina and Michael Simon Foundation

Its FY2024 filing reports that it funds preselected organizations and did not take unsolicited requests; check the foundation's own site before ruling it out.

$350k
Granted FY2024still arriving
4
Grants FY2024still arriving
3
States reached
$225k
Largest

Read this first · the figures below need context

64% of The Katalina and Michael Simon Foundation’s FY2024 grant dollars went to University Of Notre Dame Du Lac, not to grantees.

Its money now reaches organizations through that sponsor, which does not report who recommended each grant. FY2024 names 3 organizations directly, so a portfolio cannot be read from it.

Organizations named directly on the return

1
’21
4
’22
3
’23
3
’24

Amber years are those where most dollars went to a sponsor.

01What it funds
01100% classified

What it funded, over time

Every grant placed by its stated purpose and the recipient’s mission, by year, FY2021 to 2024.

Education$1.4M
02FY2024 · 4 grants

Where the money goes

Grants by size, and the largest recipients.

By grant size · FY2024

  • $10k–50k1 grant · $25k
  • $50k–250k3 grants · $325k
$50,000
Median grant
3
States reached
$1.5M
Total assets
Largest grants
RecipientAmount
UNIVERSITY OF NOTRE DAME DU LAC$225,000
UNIVERSITY OF DAYTON$50,000
CONCORD ACADEMY$50,000
CARROLL SCHOOL CORP$25,000
02The need
03

Does the money reach high-need areas?

Each grant placed by the hardship in its grantee’s ZIP, against the area’s typical level.

show:

Dollar for dollar, its grants (FY21–24) land where the poverty rate runs at 11%, against an area that typically sits at 8%. 100% of its dollars go to grantees based in above-average-need neighborhoods. Most of its grants land in higher-need ZIPs.

area typical 8%CARROLL SCHOOL CORP: $200k → 8%UNIVERSITY OF NOTRE DAME DU LAC: $225k → 13%UNIVERSITY OF DAYTON: $50k → 14%CARROLL SCHOOL CORP: $165k → 8%UNIVERSITY OF NOTRE DAME DU LAC: $200k → 13%UNIVERSITY OF DAYTON: $25k → 14%CARROLL SCHOOL CORP: $25k → 8%UNIVERSITY OF NOTRE DAME DU LAC: $200k → 13%UNIVERSITY OF DAYTON: $20k → 14%CONCORD ACADEMY: $50k → 8%UNIVERSITY OF NOTRE DAME DU LAC: $25k → 13%CONCORD ACADEMY: $50k → 8%CONCORD ACADEMY: $50k → 8%RIVERS SCHOOL CORPORATION: $63k → 8%CARROLL SCHOOL CORP: $25k → 8%TRUSTEES OF THE LAWRENCE ACADEMY AT GROTON: $50k → 8%0%20%40%50%more need →
grant to an above-average-need area below average· circle size = grant amount
How this is measured
Matched: human-services grants are those whose grantee’s IRS cause code is Human Services. Placed by people below the poverty line in the grantee’s ZIP, averaged from the tracts in that ZIP.
How this is measured
US grants placed by each grantee’s ZIP, which can differ from where services are delivered. Need from public data (U.S. Census/ACS, CDC PLACES, Eviction Lab, USDA), shown as context about the area, never attributed to the funder’s giving.
03Its grantees
04Its field
04the grantee network

6 grantees tracked through their own filings, 2017–2025.

Each grant beside the grantee’s revenue from every source, year by year.

How this is measured

Counted here: distinct organizations funded across 2017 to 2025, not grant rows in a single year, so this will not match the grant count on the cover.

Each grantee is resolved to its own IRS returns. Association, dated; never a causal claim.

0
Load-bearing (≥25% of a budget)
0
Early backer (in before they grew)
6/6
Grantees still filing
4/6
Grew since first funded

Where the money sits, by cause and then by grantee

University of Notre Dame du Lac: $650,000 · EducationUniversity of Notre Dame du LacTHE CARROLL SCHOOL: $415,000 · EducationTHE CARROLL SCHOOLCONCORD ACADEMY: $150,000 · EducationCONCORD ACADEMYUniversity of Dayton: $95,000 · EducationUniversity of DaytonTRUSTEES OF LAWRENCE ACADEMY AT GROTON MA CORP: $50,000 · EducationTHE RIVERS SCHOOL CORPORATION: $62,500 · Other
Education$1,360,000Other$62,500

Each grantee by its size and the funder’s share of it; top left is load-bearing

25%50%75%100%$100Mgrantee revenue →↑ funder's share of their budgetUniversity of Notre Dame du Lac: $650,000 over 3y, 0.0% of budgetTHE CARROLL SCHOOL: $415,000 over 4y, 0.6% of budgetCONCORD ACADEMY: $150,000 over 3y, 0.1% of budgetUniversity of Dayton: $95,000 over 2y, 0.0% of budgetTHE RIVERS SCHOOL CORPORATION: $62,500 over 1y, 0.2% of budgetTRUSTEES OF LAWRENCE ACADEMY AT GROTON MA CORP: $50,000 over 1y, 0.1% of budget
Grantee by grantee: a decade per organization, before and after funding

A decade per grantee: revenue shaded, grants as bars, all rows on one timeline.

Co-funders

Grantmakers whose grantees overlap with this funder’s far more than size alone predicts. Closer means stronger alignment; arcs show where they also fund each other. Here they form a tightly interlocked group: most of these funders back each other's grantees too.

Fidelity FoundationMA13.3× affinity4 shared granteesties to 9 of 9Hover any node to trace its alignments.Compare side by side →

Open a dossier: Fidelity Foundation · Boston Foundation Inc · American Endowment Foundation · Morgan Stanley Global Impact Funding Trust Inc · National Philanthropic Trust · Vanguard Charitable Endowment Program · American Online Giving Foundation Inc · Donor Advised Charitable Giving Inc · Fidelity Investments Charitable Gift Fund · Amazonsmile Foundation

How this is measured
Affinity is a Gamma-Poisson posterior co-funding rate, re-centered on the typical rate, so thin evidence shrinks toward no signal. Overlap is association, not proof of shared intent.

How much its grantees rely on government

Each dot is one organization The Katalina and Michael Simon Foundation funds: left to right is the share of its income from government, bottom to top the share from The Katalina and Michael Simon Foundation. Bigger dots raise more.

2025
’20’21’22’23’24’25
no gov · 30%0%1%3%5%funder's share of their income ↑0%8%15%22%30%share of the org’s income from government →
    no gov moneyreceives it· size = income
    3get no government money at all
    1report government grants on their 990 we could not trace to a source (not plotted)
    0rely on government for over half their income
    ⤢ axis zoomed · 0–30%
    typical government reliance, FY20–25
    How this is measured
    Government income is each org’s traced federal awards (USASpending grants and contracts) plus state payments (open checkbooks) as a share of its total revenue (IRS Form 990); the self-reported government-grant line (990 line 1e) is carried for cross-check: a grantee that reports government grants we could not trace to a source is left off the chart rather than shown as receiving none. An association, not a claim that a grant caused the public funding. Coverage is precision-first, a floor rather than a census; state records exist for 9 states, so a grantee outside them shows no state figure (dimmed) rather than a false zero. Federal award amounts are obligations, which can span years, so a single-year share is indicative. 990 filings lag 12 to 24 months.

    On method. Every financial figure here is read from IRS e-file XML, the funder’s own 990/990-PF, and from the multi-year returns of the 6 grantees we resolved, each linked to its source. Grantee outcomes are each organization’s own program-service reporting (Form 990, Part III), read as association with funding, never as caused by it. Low-confidence name matches are suppressed rather than guessed. How we build these →

    How this is measured
    Each figure carries one of six labels. Filed is what the funder reported on its return. Official is another government record about an organization, such as a federal award or a charity register, joined by name where no shared identifier exists. Resolved is an identity we worked out where the filing named a recipient without an EIN, kept only above a measured confidence threshold. Computed is arithmetic over those, like themes, portfolio clusters and co-funder strength. Context is a statistic about a place rather than about an organization, which is what the need overlay is: it describes the area a grantee’s address sits in, not where its work lands. Inferred is drawn by a model from text, like the partnerships read out of public news and organization websites. Each is labeled where it appears.

    Generated from the IRS Form 990-PF e-file return for fiscal year 2024, released 2024. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

    Source object · view filing

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