Loading…
Loading…
· Private foundation
This foundation does not accept unsolicited requests — it funds preselected organizations.
By grantee IRS cause code (NTEE).
A cause breakdown isn’t shown here: 40% of MARGARET A CARGILL FOUNDATION’s grantee dollars go to organizations outside the IRS cause taxonomy (common for large international and research funders), so a chart would be mostly “unclassified” and misrepresent the portfolio.
Beneath the NTEE codes, this is what the grant descriptions actually say.
…and in their own words, year by year
Words distinctive to each year’s grant purposes (TF-IDF) · event-driven terms in cyan.
Your grants by size, and where they go.
By grant size · FY2024
Each grant placed by the hardship in its grantee’s ZIP, then read against the area’s typical level.
Your human-services grants (FY17–24, $35.3M) land where the poverty rate runs at 13% — the area typically sits at 10%. 88% of those dollars reach neighborhoods with above-average need. Most of your grants land in higher-need ZIPs.
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; grantee ZIP can differ from where services are delivered.
US grants placed by each grantee’s ZIP, which can differ from where services are actually delivered. Need from public data — U.S. Census/ACS, CDC PLACES, Eviction Lab, USDA, United Way ALICE — shown as context about the area, never attributed to your giving.
The same grants, placed two ways — where each recipient sits, and where its stated purpose earmarks the money.
About 7% of MARGARET A CARGILL FOUNDATION’s grant dollars are earmarked, by their stated purpose, for a different county than the recipient’s own address — money that lands at a nonprofit in one place but is meant to do its work in another.
Recipient view: each grant at its grantee’s ZIP, mapped to a county. Directed view: each grant at the county its stated purpose names, falling back to the recipient’s county when the purpose names no place; US grants only. A county shows only if it carries the top 95% of that view’s dollars. Purposes are read from the foundation’s own 990 grant descriptions.
Which organizations you funded more than once, and which you funded a single time. Each grantee is matched to its own filings.
And the relationships you keep tend to grow: grantees you re-up on have seen median revenue of +46% since the first grant, against +39% for the ones you funded once.
547 repeat relationships — 181 still active in FY2024, 366 since wound down; 75 grantees were first funded in FY2024 (too recent to call).
How the two cohorts compare
Organizations
Total granted
Median revenue growth · since first grant
Still filing today
New vs renewed · share of each year
In FY2024, 87% of grant dollars renewed an existing relationship; $19M went to new ones.
Where new relationships form · theme of each grantee’s first grant
First-time = a grantee’s first year in your filing window; renewed = funded in an earlier year too. As a portfolio matures the renewed share naturally climbs — once funded, an org stays “renewable” — so the signal is the years that buck it (a new-grantee intake wave). The earliest year is left-censored: relationships that predate the data read as “new.” Theme is the grantee’s IRS cause.
Repeat = funded in two or more distinct years; growth and survival are read from each grantee’s own subsequent IRS filings.
The map has a center of gravity: the average direction from the rest of the sector toward the organizations the foundation funds — the shape of its giving. Scoring every nonprofit along that direction surfaces the ones that look most like the portfolio. These are the closest matchesthat aren’t grantees — a resemblance in what they say they do, not a recommendation.
To maintain a high quality of life for all minnesotans.
Be the leading voice of medicine to make minnesota the healthiest state & the best place to practice
Embolden creative leaders to transform society through equity, empathy, & imagination.
Advance public policy & job growth strategies to create an environment for businesses to prosper
Invest in nonprofits, programs, collaborations that equip, empower and create opportunities for all to thrive.
Advancing a vital profession, vibrant communities, and architecture that endures.
Grow businesses, build wealth and increase reinvestement in the african communities of minnesota
Offer a challenging education that develops the qualities of mind, spirit and body for students.
See schedule o. the minnesota center for environmental advocacy is a nonprofit organization that uses law, science and research to protect minnesota's environment, its natural resources and the health of its people.
Sparking children's learning through play
Makes strategic investments in proven and promising schools, providing the expert guidance, funding resources to create a community of great schools.
Led by minnesota state university students, we are the inclusive voice for all future, current, and former students. we actively work to represent and support minnesota state university students and advocate at a system, local, state, and…
For reference, the grantee most central to the portfolio’s shape is Amherst H Wilder Foundation and the most unlike its peers is The Museum of Russian Art. Resemblance is measured on each organization’s own IRS 990 mission text; it reflects how work is described, not its quality or impact.
For each theme you fund, this compares how the sector’s money is shifting with how your own giving is shifting.
Sector change and giving change are each shown relative to their own range, growing (right) or shrinking (left); both normalized, so inflation isn’t mistaken for growth.
Your grantees are a median of 38 years old; the field is 16. You back the established end — and your money leans older still.
The field is 22% startups (under 5 years old) — 2% of your grantees by number, and just 0% of your money.
The orgs you fund almost never close — 0.9% lost their exemption, against 11% of the field you don’t fund.
Age = years since IRS exemption (a founding proxy). “Closed” = auto-revocation for 3 years of non-filing — a floor on closure, not proof, and bigger established orgs lapse least. Association, not causation.
Each one resolved to its own IRS returns and tracked year by year — your grant beside their revenue.
Where your money sits — by cause, then by grantee
Each org by its size and your share of it — top-left is where you’re load-bearing
A decade per grantee — revenue shaded, your grants as bars, all rows on one timeline.
The grantmakers whose grantees overlap with yours far more than size alone predicts. Each orbits closer the stronger the alignment; the arcs between them show where they also fund each other. Here it reads as a tightly interlocked camp — most of these funders back each other's grantees too.
Open a dossier: Saint Paul & Minnesota Foundation · The McKnight Foundation · The K Foundation · Fr Bigelow Foundation · Pohlad Family Foundation · Target Foundation · The Minneapolis Foundation · Minnesota Community Foundation · The Jamf Nation Global Foundation · Greater Twin Cities United Way · Mortenson Family Foundation · Otto Bremer Trust
Affinity is a Gamma-Poisson posterior co-funding rate, re-centered on the typical rate, so thin evidence shrinks toward no signal. A research starting point: overlap is association, not proof of shared intent.
Every dot is one organisation MARGARET A CARGILL FOUNDATION funds. Left–right is the share of its income from government; up–down is the share from you. Bigger dots raise more. Filter to federal or a single department — and drag the year to watch it move.
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. An association, not a claim that your grant caused the public funding. Coverage is precision-first — a floor, not 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 12–24 months.
Through Plinth
This dossier was generated cold from public filings. In Plinth it’s a working system — every applicant assessed and every grant monitored. Here’s a taste, run on one of your grantees: THUNDERHEART MEDIA INC.
Agentic due diligence · confidence × risk
~18 months of operating runway; revenue grew over 7 filed years.
7 years of Form 990 filings, still active; revenue up 5.7× since.
US 501(c)(3); EIN 814842057 on file with current IRS Form 990 filings.
Board composition & governance documents — verified live in Plinth from the applicant.
OFAC / UN sanctions screening — run live in Plinth at assessment.
Staffing, M&E and activity alignment — assessed live in Plinth from submitted proposals.
Live · Plinth’s real DD engine
Run the actual assessment on THUNDERHEART MEDIA INC, cold from public data.
Generated live from public IRS filings + open web sources by Plinth’s agentic engine. Shown as an illustration of the product, not a formal assessment.
Post-award monitoring · continuous checks
What you see here is static and public. In Plinth it’s operational — the full six-pillar framework on every applicant (with their own documents + live registry and sanctions checks), monitoring dashboards on every award, custom board reports, and eligibility routing for intake.
Preview generated from this grantee’s public IRS filings and independent reporting. Pillars marked “live in Plinth” require the applicant’s submitted documents. Shown as illustration, not a formal assessment.
Warm introductions · Powered by PlinthPro
Find your warmest path to Margaret a Cargill Foundation through people who sit on both boards. Search for your organization and Plinth traces the introduction across shared trustees and officers.
Every link is a documented governance overlap in public IRS 990 filings — not a personal network — and each hop carries its own confidence tier. Low-confidence or distant paths are held back rather than guessed.