· Private foundation
J Angel 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.
What you funded, over time
Every grant placed by its stated purpose and the recipient’s mission, by year — across FY2019–2023.
Where the money goes
Your grants by size, and where they go.
By grant size · FY2023
- Under $10k1 grant · $1k
- $10k–50k1 grant · $10k
| Recipient | Amount |
|---|---|
| CHINA VILLAGE ORG | $10,000 |
| RAMUNION FOUNDATION OF USA | $1,000 |
Do your dollars go where the need is?
Each grant placed by the hardship in its grantee’s ZIP, then read against the area’s typical level.
Your US giving — 85% of grant dollars ($568k). The need read here covers only this US portion; the 15% that went abroad ($101k) is mapped below.
Your human-services grants (FY19–23, $42k) land where the poverty rate runs at 12%, against an area that typically sits at 10%. 52% of those dollars go to grantees based in above-average-need neighborhoods. Your grants spread fairly evenly across need levels.
Matched: human-services grants are those whose grantee’s IRS cause code is Human Services. Placed by people below the poverty linein the grantee’s ZIP, averaged from the tracts in that ZIP; grantee ZIP can differ from where services are delivered.
Beyond the US — 15% of all-years giving ($101k)
2 countries, by the recipient’s country on the filing.
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 — shown as context about the area, never attributed to your giving. International giving is mapped by the recipient’s country from the same 990 filings; comparable need data isn’t available at that grain.
Where the work is directed
The same grants, placed two ways — where each recipient sits, and where its stated purpose earmarks the money.
About 28% of J Angel 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.
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.
Global education programs
For reference, the grantee most central to the portfolio’s shape is Globalgiving Foundation Inc and the most unlike its peers is Dialogue China Inc. Resemblance is measured on each organization’s own IRS 990 mission text; it reflects how work is described, not its quality or impact.
11 grantees tracked through their own filings, 2017–2026.
Each one resolved to its own IRS returns and tracked year by year — your grant beside their revenue from every source. Association, dated; never a causal claim.
Counted here: distinct organizations you funded across 2017–2026, not grant rows in a single year — so this will not match the grant count on the cover. 11 of the 20 grantees resolved in that span have returns of their own we could reconcile; the rest are funded organizations whose filings we could not track year by year.
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
Go grantee by grantee — a decade per org, and how each moved after you funded them
A decade per grantee — revenue shaded, your grants as bars, all rows on one timeline.
- Who funds GIVE2ASIA ↗
- Who funds IMAGINATION LAB SCHOOL ↗
- Who funds ROUNDTABLE ACADEMY ↗
- Who funds TRUE LOVE FOR SPECIAL NEED FAMILIES INC ↗
- Who funds Dialogue China Inc ↗
- Who funds LIFE ACADEMY ↗
- Who funds ECLAT FOUNDATION ↗
- Who funds GLOBALGIVING FOUNDATION INC ↗
- Who funds VENTURA COLLEGE FOUNDATION ↗
- Who funds RAMUNION FOUNDATION OF USA ↗
- Who funds COOL EARTH ACTION USA INC ↗
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: Donor Advised Charitable Giving Inc · Amazonsmile Foundation
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.
Government reliance of your grantees
Every dot is one organization J Angel 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: 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 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.