· Private foundation
The Lillian Jean Kaplan Foundation
Its FY2023 filing reports that it accepted unsolicited grant applications.
Where the money goes
Your grants by size, and where they go.
By grant size · FY2023
- Under $10k10 grants · $35k
- $10k–50k2 grants · $27k
| Recipient | Amount |
|---|---|
| BEZERRA DE MENEZES KARDECIAL SPIRTIST ASSOCATION | $15,526 |
| SACRED MOUNTAIN SANCTUARY | $11,700 |
| CULTURE'S EDGE | $7,551 |
| ASHEVILLE SCHOOL | $5,400 |
| Individual grant recipient | $4,380 |
| Individual grant recipient | $3,894 |
| PARDEE MEMORIAL HOSPITAL FOUNDATION | $3,200 |
| Individual grant recipient | $3,200 |
| CHILDFUND | $2,409 |
| TASK BRAZIL TRUST | $1,947 |
| SOS CHILDREN'S VILLAGES | $1,460 |
| NEEMAN FOUNDATION USA | $1,460 |
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.
Dollar for dollar, your grants (FY23–23) land where the poverty rate runs at 14%, against an area that typically sits at 14%. 57% of your dollars go to grantees based in above-average-need neighborhoods. 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 linein 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 — shown as context about the area, never attributed to your giving.
5 grantees tracked through their own filings, 2017–2025.
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 2017–2025, not grant rows in a single year — so this will not match the grant count on the cover. 5 of the 12 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.
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 set of overlaps that mostly run through you, not between each other.
Open a dossier: 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 The Lillian Jean Kaplan 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.