· Private foundation
Wang Family 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 FY2017–2024.
Where the money goes
Your grants by size, and where they go.
By grant size · FY2024
- Under $10k2 grants · $12k
- $10k–50k3 grants · $46k
- $50k–250k3 grants · $375k
| Recipient | Amount |
|---|---|
| INTERNATIONAL ASSOCIATION OF LAW SCHOOLS | $192,007 |
| FIDELITY - DONOR ADVISED FUND | $100,000 |
| UC BERKELEY | $82,497 |
| MUSEUM TRUSTEE ASSOCIATION | $26,080 |
| ASIA SOCIETY | $10,000 |
| HARVARD LAW SCHOOL | $10,000 |
| KOZMINSKI LAW SCHOOL - BOARD | $7,442 |
| ASLI - ASIA LAW INSTITUTE | $4,959 |
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 (FY17–24) land where the poverty rate runs at 14%, against an area that typically sits at 12%. 74% 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.
Where the work is directed
The same grants, placed two ways — where each recipient sits, and where its stated purpose earmarks the money.
About 6% of Wang Family 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.
Who you back again
Which organizations you funded more than once, and which you funded a single time. Each grantee is matched to its own filings.
7 repeat relationships — 3 still active in FY2024, 4 since wound down; 5 grantees were first funded in FY2024 (too recent to call).
How the two cohorts compare
Organizations
Total granted
Still filing today
New vs renewed · share of each year
In FY2024, 69% of grant dollars renewed an existing relationship; $132k 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.
Backed again, and grew
Cornell University3× · 2017–2022 · $143k · revenue +59%- MTMUSEUM TRUSTEE ASSOCIATION2× · 2023–2024 · $29k · revenue +13%
- ILInternational Law Students Association3× · 2021–2023 · $3k · revenue +35%
Funded once
- IAInternational Association of Law Scone grant, 2021 · $132k
- NMNapa Medical Research Foundaone grant, 2021 · $10k
- FOFRIENDS OF UKRAINIAN JESSUP INCone grant, 2022 · $5k
Repeat = funded in two or more distinct years; growth and survival are read from each grantee’s own subsequent IRS filings.
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 16 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.
Government reliance of your grantees
Every dot is one organization Wang Family 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.
Warm introductions · Powered by PlinthPlus
How do I get to Wang Family Foundation?
Find your warmest path to Wang Family Foundation through trustees and officers whose names appear on both boards. Search for your organization and Plinth traces the shortest route it can evidence.
Each link is a name appearing on two organizations’ public IRS 990 filings, matched on that name and, where the filings support it, on location. A same-state match has geographic support, which is a second matching feature rather than confirmation that the two are one person; a cross-state one is the likeliest to be two people who share a name. Every hop shows its tier, low-confidence and distant paths are held back rather than guessed, and it is worth confirming the person before you use the introduction.