· Private foundation
Chiang Ching-Kuo Foundation for International Scholarly Exchange (Usa)
Its FY2025 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 FY2017–2020.
Where the money goes
Your grants by size, and where they go.
| Recipient | Amount |
|---|---|
| University of Washington | $8,000 |
| Hui-Wen V Groeling | $7,404 |
| Columbia University | $5,000 |
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 — 84% of grant dollars ($446k). The need read here covers only this US portion; the 16% that went abroad ($88k) is mapped below.
Dollar for dollar, your grants (FY17–20) land where the poverty rate runs at 15%, against an area that typically sits at 10%. 94% 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.
Which US states your grants reach
Beyond the US — 16% of all-years giving ($88k)
4 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 990filings; comparable need data isn’t available at that grain.
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.
And the relationships you keep tend to grow: grantees you re-up on have seen median revenue of +51% since the first grant, against +28% for the ones you funded once.
6 repeat relationships — 1 still active in FY2020, 5 since wound down; 1 grantees were first funded in FY2020 (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 FY2020, 52% of grant dollars renewed an existing relationship; $7k 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
- ACAMERICAN COUNCIL OF LEARNED SOCIETIES2× · 2018–2019 · $250k · revenue +17%
JOHNS HOPKINS UNIVERSITY2× · 2017–2019 · $20k · revenue +64%
DUKE UNIVERSITY2× · 2017–2019 · $16k · revenue +51%
Funded once
UNIVERSITY OF PITTSBURGHgraduatedone grant, 2019 · $60k · revenue +28%- UOUniversity of California Los Angelesone grant, 2017 · $20k
- IGIndividual grant recipientone grant, 2017 · $20k
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 15 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 Chiang Ching-Kuo Foundation for International Scholarly Exchange (Usa) 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.
- Johns Hopkins University — 11% of income from government
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.
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