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· Private foundation

Rockefeller Archive Center

Its FY2025 filing reports that it accepted unsolicited grant applications.

$151k
Granted FY2025still arriving
49
Grants FY2025still arriving
16
States reached
$7k
Largest
01What it funds
01100% classified

What it funded, over time

Every grant placed by its stated purpose and the recipient’s mission, by year, FY2017 to 2025.

Health$975kEducation$41k
02FY2025 · 49 grants

Where the money goes

Grants by size, and the largest recipients.

$2,890
Median grant
16
States reached
$189M
Total assets
Largest grants
RecipientAmount
Individual grant recipient$7,200
Individual grant recipient$5,000
Individual grant recipient$5,000
Individual grant recipient$5,000
Individual grant recipient$5,000
Individual grant recipient$5,000
Individual grant recipient$5,000
Individual grant recipient$4,983
Individual grant recipient$4,837
Individual grant recipient$4,734
Individual grant recipient$4,137
Individual grant recipient$4,000
Individual grant recipient$4,000
Individual grant recipient$3,862
Individual grant recipient$3,792
02The need
03

Does the money reach high-need areas?

Each grant placed by the hardship in its grantee’s ZIP, against the area’s typical level.

US giving: 59% of grant dollars ($595k). The need read here covers only this US portion; the 41% that went abroad ($421k) is mapped below.

show:

Dollar for dollar, its grants (FY17–25) land where the poverty rate runs at 14%, against an area that typically sits at 12%. 64% of its dollars go to grantees based in above-average-need neighborhoods. Most of its grants land in higher-need ZIPs.

area typical 12%JOSEPH MALHEREK: $4k → 9%ELENA HRISTOVA: $3k → 11%XIA YU: $3k → 10%MARIA PAULA OROZCO ESPINEL: $5k → 11%EDREA MENDOZA: $4k → 9%KATHLEEN BERRIN: $4k → 10%DANIEL FRANKEN: $4k → 14%FABIAN OFFERT: $5k → 14%THE GRADUATE CENTER FOUNDATION INC: $10k → 17%OLIVIA ARMANDROFF: $4k → 10%JOSHUA U THEW: $4k → 20%YISHI LIU: $5k → 14%JORDAN BUCHANAN DOWNIE: $4k → 12%JESSICA ADLER: $3k → 15%JEANNE PETIT: $4k → 10%LAURA MARIA LOSS SCHWARZ: $5k → 16%EMILY R GIOIELLI: $4k → 18%HUIMIN WANG: $3k → 10%EVGUENIA DAVIDOVA: $4k → 12%MICHAEL A OSBORNE: $3k → 18%JOHNNY GOSHEN: $7k → 13%ERIKA WEINTHAL: $4k → 11%JOSEPH SHEPHARD: $10k → 16%TAYLOR COZZENS: $5k → 17%EVAN R WARD: $5k → 8%SARAH C MELLORS: $5k → 14%JILING DUAN: $4k → 18%RUISHENG ZHANG: $4k → 19%DAVID HAMMACK: $4k → 17%GAURAV C GARG: $5k → 9%KIMBERLY AKANO: $4k → 11%YUHONG JIANG: $5k → 7%FELIPE COLLA DE AMORIM: $4k → 12%VUK VUKOVIC: $3k → 11%THE GRADUATE CENTER FOUNDATION INC: $10k → 17%MEGAN RABY: $4k → 10%AARON ROM O MORALINA: $4k → 19%DAVID HAMMACK: $3k → 17%CHRISTINE PERALTA: $3k → 19%YUHONG JIANG: $5k → 7%JULIA CUMMISKEY: $4k → 19%THE GRADUATE CENTER FOUNDATION INC: $10k → 17%ELIZABETH SPAETH: $5k → 14%THE GRADUATE CENTER FOUNDATION INC: $10k → 17%KAZUSHI MINAMI: $5k → 10%ARO VELMET: $4k → 17%ZHEN CHENG: $5k → 17%ZHEN CHENG: $4k → 17%0%20%40%50%more need →
grant to an above-average-need area below average· circle size = grant amount
How this is measured
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.

Which US states its grants reach

ME
WA
MT
MN
IL
WI
MI
NY
MA
OR
IN
OH
PA
NJ
CT
RI
CA
UT
CO
MO
KY
VA
MD
KS
AR
TN
NC
SC
DC
HI
OK
MS
AL
GA
TX
FL

Beyond the US: 41% of all-years giving ($421k)

34 countries, by the recipient’s country on the filing.

grant dollars sentlessmore
United Kingdom$99k · 34 grants
Germany$39k · 12 grants
Brazil$21k · 8 grants
Mexico$19k · 6 grants
India$19k · 5 grants
Australia$19k · 4 grants
China$18k · 4 grants
Switzerland$18k · 5 grants
Italy$14k · 7 grants
Canada$14k · 8 grants
How this is measured
US grants placed by each grantee’s ZIP, which can differ from where services are delivered. Need from public data (U.S. Census/ACS, CDC PLACES, Eviction Lab, USDA), shown as context about the area, never attributed to the funder’s giving. International giving is mapped by the recipient’s country from the same 990 filings; comparable need data isn’t available at that grain.
03Its grantees
repeat funding

Who it funds again

Organizations funded in more than one year, against those funded once.

16%of every dollar goes to organizations it has funded before.
$166k · 22 repeat orgs$851k to everyone else

22 repeat relationships: 6 still active in FY2025, 16 since wound down; 43 grantees were first funded in FY2025 (too recent to call).

How the two cohorts compare

Re-uppedFunded once

Organizations

22
283

Total granted

$166k
$714k

Still filing today

5%
0%

New vs renewed · share of each year

In FY2025, 10% of grant dollars renewed an existing relationship; $136k went to new ones.

50%100%’17’18’19’20’21’22’23’24’25
RenewedFirst-time
How this is measured
First-time means a grantee’s first year in the filing window; renewed means funded in an earlier year too. The renewed share climbs naturally as a portfolio matures, so the signal is a year that bucks it (a wave of new grantees). 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

  • TG
    THE GRADUATE CENTER FOUNDATION INC
    4× · 2021–2024 · $40k · revenue +89%
  • IG
    Individual grant recipient
    7× · 2017–2025 · $20k
  • IG
    Individual grant recipient
    7× · 2017–2025 · $16k

Funded once

  • IG
    Individual grant recipient
    one grant, 2024 · $10k
  • IG
    Individual grant recipient
    one grant, 2019 · $5k
  • IG
    Individual grant recipient
    one grant, 2018 · $5k
How this is measured

Repeat means funded in two or more distinct years. Growth and survival are read from each grantee’s own subsequent IRS filings.

04Its field
04the grantee network

1 grantees tracked through their own filings, 2017–2025.

Each grant beside the grantee’s revenue from every source, year by year.

How this is measured

Counted here: distinct organizations funded across 2017 to 2025, not grant rows in a single year, so this will not match the grant count on the cover. 1 of the 348 grantees resolved in that span have returns of their own we could reconcile.

Each grantee is resolved to its own IRS returns. Association, dated; never a causal claim.

0
Load-bearing (≥25% of a budget)
0
Early backer (in before they grew)
1/1
Grantees still filing
1/1
Grew since first funded

Where the money sits, by cause and then by grantee

THE GRADUATE CENTER FOUNDATION INC: $40,000 · Other+199 more: $765,021 · Other+199 more
Other$805,021

Showing the 200 largest grantees by grant value.

Each grantee by its size and the funder’s share of it; top left is load-bearing

25%50%75%100%grantee revenue →↑ funder's share of their budgetTHE GRADUATE CENTER FOUNDATION INC: $40,000 over 4y, 0.1% of budget
Grantee by grantee: a decade per organization, before and after funding

A decade per grantee: revenue shaded, grants as bars, all rows on one timeline.

  • Who funds THE GRADUATE CENTER FOUNDATION INC ↗

How much its grantees rely on government

Each dot is one organization Rockefeller Archive Center funds: left to right is the share of its income from government, bottom to top the share from Rockefeller Archive Center. Bigger dots raise more.

2025
’20’21’22’23’24’25
no gov · 00%0%1%3%5%funder's share of their income ↑0%1%3%4%5%share of the org’s income from government →
    no gov moneyreceives it· size = income
    0get no government money at all
    0rely on government for over half their income
    ⤢ axis zoomed · 0–5%
    typical government reliance, FY20–25
    How this is measured
    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 a grant caused the public funding. Coverage is precision-first, a floor rather than 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 to 24 months.

    On method. Every financial figure here is read from IRS e-file XML, the funder’s own 990/990-PF, and from the multi-year returns of the 348 grantees we resolved, each linked to its source. Grantee outcomes are each organization’s own program-service reporting (Form 990, Part III), read as association with funding, never as caused by it. Low-confidence name matches are suppressed rather than guessed. How we build these →

    How this is measured
    Each figure carries one of six labels. Filed is what the funder reported on its return. Official is another government record about an organization, such as a federal award or a charity register, joined by name where no shared identifier exists. Resolved is an identity we worked out where the filing named a recipient without an EIN, kept only above a measured confidence threshold. Computed is arithmetic over those, like themes, portfolio clusters and co-funder strength. Context is a statistic about a place rather than about an organization, which is what the need overlay is: it describes the area a grantee’s address sits in, not where its work lands. Inferred is drawn by a model from text, like the partnerships read out of public news and organization websites. Each is labeled where it appears.

    Generated from the IRS Form 990-PF e-file return for fiscal year 2025, released 2025. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

    Source object · view filing

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