Skip to content
Association of Pediatric Hematology/Oncology Nursesinc at a glanceMostly funded, not a grantmaker: see who funds it →

· Public charity

Association of Pediatric Hematology/Oncology Nursesinc

The Association of Pediatric Hematology/Oncology Nurses, Inc.

$10k
Granted FY2020
1
Grants FY2020
1
States reached
$10k
Largest
01What it fundsRead
02The needRead
03Its fieldRead
04Through PlinthRead
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 2020.

Science & Tech$30kHealth$10k
02FY2020 · 1 grant

Where the money goes

Grants by size, and the largest recipients.

$10,000
Median grant
1
States reached
$1.7M
Total assets
Largest grants
RecipientAmount
RUTGERS UNIVERSITY$10,000
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.

show:

Dollar for dollar, its grants (FY17–20) land where the poverty rate runs at 12%, against an area that typically sits at 12%. 50% of its dollars go to grantees based in above-average-need neighborhoods. Its grants spread fairly evenly across need levels.

area typical 12%UNIVERSITY OF CALIFORNIA LA: $10k → 14%UNIVERSITY OF CONNECTICUT: $10k → 11%ST JUDES RESEARCH HOSPTIAL: $10k → 17%RUTGERS UNIVERSITY: $10k → 8%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.
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.
03Its 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 4 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

UNIVERSITY OF CONNECTICUT: $10,000 · OtherUNIVERSITY OF CONNECTICUTREGENTS UNIV OF CALIFORNIA: $10,000 · OtherREGENTS UNIV OF CALIFORNIARUTGERS UNIVERSITY: $10,000 · OtherRUTGERS UNIVERSITYST JUDE CHILDREN'S RESEARCH HOSPITAL INC: $10,000 · HealthST JUDE CHILDREN'S RESEARCH …
Other$30,000Health$10,000

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 budgetST JUDE CHILDREN'S RESEARCH HOSPITAL INC: $10,000 over 1y, 0.0% 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 ST JUDE CHILDREN'S RESEARCH HOSPITAL INC ↗

How much its grantees rely on government

Each dot is one organization Association of Pediatric Hematology/Oncology Nursesinc funds: left to right is the share of its income from government, bottom to top the share from Association of Pediatric Hematology/Oncology Nursesinc. 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%3%5%8%10%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 · 0–10%
    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.
    04Through Plinth

    Warm introductions · Powered by PlinthPlus

    How do I get to Association of Pediatric Hematology/Oncology Nursesinc?

    Find your warmest path to Association of Pediatric Hematology/Oncology Nursesinc 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.

    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 4 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 e-file return for fiscal year 2020, released 2020. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

    Possibly out of date. A more recent filing (FY2024) is on record and reports $5k of grant expense, but none of it to a named recipient. On a Form 990 that can mean grants abroad, filed by region only (Schedule F), grants under $5,000, which are not itemized, or a schedule referenced as an attachment the e-file does not carry. The figures above are therefore from FY2020, the most recent year this funder named its grantees.

    Source object · view filing

    Play a game based on Association of Pediatric Hematology/Oncology Nursesinc’s filings →

    More from the funding graph

    The unnamed billions
    grants reported with no recipient in the public record
    The regranting layer
    51% of grant dollars land in the regranting layer
    The DAF merry-go-round
    $9.7B circulates between donor-advised funds
    The endowment market
    who holds foundation money, and what just moved
    The camps
    funders cluster by geography, not ideology
    By state
    where grant money is based, and what stays home