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L Edwin & Mary C Hoppes Foundation at a glance

· Private foundation

L Edwin & Mary C Hoppes Foundation

Its FY2017 filing reports that it funds preselected organizations and did not take unsolicited requests; check the foundation's own site before ruling it out.

$17k
Granted FY2017
12
Grants FY2017
3
States reached
$7k
Largest
01What it fundsRead
02The needRead
03Its fieldRead
01What it funds
01FY2017 · 12 grants

Where the money goes

Grants by size, and the largest recipients.

$1,006
Median grant
3
States reached
$0
Total assets
Largest grants
RecipientAmount
GOOD SAMARITAN OUTREACH$6,655
AMERICAN CANCER SOCIETY$1,055
SALVATION ARMY$1,006
RED CROSS$1,006
MOOREFIELD TOWNSHIP FIRE DEPARTMENT$1,006
CATHOLIC SOCIAL SERVICES$1,006
CLARK COUNTY HISTORICAL SOCIETY$1,005
AMERICAN HEART ASSOCIATION$856
CARE$781
THINK TV NETWORK$781
PROJECT WOMAN$755
HABITAT FOR HUMANITY$755
02The need
02

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:

Its human-services grants (FY17–17, $2k) land where the poverty rate runs at 15%, against an area that typically sits at 11%. 100% of those dollars go to grantees based in above-average-need neighborhoods. Most of its grants land in higher-need ZIPs.

area typical 11%CATHOLIC SOCIAL SERVICES: $1k → 15%PROJECT WOMAN: $755 → 15%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
03the grantee network

7 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. 7 of the 12 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)
1
Early backer (in before they grew)
6/7
Grantees still filing
6/7
Grew since first funded

Where the money sits, by cause and then by grantee

GOOD SAMARITAN OUTREACH: $6,655 · OtherGOOD SAMARITAN OUTREACHAMERICAN CANCER SOCIETY: $1,055 · OtherAMERICAN CANCER SOCIETYMOOREFIELD TOWNSHIP FIRE DEPARTMENT: $1,006 · OtherMOOREFIELD TOWNSHIP FIRE DEPARTMENTSALVATION ARMY: $1,006 · OtherSALVATION ARMYRED CROSS: $1,006 · OtherRED CROSSHABITAT FOR HUMANITY INC: $755 · OtherHABITAT FOR HUMANITY INCCLARK COUNTY HISTORICAL SOCIETY: $1,005 · Arts & CultureCLARK COUNTY…Greater Dayton Public Television dba Think TV: $781 · Arts & CultureGreater Dayt…CATHOLIC SOCIAL SERVICES INC: $1,006 · Human ServicesCATHOLIC SO…PROJECT WOMAN OF SPRINGFIELD & CLARK COUNTY: $755 · Human ServicesPROJECT WOM…American Heart Association Inc: $856 · HealthCOOPERATIVE FOR ASSISTANCE AND RELIEF EVERYWHERE INC: $781 · International
Other$11,483Arts & Culture$1,786Human Services$1,761Health$856International$781

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

25%50%75%100%$10M$100Mgrantee revenue →↑ funder's share of their budgetCATHOLIC SOCIAL SERVICES INC: $1,006 over 1y, 0.0% of budgetCLARK COUNTY HISTORICAL SOCIETY: $1,005 over 1y, 0.2% of budgetAmerican Heart Association Inc: $856 over 1y, 0.0% of budgetCOOPERATIVE FOR ASSISTANCE AND RELIEF EVERYWHERE INC: $781 over 1y, 0.0% of budgetGreater Dayton Public Television dba Think TV: $781 over 1y, 0.0% of budgetPROJECT WOMAN OF SPRINGFIELD & CLARK COUNTY: $755 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.

Co-funders

Grantmakers whose grantees overlap with this funder’s far more than size alone predicts. Closer means stronger alignment; arcs show where they also fund each other. Here they form a set of overlaps that mostly run through this funder rather than between each other.

Amazonsmile Foundation
Amazonsmile FoundationWA3.3× affinity4 shared granteesties to 0 of 0Hover any node to trace its alignments.Compare side by side →

Open a dossier: Amazonsmile Foundation

How this is measured
Affinity is a Gamma-Poisson posterior co-funding rate, re-centered on the typical rate, so thin evidence shrinks toward no signal. Overlap is association, not proof of shared intent.

How much its grantees rely on government

Each dot is one organization L Edwin & Mary C Hoppes Foundation funds: left to right is the share of its income from government, bottom to top the share from L Edwin & Mary C Hoppes Foundation. Bigger dots raise more.

2024
’20’21’22’23’24’25
no gov · 00%0%1%3%5%funder's share of their income ↑0%10%20%30%40%share of the org’s income from government →
    no gov moneyreceives it· size = income
    0get no government money at all
    2report government grants on their 990 we could not trace to a source (not plotted)
    0rely on government for over half their income
    ⤢ axis zoomed · 0–40%
    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 12 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 2017, released 2017. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

    Source object · view filing

    Play a game based on L Edwin & Mary C Hoppes’ 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