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Wabash Valley Goodwill Inc at a glanceAlso receives grants: funding profile →

· Public charity

Wabash Valley Goodwill Inc

Goodwill industries is a nonprofit provider of employment and other critical community based services for people who have a disability, people who lack education or job experience, households facings economic challenges, and others in need.

$27k
Granted FY2019
1
Grants FY2019
1
States reached
$11k
Largest
01What it fundsRead
02The needRead
03Its fieldRead

Read this first · the figures below need context

100% of Wabash Valley Goodwill Inc’s FY2019 grant dollars went to Wabash Valley Community Foundation Inc, not to grantees.

Its money now reaches organizations through that sponsor, which does not report who recommended each grant. FY2019 names 0 organizations directly, so a portfolio cannot be read from it.

Organizations named directly on the return

0
’17
0
’18
0
’19

Amber years are those where most dollars went to a sponsor.

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 2019.

Education$32k
02FY2019 · 1 grant

Where the money goes

Grants by size, and the largest recipients.

How this is measured
The 1 grants below total $11,000, the rows itemized in this filing. The $26,578 headline is the total grant expense on the return; the other $15,578 is giving the schedule does not break out (grants under the $5,000 itemization floor, grants to individuals, grants on other schedules). Every figure below describes the itemized rows only.
$11,000
Median grant
1
States reached
$13M
Total assets
Largest grants
RecipientAmount
WABASH VALLEY COMMUNITY FOUNDATION - GW TENNIS FUND$11,000
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 (FY17–19) land where the poverty rate runs at 19%, against an area that typically sits at 19%. 0% of its dollars go to grantees based in above-average-need neighborhoods. Its grants skew toward lower-need ZIPs.

area typical 19%WABASH VALLEY COMMUNITY FOUNDATION - GW TENNIS FUND: $11k → 19%WABASH VALLEY COMMUNITY FOUNDATION - GW TENNIS FUND: $11k → 19%WABASH VALLEY COMMUNITY FOUNDATION - GW TENNIS FUND: $10k → 19%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.

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)
1/1
Grantees still filing
1/1
Grew since first funded

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 budgetWABASH VALLEY COMMUNITY FOUNDATION INC: $32,000 over 3y, 0.3% 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.

How much its grantees rely on government

Each dot is one organization Wabash Valley Goodwill Inc funds: left to right is the share of its income from government, bottom to top the share from Wabash Valley Goodwill Inc. 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 1 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 2019, released 2019. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

    Possibly out of date. A more recent filing (FY2025) is on record and reports no grant expense, so the figures above are from FY2019, the most recent year this funder made grants.

    Source object · view filing

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