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Arizona · Public charity

Earn To Learn

Our mission is empowering students to achieve their goals and be workforce ready with little to no student debt. We accomplish this mission through an innovative, four-pillar approach to financial preparation including:- matched savings scholarships: student savings are matched 8:1 through a public-private funding model providing up to…

$25k
Granted FY2019
1
Grants FY2019
1
Organizations funded FY2019
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Median grant, FY2019
$25,000
Largest grant, FY2019
$25,000
States reached, FY2019
1
Total assets, FY2019
$1.3M

Top grantees

Largest recipients by total granted, FY2019 to FY2019, and the share of each one’s budget the grants supplied at peak.

GranteeTotal grantedYearsShare of their budget
United Way$25,00010%

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About Earn To Learn

How much does Earn To Learn give?
Earn To Learn reported 1 grants totaling $25,000 in its FY2019 IRS filing.
Who are Earn To Learn's largest grantees?
By total granted over FY2019 to FY2019: United Way ($25k).
Where is Earn To Learn based?
Earn To Learn is based in AZ.

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 but names no grant recipient (grants abroad are filed by region only, and grants under $5,000 are not itemized), so the figures above are from FY2019, the most recent year this funder named its grantees.

Source object · view filing

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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