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Massachusetts · Public charity

Accelerate Language and Learning Foundation

The mission of the organization is to improve the independence and functioning of those with language and learning disorders.

$42k
Granted FY2018
1
Grants FY2018
1
Organizations funded FY2018
Read the full brief
Median grant, FY2018
$41,667
Largest grant, FY2018
$41,667
States reached, FY2018
1
Total assets, FY2018
$704

Top grantees

Largest recipients by total granted, FY2018 to FY2018, and the share of each one’s budget the grants supplied at peak.

GranteeTotal grantedYearsShare of their budget
CHMC Otolaryngologic Foundation Inc$41,66710%

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How do I get to Accelerate Language and Learning Foundation?

Find your warmest path to Accelerate Language and Learning Foundation 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.

About Accelerate Language and Learning Foundation

How much does Accelerate Language and Learning Foundation give?
Accelerate Language and Learning Foundation reported 1 grants totaling $41,667 in its FY2018 IRS filing.
What does Accelerate Language and Learning Foundation fund?
By grant dollars over FY2018 to FY2018, its largest causes are Health (100%).
Who are Accelerate Language and Learning Foundation's largest grantees?
By total granted over FY2018 to FY2018: CHMC Otolaryngologic Foundation Inc ($42k).
Where is Accelerate Language and Learning Foundation based?
Accelerate Language and Learning Foundation is based in MA.

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 2018, released 2018. 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 no grant expense, so the figures above are from FY2018, the most recent year this funder made grants.

Source object · view filing

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