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· Public charity

Massachusetts Indian Association

The mission of MASSACHUSETTS INDIAN ASSOCIATION is to provide scholarship funds to native american indian students attending colleges and universities in the united states and provide funds to nonprofit universities for the benefit of students.

$1.2M
Granted FY2024still arriving
1
Grants FY2024still arriving
1
States reached
$59k
Largest
01What it funds
01FY2024 · 1 grant

Where the money goes

Grants by size, and the largest recipients.

How this is measured
The 1 grants below total $59,114, the rows itemized in this filing. The $1,162,756 headline is the total grant expense on the return; the other $1,103,642 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.
$59,114
Median grant
1
States reached
$15k
Total assets
Largest grants
RecipientAmount
SINTE GLESKA UNIVERSITY$59,114
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:

Dollar for dollar, its grants (FY24–24) land where the poverty rate runs at 40%, against an area that typically sits at 17%. 100% of its dollars go to grantees based in above-average-need neighborhoods. Most of its grants land in higher-need ZIPs.

area typical 17%SINTE GLESKA UNIVERSITY: $59k → 40%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

3 grantees tracked through their own filings, 2024–2024.

Each grant beside the grantee’s revenue from every source, year by year.

How this is measured

Counted here: distinct organizations funded across 2024 to 2024, 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)
0
Early backer (in before they grew)
3/3
Grantees still filing
1/3
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 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 tightly interlocked group: most of these funders back each other's grantees too.

Donor Advised Charitable Giving IncCO7.3× affinity4 shared granteesties to 1 of 1Hover any node to trace its alignments.Compare side by side →

Open a dossier: Donor Advised Charitable Giving Inc · 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.
04Through Plinth

Warm introductions · Powered by PlinthPlus

How do I get to Massachusetts Indian Association?

Find your warmest path to Massachusetts Indian Association 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 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 2024, released 2024. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

Source object · view filing

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