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Buckeye Lake Moose 2434

Fraternal organization

$176k
Granted FY2026still arriving
5
Grants FY2026still arriving
1
States reached
$32k
Largest
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 2026.

Education$390kArts & Culture$86kHuman Services$56kYouth Development$26kRecreation & Sports$8kHealth$6k
02FY2026 · 5 grants

Where the money goes

Grants by size, and the largest recipients.

How this is measured
The 5 grants below total $161,310, the rows itemized in this filing. The $175,890 headline is the total grant expense on the return; the other $14,580 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.
$32,262
Median grant
1
States reached
$1.0M
Total assets
Largest grants
RecipientAmount
Lakewood Ed Foun$32,262
Millersport HS$32,262
Harcum House$32,262
Sheridan HS$32,262
OSMA Museum$32,262
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:

Its human-services grants (FY25–26, $39k) land where the poverty rate runs at 9%, against an area that typically sits at 11%. 0% of those dollars go to grantees based in above-average-need neighborhoods. Its grants skew toward lower-need ZIPs.

area typical 11%Harcum House: $32k → 9%Harcum House: $6k → 9%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 grantees
repeat funding

Who it funds again

Organizations funded in more than one year, against those funded once.

98%of every dollar goes to organizations it has funded before.
$561k · 6 repeat orgs$12k to everyone else

Grantees it renews have grown median revenue +766% since the first grant, against +39% for those funded once.

6 repeat relationships: 5 still active in FY2026, 1 since wound down.

How the two cohorts compare

Re-uppedFunded once

Organizations

6
2

Total granted

$561k
$12k

Median revenue growth · since first grant

+766%
+39%

Still filing today

33%
50%

New vs renewed · share of each year

In FY2026, 100% of grant dollars renewed an existing relationship; $0 went to new ones.

50%100%’17’18’19’20’21’22’23’24’25’26
RenewedFirst-time

Where new relationships form · theme of each grantee’s first grant

’17’18’19’20’21’22’23’24’25’26
HealthMembership BenefitHuman ServicesOther
How this is measured
First-time means a grantee’s first year in the filing window; renewed means funded in an earlier year too. The renewed share climbs naturally as a portfolio matures, so the signal is a year that bucks it (a wave of new grantees). The earliest year is left-censored: relationships that predate the data read as new. Theme is the grantee’s IRS cause.

Backed again, and grew

  • MH
    Millersport HS
    10× · 2017–2026 · $133k
  • LE
    LAKEWOOD EDUCATION FOUNDATION
    10× · 2017–2026 · $133k
  • SH
    Sheridan HS
    10× · 2017–2026 · $133k

Funded once

  • MF
    MAKE-A-WISH FOUNDATION OF OH KY & INgraduated
    one grant, 2017 · $6k · revenue +39%
  • BS
    BLUE STAR MOTHERS OF AMERICA INC
    one grant, 2017 · $6k
How this is measured

Repeat means funded in two or more distinct years. Growth and survival are read from each grantee’s own subsequent IRS filings.

04Its field
04the grantee network

3 grantees tracked through their own filings, 2017–2026.

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 2026, not grant rows in a single year, so this will not match the grant count on the cover. 3 of the 8 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)
2
Early backer (in before they grew)
3/3
Grantees still filing
3/3
Grew since first funded

Where the money sits, by cause and then by grantee

Millersport HS: $133,070 · OtherMillersport HSLAKEWOOD EDUCATION FOUNDATION: $132,637 · OtherLAKEWOOD EDUCATION FOUNDATIONSheridan HS: $132,637 · OtherSheridan HS+2 more: $17,349 · OtherOHIO STATE MOOSE ASSOCIATION MUSEUM INC: $111,964 · Membership BenefitOHIO STATE MOOSE ASSOC…HARCUM HOUSE: $38,665 · Human ServicesMAKE-A-WISH FOUNDATION OF OH KY & IN: $5,764 · Health
Other$415,693Membership Benefit$111,964Human Services$38,665Health$5,764

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

25%50%75%100%$10Mgrantee revenue →↑ funder's share of their budgetOHIO STATE MOOSE ASSOCIATION MUSEUM INC: $111,964 over 7y, 1.1% of budgetMAKE-A-WISH FOUNDATION OF OH KY & IN: $5,764 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.

  • Who funds OHIO STATE MOOSE ASSOCIATION MUSEUM INC ↗
  • Who funds HARCUM HOUSE ↗
  • Who funds MAKE-A-WISH FOUNDATION OF OH KY & IN ↗

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 FoundationWA2.1× 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 Buckeye Lake Moose 2434 funds: left to right is the share of its income from government, bottom to top the share from Buckeye Lake Moose 2434. 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%1%3%4%5%share of the org’s income from government →
    no gov moneyreceives it· size = income
    0get no government money at all
    1report government grants on their 990 we could not trace to a source (not plotted)
    0rely on government for over half their income
    ⤢ axis zoomed · 0–5%
    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.
    05Through Plinth

    Warm introductions · Powered by PlinthPlus

    How do I get to Buckeye Lake Moose 2434?

    Find your warmest path to Buckeye Lake Moose 2434 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 8 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 2026, released 2026. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

    Source object · view filing

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