· Public charity
Daughters of Isabella #959
Monies given to charitable organizations
Where the money goes
Grants by size, and the largest recipients.
How this is measured
By grant size · FY2017
- Under $10k2 grants · $15k
- $10k–50k2 grants · $45k
| Recipient | Amount |
|---|---|
| OUR LADY OF MT CARMEL SCHOOL | $35,040 |
| CITY OF HERRIN POLICE DEPARTMENT | $10,000 |
| ST JOHNS SCHOOL | $9,420 |
| WILLIAMSON COUNTY PROGRAM ON AGING | $5,733 |
Does the money reach high-need areas?
Each grant placed by the hardship in its grantee’s ZIP, against the area’s typical level.
Its human-services grants (FY17–17, $6k) land where the poverty rate runs at 13%, against an area that typically sits at 14%. 0% of those dollars go to grantees based in above-average-need neighborhoods. Its grants skew toward lower-need ZIPs.
How this is measured
How this is measured
1 grantees tracked through their own filings, 2017–2024.
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 2024, not grant rows in a single year, so this will not match the grant count on the cover. 1 of the 4 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.
Where the money sits, by cause and then by grantee
Each grantee by its size and the funder’s share of it; top left is load-bearing
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 Daughters of Isabella #959 funds: left to right is the share of its income from government, bottom to top the share from Daughters of Isabella #959. Bigger dots raise more.
How this is measured
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How do I get to Daughters of Isabella #959?
Find your warmest path to Daughters of Isabella #959 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.
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