· Private foundation
Ladd & Katherine Hancher Library Foundation Inc
Its FY2025 filing reports that it accepted unsolicited grant applications.
What you funded, over time
Every grant placed by its stated purpose and the recipient’s mission, by year — across FY2017–2025.
Where the money goes
Your grants by size, and where they go.
By grant size · FY2018
- Under $10k14 grants · $96k
- $10k–50k23 grants · $361k
| Recipient | Amount |
|---|---|
| Stella Hill Memorial Library | $30,000 |
| Blanco County So Library District | $27,927 |
| Johnson City Library | $26,442 |
| City of Wolfforth Library | $24,438 |
| Mitchell County Public Library | $21,925 |
| Muenster Public Library | $20,000 |
| Jennie Trent Dew Library | $17,907 |
| Rio Grande City Public Library | $17,462 |
| Gilbreath Memorial Library | $15,120 |
| Nancy Carol Roberts Memorial Library | $14,500 |
| Bandera Public Library | $13,400 |
| Quitman Public Library | $13,000 |
| Lakehills Area Library | $12,700 |
| Onalaska Public Library | $12,020 |
| Kaufman County Library | $12,000 |
Do your dollars go where the need is?
Each grant placed by the hardship in its grantee’s ZIP, then read against the area’s typical level.
Dollar for dollar, your grants (FY17–25) land where the poverty rate runs at 15%, against an area that typically sits at 11%. 98% of your dollars go to grantees based in above-average-need neighborhoods. Most of your grants land in higher-need ZIPs.
Matched: human-services grants are those whose grantee’s IRS cause code is Human Services. Placed by people below the poverty linein the grantee’s ZIP, averaged from the tracts in that ZIP; grantee ZIP can differ from where services are delivered.
US grants placed by each grantee’s ZIP, which can differ from where services are actually delivered. Need from public data — U.S. Census/ACS, CDC PLACES, Eviction Lab, USDA — shown as context about the area, never attributed to your giving.
The map has a center of gravity: the average direction from the rest of the sector toward the organizations the foundation funds — the shape of its giving. Scoring every nonprofit along that direction surfaces the ones that look most like the portfolio. These are the closest matchesthat aren’t grantees — a resemblance in what they say they do, not a recommendation.
To own, operate and maintain a public library and all facilities necessary or appropriate thereto to service the needs of people in and around Menard, Texas.
The purpose of the organization is to provide library services to the residents of the harper community, thus facilitating the growth of knowledge in the community.
Provide library services including books, computerized library services, literacy/learning programs for all ages to the citizens of Rhome and surrounding areas of Wise County Texas.
To provide library services to the approximately 2,500 residents of eldorado in schleicher county, texas.
For reference, the grantee most central to the portfolio’s shape is Johnson City Library Inc and the most unlike its peers is Alpine Public Library Association Inc. Resemblance is measured on each organization’s own IRS 990 mission text; it reflects how work is described, not its quality or impact.
9 grantees tracked through their own filings, 2017–2025.
Each one resolved to its own IRS returns and tracked year by year — your grant beside their revenue from every source. Association, dated; never a causal claim.
Counted here: distinct organizations you funded across 2017–2025, not grant rows in a single year — so this will not match the grant count on the cover. 9 of the 66 grantees resolved in that span have returns of their own we could reconcile; the rest are funded organizations whose filings we could not track year by year.
Where your money sits — by cause, then by grantee
Each org by its size and your share of it — top-left is where you’re load-bearing
Go grantee by grantee — a decade per org, and how each moved after you funded them
A decade per grantee — revenue shaded, your grants as bars, all rows on one timeline.
The grantmakers whose grantees overlap with yours far more than size alone predicts. Each orbits closer the stronger the alignment; the arcs between them show where they also fund each other. Here it reads as a tightly interlocked camp — most of these funders back each other's grantees too.
Open a dossier: Tocker Foundation · Amazonsmile Foundation
Affinity is a Gamma-Poisson posterior co-funding rate, re-centered on the typical rate, so thin evidence shrinks toward no signal. A research starting point: overlap is association, not proof of shared intent.
Government reliance of your grantees
Every dot is one organization Ladd & Katherine Hancher Library Foundation Inc funds. Left–right is the share of its income from government; up–down is the share from you. Bigger dots raise more. Filter to federal or a single department — and drag the year to watch it move.
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 your grant caused the public funding. Coverage is precision-first — a floor, not 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 12–24 months.
Warm introductions · Powered by PlinthPlus
How do I get to Ladd & Katherine Hancher Library Foundation Inc?
Find your warmest path to Ladd & Katherine Hancher Library Foundation Inc 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.