Grants paid by The Foundation for Community Betterment
EIN 31-1724638 · Springfield, VA · Form 990, Schedule I · NTEE S30
The Foundation for Community Betterment of Springfield, VA (EIN 31-1724638) reported 7 grants paid totaling $118,022 to 4 recipients in tax years 2020–2024, on Form 990, Schedule I. Derived from IRS e-file data, dataset version 2026.09.0, built 2026-09-03.
Grants paid
$118,022
7 grants
Recipients
4
distinct organizations
Tax years
2020–2024
5 filings in the corpus
By tax year
| Tax year | Grants paid | Amount paid | Approved for future |
|---|---|---|---|
| 2020 | 1 | $47,840 | — |
| 2021 | 1 | $0 | — |
| 2022 | 1 | $0 | — |
| 2023 | 2 | $52,000 | — |
| 2024 | 2 | $18,182 | — |
Top recipients
The 4 recipients receiving the most from The Foundation for Community Betterment, by grants paid, out of 4 distinct recipients.
| Recipient | Match | Location | Grants | Total paid | Latest year |
|---|---|---|---|---|---|
| Medstar Georgetown University Hosp | U | Washington, DC | 2 | $56,932 | 2024 |
| Georgetown University Hospital 53-0196603 | D | Washington, DC | 3 | $47,840 | 2022 |
| Alexandria Bay Volunteer Fire Dept | U | Alexandria Bay, NY | 1 | $8,000 | 2023 |
| Alexandria Bay Village | U | Alexandria Bay, NY | 1 | $5,250 | 2024 |
Match tier: A Reported EIN · B Exact name and place · C Strong name match · D Probable name match · U Unresolved. Tiers C and D are inferred, not reported; see how matching works.
Every grant
All 7 grant rows this organization reported, most recent first.
| Tax year | Recipient | Match | Amount | Type | Purpose | Source filing |
|---|---|---|---|---|---|---|
| 2024 | Medstar Georgetown University Hosp Washington, DC | U | $12,932 | paid | Contribution towards Oncology treatments | 202533199349303773 |
| 2024 | Alexandria Bay Village Alexandria Bay, NY | U | $5,250 | paid | New Park Equipment and signage | 202533199349303773 |
| 2023 | Medstar Georgetown University Hosp Washington, DC | U | $44,000 | paid | Contribution towards Pediatric Oncology | 202422899349302312 |
| 2023 | Alexandria Bay Volunteer Fire Dept Alexandria Bay, NY | U | $8,000 | paid | New learning space contribution | 202422899349302312 |
| 2022 | Georgetown University Hospital Washington, DC | D | $0 | paid | Community Assistance | 202331359349320358 |
| 2021 | Georgetown University Hospital Washington, DC | D | $0 | paid | Community Assistance | 202232049349300203 |
| 2020 | Georgetown University Hospital Washington, DC | D | $47,840 | paid | Community Assistance | 202121619349300632 |
Match tier: A Reported EIN · B Exact name and place · C Strong name match · D Probable name match · U Unresolved. Tiers C and D are inferred, not reported; see how matching works.
Recipient matching for this dataset version has not yet completed its independent precision check. Tier A rows carry the EIN the filer reported; tiers B–D are the matcher's inference and should be read as leads until the check is published on the methodology page.
Source filings
Every figure above is traceable to one of these IRS e-file returns by its OBJECT_ID.
| Form | Tax year | Period end | Filed | Schema | IRS OBJECT_ID |
|---|---|---|---|---|---|
| 990 | 2024 | 2024-12-31 | not stated | 2024v5.2 | 202533199349303773 |
| 990 | 2023 | 2023-12-31 | not stated | 2023v5.1 | 202422899349302312 |
| 990 | 2022 | 2022-12-31 | not stated | 2022v5.0 | 202331359349320358 |
| 990 | 2021 | 2021-12-31 | not stated | 2021v4.2 | 202232049349300203 |
| 990 | 2020 | 2020-12-31 | not stated | 2020v4.1 | 202121619349300632 |
Derived from IRS Form 990 e-file XML; recipient identities from the IRS Exempt Organizations Business Master File. Dataset version 2026.09.0, built 2026-09-03. The same rows as Parquet: manifest; as JSON: /api/funders/311724638.json.
The same organization elsewhere in the program: exempt status and filing health · federal awards · grant guidance · open opportunities.
This is informational only, derived from public data on the dates shown. It is not an eligibility determination, and not legal, tax, or accounting advice. Verify against the official source before relying on it.