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· Public charity

Downtown Sacramento Foundation

The mission of the DOWNTOWN SACRAMENTO FOUNDATION (dsf) is to foster civic pride and enhance the quality of life by generating additional sources of funds to support the improvement of the social, physical and cultural environment of downtown sacramento.

$11k
Granted FY2024still arriving
1
Grants FY2024still arriving
1
States reached
$11k
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, FY2018 to 2024.

Food & Nutrition$17kHousing & Shelter$16kPhilanthropy$10kHealth$7k
02FY2024 · 1 grant

Where the money goes

Grants by size, and the largest recipients.

$10,500
Median grant
1
States reached
$517k
Total assets
Largest grants
RecipientAmount
FOOD LITERACY CENTER$10,500
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:

Dollar for dollar, its grants (FY18–24) land where the poverty rate runs at 12%, against an area that typically sits at 11%. 100% of its dollars go to grantees based in above-average-need neighborhoods. Most of its grants land in higher-need ZIPs.

area typical 11%SACRAMENTO METRO CHAMBER FOUNDATION: $10k → 12%FOOD LITERACY CENTER: $7k → 12%TLCS INC: $7k → 12%SACRAMENTO SELF-HELP HOUSING: $16k → 12%FOOD LITERACY CENTER: $11k → 12%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
04the grantee network

4 grantees tracked through their own filings, 2017–2025.

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 2025, 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)
1
Early backer (in before they grew)
4/4
Grantees still filing
2/4
Grew since first funded

Where the money sits, by cause and then by grantee

FOOD LITERACY CENTER: $17,000 · Food & NutritionFOOD LITERACY CENTERSACRAMENTO SELF-HELP HOUSING INC: $15,731 · OtherSACRAMENTO SELF-HELP HOUSING INCSACRAMENTO METRO CHAMBER FOUNDATION: $10,000 · PhilanthropySACRAMENTO METRO CHAMBE…TLCS INC: $6,500 · HealthTLCS INC
Food & Nutrition$17,000Other$15,731Philanthropy$10,000Health$6,500

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 budgetFOOD LITERACY CENTER: $17,000 over 2y, 1.1% of budgetSACRAMENTO SELF-HELP HOUSING INC: $15,731 over 1y, 0.2% of budgetSACRAMENTO METRO CHAMBER FOUNDATION: $10,000 over 1y, 0.9% of budgetTLCS INC: $6,500 over 1y, 0.1% 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.

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.

Sutter Valley HospitalsCA13.5× affinity4 shared granteesties to 1 of 1Hover any node to trace its alignments.Compare side by side →

Open a dossier: Sutter Valley Hospitals · 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 Downtown Sacramento Foundation funds: left to right is the share of its income from government, bottom to top the share from Downtown Sacramento Foundation. Bigger dots raise more.

2023
’20’21’22’23’24’25
no gov · 00%0%1%3%5%funder's share of their income ↑0%5%10%15%20%share of the org’s income from government →
    no gov moneyreceives it· size = income
    0get no government money at all
    2report government grants on their 990 we could not trace to a source (not plotted)
    0rely on government for over half their income
    ⤢ axis zoomed · 0–20%
    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.
    04Through Plinth

    Warm introductions · Powered by PlinthPlus

    How do I get to Downtown Sacramento Foundation?

    Find your warmest path to Downtown Sacramento Foundation 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 4 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

    Play a game based on Downtown Sacramento’s filings →

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