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· Public charity

Visions in Learning Inc

Organizations mission is to support Jewish education.

$687k
Granted FY2017
5
Grants FY2017
2
States reached
$484k
Largest
01What it funds
01FY2017 · 5 grants

Where the money goes

Grants by size, and the largest recipients.

By grant size · FY2017

  • Under $10k1 grant · $3k
  • $10k–50k1 grant · $43k
  • $50k–250k2 grants · $156k
  • $250k+1 grant · $484k
$53,015
Median grant
2
States reached
$203k
Total assets
Largest grants
RecipientAmount
SEPHARDIC TORAH AND RETURN CENTER INC$484,000
CONG SUPPORTERS OF TORAH$103,250
TORAH ANYTIME$53,015
CONG ADAS YEREIM OF KEW GARDENS INC$42,960
NER MORDECHAI$3,335
02The need
02

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 (FY17–17) land where the poverty rate runs at 12%, against an area that typically sits at 10%. 100% of its dollars go to grantees based in above-average-need neighborhoods. Most of its grants land in higher-need ZIPs.

area typical 10%CONG ADAS YEREIM OF KEW GARDENS INC: $43k → 13%CONG SUPPORTERS OF TORAH: $103k → 11%SEPHARDIC TORAH AND RETURN CENTER INC: $484k → 12%NER MORDECHAI: $3k → 13%TORAH ANYTIME: $53k → 13%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
03the grantee network

1 grantees tracked through their own filings, 2017–2023.

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 2023, not grant rows in a single year, so this will not match the grant count on the cover. 1 of the 5 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)
1
Early backer (in before they grew)
1/1
Grantees still filing
1/1
Grew since first funded

Where the money sits, by cause and then by grantee

SEPHARDIC TORAH AND RETURN CENTER INC: $484,000 · OtherSEPHARDIC TORAH AND RETURN CENTER INCCONGREGATION SUPPORTERS OF TORAH INC: $103,250 · OtherCONGREGATION SUPPORTERS OF TORAH INCCONGREGATION ADAS YEREIM OF KEW GARDENS INC: $42,960 · OtherCONGREGATION ADAS YEREIM OF KEW GARDENS INC+1 more: $3,335 · OtherTorahAnytimeCom Inc: $53,015 · Religion
Other$633,545Religion$53,015

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

25%50%75%100%grantee revenue →↑ funder's share of their budgetTorahAnytimeCom Inc: $53,015 over 1y, 7.9% 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 TorahAnytimeCom Inc ↗

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.

Fidelity Investments Charitable Gift FundMA6.1× affinity5 shared granteesties to 0 of 0Hover any node to trace its alignments.Compare side by side →

Open a dossier: Fidelity Investments Charitable Gift Fund

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 Visions in Learning Inc funds: left to right is the share of its income from government, bottom to top the share from Visions in Learning Inc. Bigger dots raise more.

2023
’20’21’22’23
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
    0rely on government for over half their income
    ⤢ axis zoomed · 0–5%
    typical government reliance, FY20–23
    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.

    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 5 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 2017, released 2017. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

    Possibly out of date. A more recent filing (FY2024) is on record but names no grant recipient (grants abroad are filed by region only, and grants under $5,000 are not itemized), so the figures above are from FY2017, the most recent year this funder named its grantees.

    Source object · view filing

    Play a game based on Visions in Learning’s filings →

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