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· Public charity

San Jose Taiko Group Inc

San jose taiko teaches, performs, and expands the taiko art form.

$15k
Granted FY2021
4
Grants FY2021
3
States reached
$4k
Largest
01What it funds
01FY2021 · 4 grants

Where the money goes

Grants by size, and the largest recipients.

$3,625
Median grant
3
States reached
$2.9M
Total assets
Largest grants
RecipientAmount
HOLLABACK$3,625
JAPANTOWN COMMUNITY CONGRESS OF SAN JOSE$3,625
ASIAN AMERICANS ADVANCING JUSTICE$3,625
YU AI KAI$3,625
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:

Its human-services grants (FY21–21, $7k) land where the poverty rate runs at 14%, against an area that typically sits at 11%. 50% of those dollars go to grantees based in above-average-need neighborhoods. Its grants spread fairly evenly across need levels.

area typical 11%YU AI KAI: $4k → 8%HOLLABACK: $4k → 20%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

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)
0
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

YU-AI KAI JAPANTOWN COMMUNITY SENIOR CENTER: $3,625 · Human ServicesYU-AI KAI JAPANTOWN COMMUNITY SENIOR CENTERRIGHT TO BE INC: $3,625 · Human ServicesRIGHT TO BE INCJAPANTOWN COMMUNITY CONGRESS OF SAN JOSE: $3,625 · Arts & CultureJAPANTOWN COMMUNITY CONGRESS…Asian Law Caucus: $3,625 · Crime & LegalAsian Law Caucus
Human Services$7,250Arts & Culture$3,625Crime & Legal$3,625

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

25%50%75%100%$100k$1.0M$10Mgrantee revenue →↑ funder's share of their budgetYU-AI KAI JAPANTOWN COMMUNITY SENIOR CENTER: $3,625 over 1y, 0.2% of budgetJAPANTOWN COMMUNITY CONGRESS OF SAN JOSE: $3,625 over 1y, 9.7% of budgetRIGHT TO BE INC: $3,625 over 1y, 0.1% of budgetAsian Law Caucus: $3,625 over 1y, 0.0% 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 set of overlaps that mostly run through this funder rather than between each other.

Fidelity Investments Charitable Gift FundMA6.6× affinity4 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 San Jose Taiko Group Inc funds: left to right is the share of its income from government, bottom to top the share from San Jose Taiko Group Inc. Bigger dots raise more.

2025
’20’21’22’23’24’25
no gov · 00%1%3%6%10%funder's share of their income ↑0%4%8%11%15%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 · 0–15%
    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 San Jose Taiko Group Inc?

    Find your warmest path to San Jose Taiko Group 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.

    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 2021, released 2021. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

    Possibly out of date. A more recent filing (FY2025) is on record and reports no grant expense, so the figures above are from FY2021, the most recent year this funder made grants.

    Source object · view filing

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