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Veteran & Disabled Veteran Transportation Support

01 Veteran & Disabled Veteran Transportation Support · 10 edit slice
7
orgs
10
activities
1
strategies
AZ
epicenter
the opening take
This slice touches 7 organizations and 10 activities — SEMPER FI & AMERICA'S FUND, Yavapai Regional Transit, Veterans Helping Veterans, DISABLED AMERICAN VETERANS and others. Activity concentrates in Arizona (86%) and California (14%). The field's most common shared approach is "Coordinated Data Sharing", run by 1 orgs.
SEMPER FI & AMERICA'S FUND and Yavapai Regional Transit hold roughly a third of all activity — know those first.
pull-quote · for funders
who to look at first

shortlist

Ranked by activity breadth, method diversity, and network reach across the slice. Attach a memo to this report and this list re-ranks around your intent.

where this slice is thin

gap signals

Concrete structural gaps — method mix, geographic concentration, coalition density, funder diversity. Evidence is cited from the slice's own numbers.

where the field lives · works

geography

Orange headquarters dots are sized by how many grantees are based in the state. Green circles mark real locations these orgs say they serve — from city-level populations in this slice's impact_map_populations data. Toggle layers at the bottom right.

regional breakdown · hq density
Arizona 86% · 6 orgs
California 14% · 1 orgs
gap signal →
Arizona accounts for 86% of field activity — the other 49 states combined hold less than half.
who's here

organizations in this field · 7

sort by
direct service advocacy research capacity building
where the money comes from

funders already active in this field

Funders named as a funding source on these orgs' own materials. The count is the number of orgs in this slice that cite them — higher means a funder with demonstrable commitment to the field.

Arizona Department of Veterans Services 1
Government
GEO Group 1
Corporate
GoDaddy 1
Corporate
Home Depot 1
Corporate
The Bob & Renee Parsons Foundation 1
Foundation
Timothy T. Day Foundation 1
Foundation
USDA 1
Government
how the field thinks

strategies in this slice

Theories of action extracted from the orgs in this slice. The count is how many orgs cite each one — a strategy run by many orgs in common is a through-line; one cited by a single org is still surfaced so the reader can gauge the full spread.

where strategy meets practice

strategies × activity types

How each shared strategy breaks down across the four activity types the orgs running it actually do.

direct service
advocacy
research
capacity building
Coordinated Data Sharing
1
who works with whom

named partnerships · coalitions · networks

Entities these orgs explicitly call out as partners, coalition members, or networks. Unlike the strategy-sharing graph below (which is inferred from shared approaches), these are relationships the orgs claim on their own sites.

VA Partner
shared by 2 orgs
AMVETS Partner
shared by 1 org
American Legion Post #14 Network
shared by 1 org
American Legion Riders of Arizona Partner
shared by 1 org
Arizona Attorney General Government
shared by 1 org
Arizona Department of Veterans Services Funder
shared by 1 org
Banner Alzheimer’s Institute Partner
shared by 1 org
Banner Health Partner
shared by 1 org
Banner Health Foundation Partner
shared by 1 org
Bob Parsons Partner
shared by 1 org
Bosom Buddies Partner
shared by 1 org
Boys State Partner
shared by 1 org
Camp Hope Thrift Store Partner
shared by 1 org
Cancer Association of Havasu Partner
shared by 1 org
Central Yavapai Metropolitan Planning Organization Partner
shared by 1 org
Community Athlete Team Partner
shared by 1 org
where the field connects

strategy-sharing network

Inferred from shared theories of action: each line connects an org to a strategy it runs. Organizations that share many strategies cluster through the same nodes — funders can spot the field's structural bridges.

scale of the field

rollup metrics

Aggregated scale claims from orgs in the slice. Treat as a floor, not a ceiling — many orgs don't publish these numbers, so totals underrepresent real reach. Extreme outliers (often unit-mismatches upstream) are filtered out.

2.6M
People served
from 3 orgs