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Community Innovation & Co-Working Hubs

01 Community Innovation & Co-Working Hubs · 15 edit slice
6
orgs
15
activities
3
strategies
AZ
epicenter
the opening take
This slice touches 6 organizations and 15 activities — NORTHERN ARIZONA TECHNOLOGY &, Change Labs, Nogales Community Development Corp, YEE HAOLNII DOO and others. Activity concentrates in Arizona (100%). The field's most common shared approach is "DMCA Compliance Framework", run by 1 orgs.
NORTHERN ARIZONA TECHNOLOGY & and Change Labs 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 100% · 6 orgs
who's here

organizations in this field · 6

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 Commerce Authority 1
Government
Arizona Department of Housing 1
Government
Arizona Department of Transportation 1
Government
Arizona Office of Tourism 1
Government
Blue Cross Blue Shield of Arizona 1
Corporate
EDA 1
Government
EPA Environmental Justice program 1
Government
U.S. Department of Housing and Urban Development (HUD) 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
DMCA Compliance Framework
3
Investment Readiness Training
3
Virtual Accessibility Bridge
3
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.

Arizona Commerce Authority Partner
shared by 2 orgs
Colorado Plateau Foundation Partner
shared by 2 orgs
APS Partner
shared by 1 org
ASU Partner
shared by 1 org
Ahehee’ Shidine’e Homecare LLC Partner
shared by 1 org
Ambos Nogales Partner
shared by 1 org
Arizona Department of Housing Government
shared by 1 org
Arizona Department of Transportation Funder
shared by 1 org
Arizona Foundation Partner
shared by 1 org
Arizona House and Senate Government
shared by 1 org
Arizona Main Street Funder
shared by 1 org
Arizona Office of Tourism Funder
shared by 1 org
Arizona Small Business Development Center Partner
shared by 1 org
BCBS of Arizona Partner
shared by 1 org
BETTER BUSINESS BUREAU Pacific Southwest Region Partner
shared by 1 org
BHP Billiton 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.

900K
People served
from 3 orgs