Collective efficacy proxies
Who reports, who reacts, who joins a neighborhood group. These behavioral traces are the observable face of the social cohesion Sampson found to predict neighborhood outcomes.
Sampson et al. (1997)A computational sociology platform
Neighborhood safety as a measurable, equitable social fact.
Gorebet gives Ethiopian communities, partner agencies, and researchers the spatial and social intelligence to understand — and act on — neighborhood safety.
What Gorebet measures — and what it doesn't
Geo-temporal incident patterns
Where and when incidents cluster — not who commits them. Our map reveals the time-space signatures that shape risk for everyone in a neighborhood.
Cohen & Felson (1979)Report deserts, not absence of crime
Where few reports arrive, we apply Bayesian adjustment — not silence-as-safety. Every score we publish comes with a coverage indicator.
Methods →Who uses Gorebet data
Governments
Incident intelligence for public agencies and woreda offices. Supplement formal complaint systems with neighborhood-level reporting data.
NGOs & Civil Society
Fairness audits and community data for civil-society programs. We publish what our data cannot see as clearly as what it can.
Researchers
Open methodology, request-based data access, and a reproducibility commitment. Behavioral trace data analyzed with social-science rigor.
Businesses & Operators
Situational awareness for the assets and locations you operate. Register your premises; receive incident routing relevant to your footprint.
What 'safer' means — precisely
Gorebet does not claim to reduce crime. It provides the information infrastructure for communities, institutions, and services to make evidence-grounded decisions. Every score, map, and count we publish comes with a methodology note.
Read our methods →