LBTAS assumes transparency as default. Every rating is visible. Averages propagate through the network. Communities can analyze their own transaction patterns without platform intermediation. This shifts power from platform operators to participants—exactly what cooperative structures require.

LBTAS has been implemented in four languages: Python (original) TypeScript/Node.js Go Rust Each implementation maintains the same core functionality and AGPL-3.0 license.

LBTAS is designed as a foundational rating calculation engine that requires integration with external systems for persistence, user interfaces, and advanced analytics. The core module provides rating collection, validation, and aggregation logic while deliberately remaining agnostic about implementation context to maximize reusability across diverse research platforms.