Context Collapse: A Canonical Environmental Condition within the IDM Spiral Model
Abstract
In high-efficiency automated infrastructures, human meaning is not merely lost or degraded; it is systematically re-encoded. Context Collapse, in this setting, is not a transient interpretive error but a persistent environmental constraint. This working paper offers a canonical formulation of Context Collapse as a structural field that forcibly compresses multidimensional human context into machine-legible signals. By mapping the dimensions of this collapse and identifying canonical compression regimes, the paper specifies the conditions under which Human Drift becomes necessary for meaning-bearing intent to remain operative. The framework extends the IDM Spiral Model and the canonical account of Human Drift by moving beyond sociological “audience collision” toward a structural analysis of semantic erasure and re-encoding in automated systems. Version 1.1 – Minor metadata correction, internal reference alignment, and inclusion of cryptographic signature (.sig). Cryptographic signature verification:The author's public key is available at:https://aporya.com/keys/
Fields of Study & Subjects
Ethics and Social Impacts of AI
Information Systems Theories and Implementation
Cybernetics and Technology in Society
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 16 February 2026
- Language
- EN