
This paper introduces the Meaning Equation (Meaning = Context × Coherence) and the Drift Equation (Drift = Optimization – Context) as a minimal framework for understanding how meaning emerges and erodes across language, culture, organizations, and AI. It formalizes the role of context dimensions (temporal, relational, spatial, symbolic) in sustaining meaning, and describes drift as the hollowing of meaning when optimization strips away context. The framework extends traditions in semiotics, information theory, and organizational sensemaking while engaging recent debates in AI about semantic drift, fidelity, and alignment. Applications include language models, cultural trends, and organizational fragility, offering a portable shorthand for diagnosing the dynamics of meaning and drift. Part of Reality Drift framework (2023-2026) by A. Jacobs.
optimization trap, organizational fragility, drift equation, AI alignment, meaning equation, context collapse, semantic compression, semantic fidelity, semantic drift, coherence, information theory
optimization trap, organizational fragility, drift equation, AI alignment, meaning equation, context collapse, semantic compression, semantic fidelity, semantic drift, coherence, information theory
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
