Abstract:
This paper introduces The Occupation Framework (TOF), a novel meta-theoretical model for the unified analysis of efficiency across all forms of occupation. Traditional performance metrics are domain-specific, creating a conceptual chasm between the analysis of human productivity, computational performance, and societal well-being. TOF bridges this gap by building upon General Occupation Theory (GOT), which models any occupation as the dynamic trajectory of an abstract agent within an 11-dimensional state space. By demonstrating that this state space is isomorphic to a computable geometric object—the 11-dimensional Yıldırım Polytope (Y11)—we provide a universal metric space for all occupational phenomena. The core postulate of TOF is that occupation is an efficiency-optimizing process, wherein an agent’s trajectory within Y11 aims to maximize output while minimizing resource expenditure. By mapping established efficiency metrics from fields such as computer science (e.g., throughput, latency), industrial-organizational psychology (e.g., worker productivity), and sociology (e.g., Human Development Index) onto this geometric landscape, TOF offers a common grammar for performance. We culminate this synthesis by proposing a new, substrate-independent scalar metric derived from the geometric properties of an agent’s trajectory: the Occupational Yield (OY) Coefficient. This coefficient allows, for the first time, a direct quantitative comparison of efficiency between human, non-human, and collective agents.
Yıldırım, E. (2025). THE MONOGRAPH of THE OCCUPATION FRAMEWORK. Zenodo. https://doi.org/10.5281/zenodo.17162176
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