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 Occupation Framework (TOF): A Unified Geometric Model for the Analysis of Human and Systematic Efficiency. Zenodo. https://doi.org/10.5281/zenodo.17058202
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