This paper introduces an exploratory conceptual synthesis that maps Karl Friston's Free Energy Principle (FEP) and the Fehr–Schmidt inequity aversion utility function onto classical DeGroot consensus dynamics. We propose a phenomenological toy model—the Variational Epistemic Inequity-Aversion (VEIA) framework—wherein agents update internal states by minimizing a multi-criteria heuristic that balances parameterized generative model errors, network alignment pressures, and an epistemic analog of status equity. Rather than modeling a universally validated biological mechanism, this work functions strictly as a conceptual preprint and a hypothesis-generating framework. We map relative informational uncertainty as a scalar psychological loss parameter and adapt traditional material equity utility into an epistemic status asset context. The paper outlines the severe mathematical bounds required for local linear-quadratic solvability, includes a reproducible Python simulation routine for a 5-node test network matrix, and proposes a human-subject laboratory experimental methodology via oTree and Maximum Likelihood Estimation (MLE) to evaluate the framework's eventual descriptive utility in computational network sociology.