The Bayesian Situational Construal Model (BSCM): A Cognitive Operating System for Adaptive Human Behaviour

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The Bayesian Situational Construal Model (BSCM) formalizes human behavior as dynamic Bayesian inference, where personality traits and situational cues interact to generate subjective beliefs that guide adaptive action across various domains.

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Abstract

This paper introduces the Bayesian Situational Construal Model (BSCM), a unifying psychological framework that models human behaviour as a process of dynamic Bayesian inference. Building on Funder’s Situational Construal Model, the BSCM incorporates principles from Bayesian brain theory and the Free Energy Principle (FEP) to formalise how personality traits (priors) and situational cues (likelihoods) interact to generate subjective construals (posterior beliefs), which in turn guide behaviour. This recursive cycle of interpretation and updating allows individuals to navigate uncertainty and maintain psychological coherence. Originally developed to explain healthcare non-attendance, the BSCM generalises to a wide range of behavioural domains. The model functions as a cognitive operating system, offering a theoretically integrative, neurocognitively grounded, and computationally tractable scaffold for understanding context-sensitive human action.

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License: CC-BY-4.0