Something out of nothing: a Bayesian learning computational model for the social construction of value

Lynette A. Shaw

The Journal of Mathematical Sociology, 2020, vol. 44, issue 2, 65-89

Abstract: This article develops a formalism for the social construction of value. Using a model based on Bayesian agents, it demonstrates how “something” arises out of “nothing” via the emergence of durable value conventions and shows how the developed framework can be used to investigate socially constructed valuations under a variety of circumstances. The resulting analysis clarifies why assumptions that collectives will converge upon the “intrinsic” (i.e., non-socially originating) value of an object (e.g., market efficiency) may not hold for mixed social and non-social valuation regimes, explains the dependency of socially constructed valuations on early accidents, demonstrates the effects of confident actors on constructed values, and identifies the production of time-dependent ratcheting effects from the interaction of bubbles with value conventions.

Date: 2020
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DOI: 10.1080/0022250X.2019.1652173

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