Why are there descriptive norms? Because we looked for them

In this work, we present a mathematical model for the emergence of descriptive norms, where the individual decision problem is formalized with the standard Bayesian belief revision machinery. Previous work on the emergence of descriptive norms has relied on heuristic modeling. In this paper we show that with a Bayesian model we can provide a more general picture of the emergence of norms, which helps to motivate the assumptions made in heuristic models. In our model, the priors formalize the belief that a certain behavior is a regularity. The evidence is provided by other group members’ behavior and the likelihood by their reliability. We implement the model in a series of computer simulations and examine the group-level outcomes. We claim that domain-general belief revision helps explain why we look for regularities in social life in the first place. We argue that it is the disposition to look for regularities and react to them that generates descriptive norms. In our search for rules, we create them.

[1]  John H. Miller,et al.  The standing ovation problem , 2004, Complex..

[2]  J. Tenenbaum,et al.  Bayesian Networks, Bayesian Learning and Cognitive Development , 2022 .

[3]  M. Tomasello,et al.  Twelve- and 18-month-olds copy actions in terms of goals. , 2005, Developmental science.

[4]  E. Turiel,et al.  The Development of Social Knowledge: Morality and Convention , 1983 .

[5]  T. Schelling.  Micromotives and Macrobehavior , 1978 .

[6]  David P. Myatt,et al.  Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning , 2009 .

[7]  J. Tenenbaum,et al.  Probabilistic models of cognition: exploring representations and inductive biases , 2010, Trends in Cognitive Sciences.

[8]  Nick Chater,et al.  The probabilistic mind , 2008 .

[9]  Sven Bernecker,et al.  Routledge Companion to Epistemology , 2011 .

[10]  J. Schupbach.  Comparing Probabilistic Measures of Explanatory Power , 2011, Philosophy of Science.

[11]  D. Osherson,et al.  Comparison of confirmation measures , 2007, Cognition.

[12]  N. Chater,et al.  The probabilistic mind: prospects for Bayesian cognitive science , 2008 .

[13]  I. Hacking.  An Introduction to Probability and Inductive Logic , 2001 .

[14]  Daniel N. Osherson,et al.  Comparison of confirmation measures q,qq , 2007 .

[15]  Michael Tomasello,et al.  The sources of normativity: young children's awareness of the normative structure of games. , 2008, Developmental psychology.

[16]  Stephan Hartmann,et al.  On the emergence of descriptive norms , 2011 .

[17]  B. Love,et al.  The myth of computational level theory and the vacuity of rational analysis , 2011, Behavioral and Brain Sciences.

[18]  C. Glymour,et al.  Causal maps and Bayes nets: A cognitive and computational account of theory-formation , 2002 .

[19]  Ian Hacking,et al.  An Introduction to Probability and Inductive Logic: Contents , 2001 .

[20]  David M. Sobel,et al.  A theory of causal learning in children: causal maps and Bayes nets. , 2004, Psychological review.