Why I know but don't believe

Individuals hold interdependent beliefs that affect whether or not they accept scientific findings Despite extensive efforts at public science education, polling over the past 30 years has consistently shown that about 40 to 45% of Americans believe that humans were supernaturally created in the past 10,000 years (1). A natural interpretation of this finding is that U.S. science education is failing to reach nearly half of the population, and that widespread belief in recent human origins reflects basic scientific illiteracy. However, the reality is more complex (2): Many of those who reject evolutionary theory are aware of the scientific consensus on the subject, and such rejection is not always associated with low scientific literacy. Similar results have been found for beliefs regarding anthropogenic climate change (3). On page 321 of this issue, Friedkin et al. (4) provide a key step toward understanding this phenomenon by introducing a simple family of models for social influence among individuals with multiple, interdependent beliefs.

[1]  O. Larsen,et al.  Diffusion and Belief in a Collective Delusion: The Seattle Windshield Pitting Epidemic , 1958 .

[2]  Noah E. Friedkin,et al.  Social influence and opinions , 1990 .

[3]  Carter T. Butts,et al.  A Bayesian Model of Panic in Belief , 1998, Comput. Math. Organ. Theory.

[4]  M. McPherson,et al.  Birds of a Feather: Homophily in Social Networks , 2001 .

[5]  F. Schweitzer,et al.  SOCIAL IMPACT MODELS OF OPINION DYNAMICS , 2001 .

[6]  P. Johnson-Laird,et al.  Conditionals: A Theory of Meaning, Pragmatics, and Inference , 2002 .

[7]  Bart Geurts,et al.  Reasoning with quantifiers , 2003, Cognition.

[8]  J. Kitts.  Egocentric bias or information management? Selective disclosure and the social roots of norm misperception , 2003 .

[9]  M. Macy,et al.  Complex Contagions and the Weakness of Long Ties1 , 2007, American Journal of Sociology.

[10]  C. Steglich,et al.  DYNAMIC NETWORKS AND BEHAVIOR: SEPARATING SELECTION FROM INFLUENCE: separating selection from influence , 2010 .

[11]  David E. Over,et al.  Bayesian reasoning with ifs and ands and ors , 2015, Front. Psychol..

[12]  D. Kahan.  Climate-Science Communication and the Measurement Problem , 2015 .

[13]  E. Johns,et al.  Neural regulation of the kidney function in rats with cisplatin induced renal failure , 2015, Front. Physiol..

[14]  Americans’ Attitudes About Science and Technology: The Social Context for Public Communication , 2016 .

[15]  Roberto Tempo,et al.  Network science on belief system dynamics under logic constraints , 2016, Science.