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How representations of number and numeracy predict decision paradoxes: A fuzzy-trace theory approach
Authors:Valerie F. Reyna  Priscila G. Brust-Renck
Affiliation:Human Neuroscience Institute, Cornell University, Ithaca, NY, USA
Abstract:Higher numeracy has been associated with decision biases in some numerical judgment-and-decision problems. According to fuzzy-trace theory, understanding such paradoxes involves broadening the concept of numeracy to include processing the gist of numbers—their categorical and ordinal relations—in addition to objective (verbatim) knowledge about numbers. We assess multiple representations of gist, as well as numeracy, and use them to better understand and predict systematic paradoxes in judgment and decision-making. In two samples (Ns = 978 and 957), we assessed categorical (some vs. none) and ordinal gist representations of numbers (higher vs. lower, as in relative magnitude judgment, estimation, approximation, and simple ratio comparison), objective numeracy, and a nonverbal, nonnumeric measure of fluid intelligence in predicting: (a) decision preferences exhibiting the Allais paradox and (b) attractiveness ratings of bets with and without a small loss in which the loss bet is rated higher than the objectively superior no-loss bet. Categorical and ordinal gist tasks predicted unique variance in paradoxical decisions and judgments, beyond objective numeracy and intelligence. Whereas objective numeracy predicted choosing or rating according to literal numerical superiority, appreciating the categorical and ordinal gist of numbers was pivotal in predicting paradoxes. These results bring important paradoxes under the same explanatory umbrella, which assumes three types of representations of numbers—categorical gist, ordinal gist, and objective (verbatim)—that vary in their strength across individuals.
Keywords:Allais paradox  fuzzy-trace theory  gist  individual differences  loss bet  numeracy  numerical cognition  risky choice
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