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In this article, we explore how independently reported measures of subjects' cognitive capabilities, preferences, and sociodemographic characteristics relate to their behavior in a real-effort moral dilemma experiment. To do this, we use a unique dataset, the Chapman Preferences and Characteristics

In this article, we explore how independently reported measures of subjects' cognitive capabilities, preferences, and sociodemographic characteristics relate to their behavior in a real-effort moral dilemma experiment. To do this, we use a unique dataset, the Chapman Preferences and Characteristics Instrument Set (CPCIS), which contains over 30 standardized measures of preferences and characteristics. We find that simple correlation analysis provides an incomplete picture of how individual measures relate to behavior. In contrast, clustering subjects into groups based on observed behavior in the real-effort task reveals important systematic differences in individual characteristics across groups. However, while we find more differences, these differences are not systematic and difficult to interpret. These results indicate a need for more comprehensive theory explaining how combinations of different individual characteristics impact behavior is needed.

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    Title
    • Angels and Demons: Using Behavioral Types in a Real-Effort Moral Dilemma to Identify Expert Traits
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    Date Created
    2016-10-25
    Resource Type
  • Text
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    Identifier
    • Digital object identifier: 10.3389/fpsyg.2016.01464
    • Identifier Type
      International standard serial number
      Identifier Value
      1664-1078
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    • View the article as published at http://journal.frontiersin.org/article/10.3389/fpsyg.2016.01464/full

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    This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.

    Bejarano, H. D., Green, E. P., & Rassenti, S. J. (2016). Angels and Demons: Using Behavioral Types in a Real-Effort Moral Dilemma to Identify Expert Traits. Frontiers in Psychology, 7. doi:10.3389/fpsyg.2016.01464

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