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The More the Better? Effects of Training and Information Amount in Legal Judgments

Author

Listed:
  • Stephan Dickert

    (Max Planck Institute for Research on Collective Goods, Bonn)

  • Britta Herbig

    (Institute for Occupational, Social and Environmental Medicine, Ludwig-Maximilians-University, Munich, Germany)

  • Andreas Glöckner

    (Max Planck Institute for Research on Collective Goods, Bonn)

  • Christina Gansen

    (University of Bonn)

  • Roman Portack

    (University of Bonn)

Abstract

In an experimental study we investigated effects of information amount and legal training on the judgment accuracy in legal cases. In a two (legal training: yes vs. no) x two (information amount: high vs. low) between-subjects design, 90 participants judged the premeditation of a perpetrator in eight real-world cases decided by the German Federal Court of Justice. Judgment accuracy was assessed in comparison with the Court’s ruling. Legal training increased judgment accuracy, but did not depend on the amount of information given. Furthermore, legal training corresponded with higher confidence. Interestingly, emotional reactions to the legal cases were stronger when more information was given for individuals without legal training but decreased for individuals with training. This interaction seems to be caused by fundamental differences in the way people construct their mental representations of the cases. We advance an information processing perspective to explain the observed differences in legal judgments and conclude with a discussion on the merits and problems of offering more information to lay people participating in legal decision making.

Suggested Citation

  • Stephan Dickert & Britta Herbig & Andreas Glöckner & Christina Gansen & Roman Portack, 2010. "The More the Better? Effects of Training and Information Amount in Legal Judgments," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2010_34, Max Planck Institute for Research on Collective Goods.
    • Handle: RePEc:mpg:wpaper:2010_34
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    References listed on IDEAS

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    1. William W. Gould & Jeffrey Pitblado & Brian Poi, 2010. "Maximum Likelihood Estimation with Stata," Stata Press books, StataCorp LP, edition 4, number ml4, March.
    2. Andreas Glöckner & Tilmann Betsch, 2008. "Modeling Option and Strategy Choices with Connectionist Networks: Towards an Integrative Model of Automatic and Deliberate Decision Making," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2008_02, Max Planck Institute for Research on Collective Goods.
    3. repec:cup:judgdm:v:3:y:2008:i::p:215-228 is not listed on IDEAS
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