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Moral Judgments Depend on Information Presentation: Evidence for Recency and Transfer Effects
Laëtitia Leloup1, Gaëlle Meert1, Dana Samson1,2
1Psychological Sciences Research Institute, Université catholique de Louvain, Louvain-la-Neuve, BE.
The order of information significantly impacts moral judgments, with people often favoring the last details they receive. This recency effect influences decisions, especially in complex situations like legal trials.
Area of Science:
- Cognitive Psychology
- Moral Psychology
- Social Cognition
Background:
- Moral judgments are fundamental to social interactions.
- These judgments typically involve assessing an agent's intention and the action's outcome.
- Understanding factors influencing moral decision-making is crucial for fields like law.
Purpose of the Study:
- To investigate how the presentation order of information affects moral judgments.
- To examine the influence of judgment type (wrongness vs. punishment) on information processing.
- To identify factors that bias moral decision-making in complex scenarios.
Main Methods:
- Experiment 1: Manipulated the presentation order of intention and outcome information.
- Experiment 2: Varied the order of wrongness and punishment judgments.
- Utilized participant responses to assess moral judgments and identify cognitive biases.
Main Results:
- A recency effect was observed, where participants gave more weight to the last presented information (intention or outcome).
- An asymmetrical transfer effect emerged: punishment judgments were influenced by presentation order, but wrongness judgments were not.
- This asymmetry was linked to the inherent ambiguity of punishment-related evaluations.
Conclusions:
- Information presentation order and judgment type order can significantly, yet irrelevantly, influence moral judgments.
- These effects are more pronounced in difficult judgments, mirroring real-world decision-making contexts like court trials.
- Findings highlight the susceptibility of moral reasoning to cognitive biases, even when such biases should be logically excluded.
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