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A signal一detection approach to modeling forgiveness decisions
Jolene H. Tan; Shenghua Luan; Konstantinos Katsilcopoulos
First AuthorJolene H. Tan
Correspondent Emailtan@mpib-berlin.mpg.de, jolene.tan.h@gmail.com (j.h. tan)
2017
Source PublicationEVOLUTION AND HUMAN BEHAVIOR
ISSN1090-5138
Subtypearticle
Volume38Issue:1Pages:27-38
QuartileQ1
Abstract

Whether to forgive is a key decision supporting cooperation. Like many other evolutionarily recurrent decisions, it is made under uncertainty and requires the trade-off of costs and benefits. This decision can be conceptualized as a signal detection or error management task: Forgiving is adaptive if a relationship with the "harmdoer" will be fitness enhancing and not adaptive if the relationship will be fitness reducing, and the decision should be biased toward lowering the likelihood of the more costly error, which depending on the context may be either erroneously not forgiving or forgiving. Building on such conceptualization, we developed two cognitive models and examined how well they described participants' forgiveness decisions in hypothetical scenarios and predicted their decisions in recalled real-life incidents. We found that the models performed similarly and generally well around 80% in describing and 70% in prediction. Moreover, this modeling approach allowed us to estimate the decision bias of each participant; we found that the biases were generally consistent with the prescriptions of signal detection theory and were directed at reducing the more costly error. In addition to testing mechanistic models of the forgiveness decision, our study also contributes to forgiveness research by applying a novel experimental method that studied both hypothetical and real-life decisions in tandem. These models and experimental methods could be used to study other evolutionarily recurrent problems, advancing understanding of how they are solved in the mind. 

KeywordCooperation Signal detection theory Forgiveness Fast-and-frugal trees Franklin s rule Error management theory
DOI10.1016/j.evolhumbehav.2016.06.004
Indexed BySSCI ; SSCI
Language中文
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/32016
Collection中国科学院心理研究所
AffiliationMax Planck Institute for Human Development, Center forAdaptive Behavior and Cognition, Lentzeallee 94, 14195, Berlin, Germany
Recommended Citation
GB/T 7714
Jolene H. Tan,Shenghua Luan,Konstantinos Katsilcopoulos. A signal一detection approach to modeling forgiveness decisions[J]. EVOLUTION AND HUMAN BEHAVIOR,2017,38(1):27-38.
APA Jolene H. Tan,Shenghua Luan,&Konstantinos Katsilcopoulos.(2017).A signal一detection approach to modeling forgiveness decisions.EVOLUTION AND HUMAN BEHAVIOR,38(1),27-38.
MLA Jolene H. Tan,et al."A signal一detection approach to modeling forgiveness decisions".EVOLUTION AND HUMAN BEHAVIOR 38.1(2017):27-38.
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