Master of Arts (M.A.)
Researchers have recently suggested that humans possess dedicated cognitive systems for forgiveness, which evolved to repair valuable cooperative relationships with transgressors and stave off harmful revenge behaviors. These putative systems are computational in nature, utilizing information pertaining to the relationship value, exploitation risk, and genetic relatedness of a transgressor in determining whether or not to employ forgiveness. While a few studies have provided empirical support for this conjecture, surprisingly little empirical research has been conducted to determine if forgiveness systems actually have such a computational structure. The aim of this thesis was to fill this gap in the literature by testing hypotheses related to evolved systems for forgiveness. Using a sample of undergraduate participants, we tested hypotheses related to the computational structure of forgiveness, focusing on the role of internal regulatory variables (IRVs) including relationship value, exploitation risk, and genetic relatedness. Seven separate predictions were all empirically supported, providing verisimilitude to evolved accounts of forgiveness, and offering new insights into the form and function of forgiveness systems.
© The Author
McCauley, Thomas G., "Computational Structure of Evolved Forgiveness Systems." (2017). Dissertations, Theses, and Masters Projects. Paper 1516639578.
Available for download on Sunday, October 06, 2019