Reports an error in "Computational signatures of inequity aversion in children across seven societies" by Dorsa Amir, David Melnikoff, Felix Warneken, Peter R. Blake, John Corbit, Tara C. Callaghan, Oumar Barry, Aleah Bowie, Lauren Kleutsch, Karen L. Kramer, Elizabeth Ross, Hurnan Vongsachang, Richard Wrangham and Katherine McAuliffe (Journal of Experimental Psychology: General, Advanced Online Publication, May 08, 2023, np). In the original article, there were affiliation errors for the first and 14th authors. The affiliations for Dorsa Amir are Department of Psychology, University of California, Berkeley; and Department of Psychology, Boston College. The affiliation for Katherine McAuliffe is Department of Psychology, Boston College. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2023-69306-001). Inequity aversion is an important factor in fairness behavior. Previous work suggests that children show more cross-cultural variation in their willingness to reject allocations that would give them more rewards than their partner-advantageous inequity-as opposed to allocations that would give them less than their partner-disadvantageous inequity. However, as past work has relied solely on children's decisions to accept or reject these offers, the algorithms underlying this pattern of variation remain unclear. Here, we explore the computational signatures of inequity aversion by applying a computational model of decision-making to data from children (N = 807) who played the Inequity Game across seven societies. Specifically, we used drift-diffusion models to formally distinguish evaluative processing (i.e., the computation of the subjective value of accepting or rejecting inequity) from alternative factors such as decision speed and response strategies. Our results suggest that variation in the development of inequity aversion across societies is best accounted for by variation in the drift rate-the direction and strength of the evaluative preference. Our findings underscore the utility of looking beyond decision data to better understand behavioral diversity. (PsycInfo Database Record (c) 2023 APA, all rights reserved).