Assessing and dissociating virtues from the ‘bottom up’: A case study of generosity vs. fairness

The empirical study of virtue is plagued by imprecise definitions and assessment. Here we propose a three-stage, data-driven (‘bottom-up’) method to differentiate lay perceptions of virtues. Employing two virtues— generosity (as cooperation) and fairness (as impartiality)—as a case study, we present findings utilizing data from 9 experiments (total N =2,667). First, natural language processing of free-response data indicated that participants used different ‘topics’ (i.e. clusters of words) to describe behaviours representing generosity (topics: ‘charity’ and ‘kindness’) and fairness (‘equality’). Second, participants in a survey experiment rated behaviours expressing generosity and fairness differently across 6 out of 9 underlying features measured. Third, participants perceive that actors in vignette-based experiments engaging in behaviours expressing generosity versus fairness were motivated differently on 5 out of 6 motivations measured. Our findings support the distinction of the virtues of generosity (as cooperation) and fairness (as impartiality) and indicate the utility of our bottom-up method for assessing and distinguishing virtues.