Small-scale societies exhibit fundamental variation in the role of intentions in moral judgment

Intent and mitigating circumstances play a central role in moral and legal assessments in large-scale industrialized societies. Although these features of moral assessment are widely assumed to be universal, to date, they have only been studied in a narrow range of societies. We show that there is substantial cross-cultural variation among eight traditional small-scale societies (ranging from hunter-gatherer to pastoralist to horticulturalist) and two Western societies (one urban, one rural) in the extent to which intent and mitigating circumstances influence moral judgments. Although participants in all societies took such factors into account to some degree, they did so to very different extents, varying in both the types of considerations taken into account and the types of violations to which such considerations were applied. The particular patterns of assessment characteristic of large-scale industrialized societies may thus reflect relatively recently culturally evolved norms rather than inherent features of human moral judgment

Multidimensional Signals and Analytic Flexibility: Estimating Degrees of Freedom in Human-Speech Analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis that can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling but also from decisions regarding the quantification of the measured behavior. In this study, we gave the same speech-production data set to 46 teams of researchers and asked them to answer the same research question, resulting in substantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further found little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise, or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system, and calibrate their (un)certainty in their conclusions

Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions

Homo Æqualis: A Cross-Society Experimental Analysis of Three Bargaining Games ∗

Abstract. Data from three bargaining games—the Dictator Game, the Ultimatum Game, and the Third-Party Punishment Game—played in 15 societies are presented. The societies range from US undergraduates to Amazonian, Arctic, and African hunter-gatherers. Behaviour within the games varies markedly across societies. The paper investigates whether this behavioural diversity can be explained solely by variations in inequality aversion. Combining a single parameter utility function with the notion of subgame perfection generates a number of testable predictions. While most of these are supported, there are some telling divergences between theory and data: uncertainty and preferences relating to acts of vengeance may have influenced play in the Ultimatum and Third-Party Punishment Games; and a few subjects used the games as an opportunity to engage in costly signalling. 1