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Intentional harms are perceived as more painful and more deserving of compensation than unintentional harms. In conjunction with research demonstrating that people are poor judges of intent, this observation may explain why people are more willing to help victims whose suffering appears to be caused by others. This account further explains the authors' finding that people high in cognitive empathy are especially sensitive to other‐caused harm, and aligns well with existing attributional accounts of why perceived victim responsibility reduces helping behavior. Finally, this account suggests a number of novel predictions about the determinants of donor behavior.

Conceptual representations of warmth have been shown to be related to people's perceptions of ambient temperature. Based on this premise, we hypothesized that merely thinking about personality traits related to communion (but not agency) influences physical experience of warmth. Specifically, the three studies revealed that (a) perceptions of temperature are influenced by both positive and negative attributes within the communion but not agency dimension, (b) the effect is stronger when traits indicate sociability rather than morality subdimension of communion, and (c) communion activation affects temperature perceptions independently of target's or self-perceptions.

The online labor market Amazon Mechanical Turk (MTurk) is an increasingly popular source of respondents for social science research. A growing body of research has examined the demographic composition of MTurk workers as compared with that of other populations. While these comparisons have revealed the ways in which MTurk workers are and are not representative of the general population, variations among samples drawn from MTurk have received less attention. This article focuses on whether MTurk sample composition varies as a function of time. Specifically, we examine whether demographic characteristics vary by (a) time of day, (b) day of week, and serial position (i.e., earlier or later in data collection), both (c) across the entire data collection and (d) within specific batches. We find that day of week differences are minimal, but that time of day and serial position are associated with small but important variations in demographic composition. This demonstrates that MTurk samples cannot be presumed identical across different studies, potentially affecting reliability, validity, and efforts to reproduce findings.

Background: Bayesian statistics have become popular in the social sciences, in part because they are thought to present more useful information than traditional frequentist statistics. Unfortunately, little is known about whether or how interpretations of frequentist and Bayesian results differ. Objectives: We test whether presenting Bayesian or frequentist results based on the same underlying data influences the decisions people made. Research design: Participants were randomly assigned to read Bayesian and frequentist interpretations of hypothetical evaluations of new education technologies of various degrees of uncertainty, ranging from posterior probabilities of 99.8% to 52.9%, which have equivalent frequentist p values of .001 and .65, respectively. Subjects: Across three studies, 933 U.S. adults were recruited from Amazon Mechanical Turk. Measures: The primary outcome was the proportion of participants who recommended adopting the new technology. We also measured respondents' certainty in their choice and (in Study 3) how easy it was to understand the results. Results: When presented with Bayesian results, participants were more likely to recommend switching to the new technology. This finding held across all degrees of uncertainty, but especially when the frequentist results reported a p value >.05. Those who recommended change based on Bayesian results were more certain about their choice. All respondents reported that the Bayesian display was easier to understand. Conclusions: Presenting the same data in either frequentist or Bayesian terms can influence the decisions that people make. This finding highlights the importance of understanding the impact of the statistical results on how audiences interpret evaluation results.

Although replication is a central tenet of science, direct replications are rare in psychology. This research tested variation in the replicability of 13 classic and contemporary effects across 36 independent samples totaling 6,344 participants. In the aggregate, 10 effects replicated consistently. One effect – imagined contact reducing prejudice – showed weak support for replicability. And two effects – flag priming influencing conservatism and currency priming influencing system justification – did not replicate. We compared whether the conditions such as lab versus online or US versus international sample predicted effect magnitudes. By and large they did not. The results of this small sample of effects suggest that replicability is more dependent on the effect itself than on the sample and setting used to investigate the effect.

While direct replications such as the "Many Labs" project are extremely valuable in testing the reliability of published findings across laboratories, they reflect the common reliance in psychology on single vignettes or stimuli, which limits the scope of the conclusions that can be reached. New experimental tools and statistical techniques make it easier to routinely sample stimuli, and to appropriately treat them as random factors. We encourage researchers to get into the habit of including multiple versions of the content (e.g., stimuli or vignettes) in their designs, to increase confidence in cross-stimulus generalization and to yield more realistic estimates of effect size. We call on editors to be aware of the challenges inherent in such stimulus sampling, to expect and tolerate unexplained variability in observed effect size between stimuli, and to encourage stimulus sampling instead of the deceptively cleaner picture offered by the current reliance on single stimuli.

We conducted preregistered replications of 28 classic and contemporary published findings, with protocols that were peer reviewed in advance, to examine variation in effect magnitudes across samples and settings. Each protocol was administered to approximately half of 125 samples that comprised 15,305 participants from 36 countries and territories. Using the conventional criterion of statistical significance (p <.05), we found that 15 (54%) of the replications provided evidence of a statistically significant effect in the same direction as the original finding. With a strict significance criterion (p <.0001), 14 (50%) of the replications still provided such evidence, a reflection of the extremely high-powered design. Seven (25%) of the replications yielded effect sizes larger than the original ones, and 21 (75%) yielded effect sizes smaller than the original ones. The median comparable Cohen?s ds were 0.60 for the original findings and 0.15 for the replications. The effect sizes were small (<0.20) in 16 of the replications (57%), and 9 effects (32%) were in the direction opposite the direction of the original effect. Across settings, the Q statistic indicated significant heterogeneity in 11 (39%) of the replication effects, and most of those were among the findings with the largest overall effect sizes; only 1 effect that was near zero in the aggregate showed significant heterogeneity according to this measure. Only 1 effect had a tau value greater than .20, an indication of moderate heterogeneity. Eight others had tau values near or slightly above .10, an indication of slight heterogeneity. Moderation tests indicated that very little heterogeneity was attributable to the order in which the tasks were performed or whether the tasks were administered in lab versus online. Exploratory comparisons revealed little heterogeneity between Western, educated, industrialized, rich, and democratic (WEIRD) cultures and less WEIRD cultures (i.e., cultures with relatively high and low WEIRDness scores, respectively). ...

We conducted preregistered replications of 28 classic and contemporary published findings, with protocols that were peer reviewed in advance, to examine variation in effect magnitudes across samples and settings. Each protocol was administered to approximately half of 125 samples that comprised 15,305 participants from 36 countries and territories. Using the conventional criterion of statistical significance (p < .05), we found that 15 (54%) of the replications provided evidence of a statistically significant effect in the same direction as the original finding. With a strict significance criterion (p < .0001), 14 (50%) of the replications still provided such evidence, a reflection of the extremely high-powered design. Seven (25%) of the replications yielded effect sizes larger than the original ones, and 21 (75%) yielded effect sizes smaller than the original ones. The median comparable Cohen's ds were 0.60 for the original findings and 0.15 for the replications. The effect sizes were small (< 0.20) in 16 of the replications (57%), and 9 effects (32%) were in the direction opposite the direction of the original effect. Across settings, the Q statistic indicated significant heterogeneity in 11 (39%) of the replication effects, and most of those were among the findings with the largest overall effect sizes; only 1 effect that was near zero in the aggregate showed significant heterogeneity according to this measure. Only 1 effect had a tau value greater than .20, an indication of moderate heterogeneity. Eight others had tau values near or slightly above .10, an indication of slight heterogeneity. Moderation tests indicated that very little heterogeneity was attributable to the order in which the tasks were performed or whether the tasks were administered in lab versus online. Exploratory comparisons revealed little heterogeneity between Western, educated, industrialized, rich, and democratic (WEIRD) cultures and less WEIRD cultures (i.e., cultures with relatively high and low WEIRDness scores, respectively). Cumulatively, variability in the observed effect sizes was attributable more to the effect being studied than to the sample or setting in which it was studied.