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.

Four studies examined gender differences in self-construals and the role of social comparison in generating these differences. Consistent with previous research, Study 1 (N=461) showed that women define themselves as higher in relational interdependence than men, and men define themselves as higher in independence/agency than women. Study 2 (N=301) showed that within-gender social comparison decreases gender differences in self-construals relative to a control condition, whereas between-genders comparison increases gender differences on both relational interdependence and independence/agency. Studies 3 (N=169) and 4 (N=278) confirmed these findings and showed that changing self-construal changes gender differences in social dominance orientation. Across the 4 studies, strong evidence for the role of in-group stereotyping as mediator of the effect of gender on self-construal was observed on the relational dimension but not on the agentic dimension.

Psychological differences between women and men, far from being invariant as a biological explanation would suggest, fluctuate in magnitude across cultures. Moreover, contrary to the implications of some theoretical perspectives, gender differences in personality, values, and emotions are not smaller, but larger, in American and European cultures, in which greater progress has been made toward gender equality. This research on gender differences in self-construals involving 950 participants from 5 nations/cultures (France, Belgium, the Netherlands, the United States, and Malaysia) illustrates how variations in social comparison processes across cultures can explain why gender differences are stronger in Western cultures. Gender differences in the self are a product of self-stereotyping, which occurs when between-gender social comparisons are made. These social comparisons are more likely, and exert a greater impact, in Western nations. Both correlational and experimental evidence supports this explanation.

Concerns have been growing about the veracity of psychological research. Many findings in psychological science are based on studies with insufficient statistical power and nonrepresentative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Crowdsourced research, a type of large-scale collaboration in which one or more research projects are conducted across multiple lab sites, offers a pragmatic solution to these and other current methodological challenges. The Psychological Science Accelerator (PSA) is a distributed network of laboratories designed to enable and support crowdsourced research projects. These projects can focus on novel research questions, or attempt to replicate prior research, in large, diverse samples. The PSA’s mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science. Here, we describe the background, structure, principles, procedures, benefits, and challenges of the PSA. In contrast to other crowdsourced research networks, the PSA is ongoing (as opposed to time-limited), efficient (in terms of re-using structures and principles for different projects), decentralized, diverse (in terms of participants and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside of the network). The PSA and other approaches to crowdsourced psychological science will advance our understanding of mental processes and behaviors by enabling rigorous research and systematically examining its generalizability.