Over the last ten years, Oosterhof and Todorov's valence-dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgments of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov's methodology across 11 world regions, 41 countries, and 11,570 participants. When we used Oosterhof and Todorov's original analysis strategy, the valence-dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions we observed much less generalization. Collectively, these results suggest that, while the valence-dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods, correlate and rotate the dimension reduction solution.

A theory of political belief system dynamics should incorporate causal connections between elements of the belief system and the possibility that belief systems are influenced by exogenous factors. These necessary components can be satisfied by conceptualizing an individual’s belief system as a network of causally connected attitudes and identities which, via the interactions between the elements and the push of exogenous influences, produces the disparate phenomena in the belief systems literature. We implement this belief systems as networks theory in a dynamic Ising model and demonstrate that the theory can integrate at least six otherwise unrelated phenomenon in the political belief systems literature, including work on attitude consistency, cross-pressures, spillover effects, partisan cues, and ideological differences in attitude consensus. Our findings suggest that belief systems are not just one thing, but emerge from the interactions between the attitudes and identities in the belief system. All code is available: https://osf.io/aswy8/?view_only=99aff77909094bddabb5d382f6db2622 .

A growing body of literature is exploring the link between social support and international students’ psychological adjustment. So far, however, there has been no systematic assessment of the overall relationship, and no indication which types and sources of social support may be most strongly associated with psychological adjustment. Our meta-analysis of 257 effect sizes across 76 studies fills this gap and assesses (a) the magnitude of the overall association between social support and international students’ psychological adjustment, (b) how different types (subjective, objective, and mixed) and sources (host, conational, international, mixed, and unspecified) of social support moderate the relationship between social support and psychological adjustment, and (c) whether the relationship between social support and psychological adjustment holds across different operationalizations of psychological adjustment. We find a positive overall association ( r = .20, 95% confidence interval [CI] = [0.16, 0.23]) between social support and international students’ psychological adjustment. Types and sources of social support matter as well: Subjective social support relates more strongly to psychological adjustment than objective social support. The data revealed that only support from mixed sources (i.e., not distinguishing between internationals, host, or conationals) is associated with a stronger effect of social support than support from conationals or from fellow international students (compared with support from host sources). We find no differences in the relation between social support and positive or negative adjustment. We outline recommendations for future research based on the meta-analysis.

This study explores how researchers’ analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers’ expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team’s workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers’ results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.

Pseudo profound bullshit receptivity is the tendency to perceive meaning in important-sounding, nonsense statements. To understand how bullshit receptivity differs across domains, we developed a scale to measure scientific bullshit receptivity—the tendency to perceive truthfulness in nonsensical scientific statements. Across three studies (total N = 1,948), scientific bullshit receptivity was positively correlated with pseudo profound bullshit receptivity. Both types of bullshit receptivity were positively correlated with belief in science, conservative political beliefs, and faith in intuition. However, compared to pseudo profound bullshit receptivity, scientific bullshit receptivity was more strongly correlated with belief in science, and less strongly correlated with conservative political beliefs and faith in intuition. Finally, scientific literacy moderated the relationship the two types of bullshit receptivity; the correlation between the two types of receptivity was weaker for individuals scoring high in scientific literacy.