Going Public in Support of Science.

Scientists are stepping up like never before to support science in the public arena. In big and small ways, scientists are adopting creative ideas to promote science.

Like-minded sources on Facebook are prevalent but not polarizing.

Many critics raise concerns about the prevalence of 'echo chambers' on social media and their potential role in increasing political polarization. However, the lack of available data and the challenges of conducting large-scale field experiments have made it difficult to assess the scope of the problem1,2. Here we present data from 2020 for the entire population of active adult Facebook users in the USA showing that content from 'like-minded' sources constitutes the majority of what people see on the platform, although political information and news represent only a small fraction of these exposures. To evaluate a potential response to concerns about the effects of echo chambers, we conducted a multi-wave field experiment on Facebook among 23,377 users for whom we reduced exposure to content from like-minded sources during the 2020 US presidential election by about one-third. We found that the intervention increased their exposure to content from cross-cutting sources and decreased exposure to uncivil language, but had no measurable effects on eight preregistered attitudinal measures such as affective polarization, ideological extremity, candidate evaluations and belief in false claims. These precisely estimated results suggest that although exposure to content from like-minded sources on social media is common, reducing its prevalence during the 2020 US presidential election did not correspondingly reduce polarization in beliefs or attitudes.

Europeans' support for refugees of varying background is stable over time.

Protracted global conflicts during the past decade have led to repeated major humanitarian protection crises in Europe. During the height of the Syrian refugee crisis at the end of 2015, Europe hosted around 2.3 million people requesting asylum1. Today, the ongoing war in Ukraine has resulted in one of the largest humanitarian emergencies in Europe since World War II, with more than eight million Ukrainians seeking refuge across Europe2. Here we explore whether repeated humanitarian crises threaten to exhaust solidarity and whether Europeans welcome Ukrainian asylum seekers over other asylum seekers3,4. We conducted repeat conjoint experiments during the 2015-2016 and 2022 refugee crises, asking 33,000 citizens in 15 European countries to evaluate randomly varied profiles of asylum seekers. We find that public preferences for asylum seekers with specific attributes have remained remarkably stable and general support has, if anything, increased slightly over time. Ukrainian asylum seekers were welcomed in 2022, with their demographic, religious and displacement profile having a larger role than their nationality. Yet, this welcome did not come at the expense of support for other marginalized refugee groups, such as Muslim refugees. These findings have implications for our theoretical understanding of the drivers and resilience of public attitudes towards refugees and for policymakers tasked to find effective responses to the enduring stress on the asylum system5-8.

High aboveground carbon stock of African tropical montane forests.

Tropical forests store 40-50 per cent of terrestrial vegetation carbon1. However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests2. Owing to climatic and soil changes with increasing elevation3, AGC stocks are lower in tropical montane forests compared with lowland forests2. Here we assemble and analyse a dataset of structurally intact old-growth forests (AfriMont) spanning 44 montane sites in 12 African countries. We find that montane sites in the AfriMont plot network have a mean AGC stock of 149.4 megagrams of carbon per hectare (95% confidence interval 137.1-164.2), which is comparable to lowland forests in the African Tropical Rainforest Observation Network4 and about 70 per cent and 32 per cent higher than averages from plot networks in montane2,5,6 and lowland7 forests in the Neotropics, respectively. Notably, our results are two-thirds higher than the Intergovernmental Panel on Climate Change default values for these forests in Africa8. We find that the low stem density and high abundance of large trees of African lowland forests4 is mirrored in the montane forests sampled. This carbon store is endangered: we estimate that 0.8 million hectares of old-growth African montane forest have been lost since 2000. We provide country-specific montane forest AGC stock estimates modelled from our plot network to help to guide forest conservation and reforestation interventions. Our findings highlight the need for conserving these biodiverse9,10 and carbon-rich ecosystems.

Uncommon and nonpartisan: Antidemocratic attitudes in the American public.

Democratic regimes flourish only when there is broad acceptance of an extensive set of norms and values. In the United States, fundamental democratic norms have recently come under threat from prominent Republican officials. We investigate whether this antidemocratic posture has spread from the elite level to rank-and-file partisans. Exploiting data from a massive repeated cross-sectional and panel survey ([Formula: see text] = 45,095 and 5,231 respectively), we find that overwhelming majorities of the public oppose violations of democratic norms, and virtually nobody supports partisan violence. This bipartisan consensus remains unchanged over time despite high levels of affective polarization and exposure to divisive elite rhetoric during the 2022 political campaign. Additionally, we find no evidence that elected officials' practice of election denialism encourages their constituents to express antidemocratic attitudes. Overall, these results suggest that the clear and present threat to American democracy comes from unilateral actions by political elites that stand in contrast to the views of their constituents. In closing, we consider the implications of the stark disconnect between the behavior of Republican elites and the attitudes of Republican voters.

White Americans' preference for Black people in advertising has increased in the past 66 y: A meta-analysis.

This study investigates Black and White consumers' preferences for Black versus White people in United States advertising contexts over 66 y, from 1956 until 2022, a time in which the United States has experienced significant ethno-racial diversification. Examining Black and White consumers' reactions to visual advertising over more than half a century offers a unique and dynamic view of interracial preferences. Mass advertising reaches an audience of billions and can shape people's attitudes and behavior, emphasizing the relevance of clarifying the influence of race in advertising, how it has evolved over time, and how it may contribute to mitigating discrimination based on racial perceptions. A meta-analysis of extant experiments into the relationship between the depicted endorser's race (i.e., the model in a visual ad) and the reaction of Black and White viewers pertains to 332 effect sizes from 62 studies reported in 52 scientific papers, comprising 10,186 Black and White participants. Our results are anchored in a conceptual framework, including a comprehensive set of perceiver (viewer), target (endorser), social/societal context, and publication characteristics. Without accounting for temporal dynamics, the results indicate ingroup favoritism, such that White viewers prefer White models and Black viewers prefer Black models. But by controlling for the publication year, it is possible to observe a time-dependent trend: Historically, White consumers preferred endorsers of the same race, but this preference has significantly shifted toward Black endorsers in recent years. In contrast, the level of Black consumers' reactions to endorsers of the same race remains largely unchanged over time.

The effects of Facebook and Instagram on the 2020 election: A deactivation experiment.

We study the effect of Facebook and Instagram access on political beliefs, attitudes, and behavior by randomizing a subset of 19,857 Facebook users and 15,585 Instagram users to deactivate their accounts for 6 wk before the 2020 U.S. election. We report four key findings. First, both Facebook and Instagram deactivation reduced an index of political participation (driven mainly by reduced participation online). Second, Facebook deactivation had no significant effect on an index of knowledge, but secondary analyses suggest that it reduced knowledge of general news while possibly also decreasing belief in misinformation circulating online. Third, Facebook deactivation may have reduced self-reported net votes for Trump, though this effect does not meet our preregistered significance threshold. Finally, the effects of both Facebook and Instagram deactivation on affective and issue polarization, perceived legitimacy of the election, candidate favorability, and voter turnout were all precisely estimated and close to zero.

The politics of allyship: Multiethnic coalitions and mass attitudes toward protest.

Recent work finds that nonviolent resistance by ethnic minorities is perceived as more violent and requiring more policing than identical resistance by ethnic majorities, reducing its impact and effectiveness. We ask whether allies-advantaged group participants in disadvantaged group movements-can mitigate these barriers. On the one hand, allies can counter negative stereotypes and defuse threat perceptions among advantaged group members, while raising expectations of success and lowering expected risks among disadvantaged group members. On the other hand, allies can entail significant costs, carrying risks of cooptation, replication of power hierarchies, and marginalization of core constituencies. To shed light on this question we draw on the case of the Black Lives Matter (BLM) movement, which, in 2020, attracted unprecedented White participation. Employing a national survey experiment, we find that sizeable White presence at racial justice protests increases protest approval, reduces perceptions of violence, and raises the likelihood of participation among White audiences, while not causing significant backlash among Black audiences. Black respondents mostly see White presence as useful for advancing the movement's goals, and predominant White presence reduces expectations that protests will be forcefully repressed. We complement these results with analysis of tens of thousands of images shared on social media during the 2020 BLM protests, finding a significant association between the presence of Whites in the images and user engagement and amplification. The findings suggest that allyship can be a powerful tool for promoting sociopolitical change amid deep structural inequality.

Declining Chinese attitudes toward the United States amid COVID-19.

In this paper, we present findings from four separate studies using different data sources and methods to examine Chinese attitudes toward the United States amid the COVID-19 pandemic. The empirical results consistently indicate a marked and significant decline in Chinese attitudes toward the US between late 2019 and the end of 2022. Using a quasi-experimental design and granular survey data that exploit daily variations in public opinion, we offer additional evidence that the decline in Chinese attitudes toward the United States followed a distinct pattern not true for Chinese attitudes toward other countries. Specifically, the rise in Chinese unfavorability toward the United States closely corresponded to the heightened Chinese attention to the pandemic's progression in the United States. These results collectively suggest a causal effect of COVID-19, shedding light on how public health crises, international relations, and media jointly shape the increasing enmity between the two great powers.

People with more extreme attitudes towards science have self-confidence in their understanding of science, even if this is not justified.

People differ greatly in their attitudes towards well-evidenced science. What characterises this variation? Here, we consider this issue in the context of genetics and allied sciences. While most prior research has focused on the relationship between attitude to science and what people know about it, recent evidence suggests that individuals with strongly negative attitudes towards specific genetic technologies (genetic modification (GM) technology and vaccines) commonly do not objectively understand the science, but, importantly, believe that they do. Here, using data from a probability survey of United Kingdom adults, we extend this prior work in 2 regards. First, we ask whether people with more extreme attitudes, be they positive or negative, are more likely to believe that they understand the science. Second, as negativity to genetics is commonly framed around issues particular to specific technologies, we ask whether attitudinal trends are contingent on specification of technology. We find (1) that individuals with strongly positive or negative attitudes towards genetics more strongly believe that they well understand the science; but (2) only for those most positive to the science is this self-confidence warranted; and (3) these effects are not contingent on specification of any particular technologies. These results suggest a potentially general model to explain why people differ in their degree of acceptance or rejection of science, this being that the more someone believes they understand the science, the more confident they will be in their acceptance or rejection of it. While there are more technology nonspecific opponents who also oppose GM technology than expected by chance, most GM opponents fit a different demographic. For the most part, opposition to GM appears not to reflect a smokescreen concealing a broader underlying negativity.

Predicting implicit attitudes with natural language data.

Large-scale language datasets and advances in natural language processing offer opportunities for studying people's cognitions and behaviors. We show how representations derived from language can be combined with laboratory-based word norms to predict implicit attitudes for diverse concepts. Our approach achieves substantially higher correlations than existing methods. We also show that our approach is more predictive of implicit attitudes than are explicit attitudes, and that it captures variance in implicit attitudes that is largely unexplained by explicit attitudes. Overall, our results shed light on how implicit attitudes can be measured by combining standard psychological data with large-scale language data. In doing so, we pave the way for highly accurate computational modeling of what people think and feel about the world around them.

How contact can promote societal change amid conflict: An intergroup contact field experiment in Nigeria.

Intergroup contact, originally designed as a tool for prejudice reduction, offers a promising means to resolve intergroup conflict. Evidence for contact-based interventions to improve intergroup relations is sparse, however, with most studies focusing only on the individuals who directly engage in contact. We test the ability of a contact-based intervention to promote peace between conflicting groups with a field experiment in Nigeria, where farmer and pastoralist communities are embroiled in a deadly conflict over land use. We examine the effectiveness of the contact intervention on the wider population-not just those directly engaged in contact-using surveys, direct observation of behavior in markets and social events, and a behavioral game. We find those who lived in the communities that received the intervention had more positive intergroup attitudes and feelings of physical security, as well as were more likely to engage in voluntary intergroup contact measured through self-reports and observed behavior in markets. Exploratory analyses show that those who directly participated in the program and those who were exposed to it by living in the communities where activities were taking place changed similarly with regard to attitudes and perceptions of security, but not with regard to behaviors, indicating the spread to the wider community was likely due to norm change. These results suggest that contact interventions can have wider societal change and reduce the barriers to peace between conflicting groups.

Educating for inclusion: Diversity education programs can reduce prejudice toward outgroups in Israel.

Intergroup prejudice is pervasive in many contexts worldwide, leading to discrimination and conflict. Existing research suggests that prejudice is acquired at an early age and that durably improving intergroup relations is extremely challenging, often requiring intense interventions. Building on existing research in social psychology and inspired by the Israeli TV series "You Can't Ask That," which depicts charismatic children from minority groups broaching sensitive topics at the core of intergroup relations, we develop a month-long diversity education program. Our program exposed students to the TV series and facilitated follow-up classroom discussions in which students constructively addressed various sensitive topics at the core of intergroup relations and learned about intergroup similarities, intragroup heterogeneity, and the value of taking others' perspectives. Through two field experiments implemented in Israeli schools, we show that integrating our intervention into school curricula improved Jewish students' attitudes toward minorities and increased some pro-diversity behavior up to 13 wk posttreatment. We further provide suggestive evidence that the intervention was effective by encouraging students to take their outgroups' perspectives and address an element of scalability by delegating implementation responsibilities to classroom teachers in our second study. Our findings suggest that theoretically informed intensive education programs are a promising route to reducing prejudice at a young age.

Persistence of gender biases in Europe.

Prior work suggests that modern gender bias might have historical roots but has not been able to demonstrate long-term persistence of this bias due to a lack of historical data. We follow archaeological research and employ skeletal records of women's and men's health from 139 archaeological sites in Europe dating back, on average, to about 1200 AD to construct a site-level indicator of historical bias in favor of one gender over the other using dental linear enamel hypoplasias. This historical measure of gender bias significantly predicts contemporary gender attitudes, despite the monumental socioeconomic and political changes that have taken place since. We also show that this persistence is most likely due to the intergenerational transmission of gender norms, which can be disrupted by significant population replacement. Our results demonstrate the resilience of gender norms and highlight the importance of cultural legacies in sustaining and perpetuating gender (in)equality today.

Neural alignment during outgroup intervention predicts future change of affect towards outgroup.

While social psychology studies have shown that paradoxical thinking intervention has a moderating effect on negative attitudes toward members from rival social groups (i.e. outgroup), the neural underpinnings of the intervention have not been studied. Here, we investigate this by examining neural alignment across individuals at different phases during the intervention regarding Covid-19 vaccine-supporters' attitudes against vaccine-opposers. We raise two questions: Whether neural alignment varies during the intervention, and whether it predicts a change in outgroup attitudes measured via a survey 2 days after the intervention and compared to baseline. We test the neural alignment using magnetoencephalography-recorded neural oscillations and multiset canonical correlation analysis. We find a build-up of neural alignment which emerges at the final phase of the paradoxical thinking intervention in the precuneus-a hub of mentalizing; there was no such effect in the control conditions. In parallel, we find a behavioral build-up of dissent to the interventional stimuli. These neural and behavioral patterns predict a prosocial future change in affect and actions toward the outgroup. Together, these findings reveal a new operational pattern of mentalizing on the outgroup, which can change the way individuals may feel and behave toward members of that outgroup.

Impression management attenuates the effect of ability on trust in economic exchange.

Are competent actors still trusted when they promote themselves? The answer to this question could have far-reaching implications for understanding trust production in a variety of economic exchange settings in which ability and impression management play vital roles, from succeeding in one's job to excelling in the sales of goods and services. Much social science research assumes an unconditional positive impact of an actor's ability on the trust placed in that actor: in other words, competence breeds trust. In this report, however, we challenge this assumption. Across a series of experiments, we manipulated both the ability and the self-promotion of a trustee and measured the level of trust received. Employing both online laboratory studies (n = 5,606) and a field experiment (n = 101,520), we find that impression management tactics (i.e., self-promotion and intimidation) can substantially backfire, at least for those with high ability. An explanation for this effect is encapsuled in attribution theory, which argues that capable actors are held to higher standards in terms of how kind and honest they are expected to be. Consistent with our social attribution account, mediation analyses show that competence combined with self-promotion decreases the trustee's perceived benevolence and integrity and, in turn, the level of trust placed in that actor.

Talking with strangers is surprisingly informative.

A meaningful amount of people's knowledge comes from their conversations with others. The amount people expect to learn predicts their interest in having a conversation (pretests 1 and 2), suggesting that the presumed information value of conversations guides decisions of whom to talk with. The results of seven experiments, however, suggest that people may systematically underestimate the informational benefit of conversation, creating a barrier to talking with-and hence learning from-others in daily life. Participants who were asked to talk with another person expected to learn significantly less from the conversation than they actually reported learning afterward, regardless of whether they had conversation prompts and whether they had the goal to learn (experiments 1 and 2). Undervaluing conversation does not stem from having systematically poor opinions of how much others know (experiment 3) but is instead related to the inherent uncertainty involved in conversation itself. Consequently, people underestimate learning to a lesser extent when uncertainty is reduced, as in a nonsocial context (surfing the web, experiment 4); when talking to an acquainted conversation partner (experiment 5); and after knowing the content of the conversation (experiment 6). Underestimating learning in conversation is distinct from underestimating other positive qualities in conversation, such as enjoyment (experiment 7). Misunderstanding how much can be learned in conversation could keep people from learning from others in daily life.

How digital media drive affective polarization through partisan sorting.

Politics has in recent decades entered an era of intense polarization. Explanations have implicated digital media, with the so-called echo chamber remaining a dominant causal hypothesis despite growing challenge by empirical evidence. This paper suggests that this mounting evidence provides not only reason to reject the echo chamber hypothesis but also the foundation for an alternative causal mechanism. To propose such a mechanism, the paper draws on the literatures on affective polarization, digital media, and opinion dynamics. From the affective polarization literature, we follow the move from seeing polarization as diverging issue positions to rooted in sorting: an alignment of differences which is effectively dividing the electorate into two increasingly homogeneous megaparties. To explain the rise in sorting, the paper draws on opinion dynamics and digital media research to present a model which essentially turns the echo chamber on its head: it is not isolation from opposing views that drives polarization but precisely the fact that digital media bring us to interact outside our local bubble. When individuals interact locally, the outcome is a stable plural patchwork of cross-cutting conflicts. By encouraging nonlocal interaction, digital media drive an alignment of conflicts along partisan lines, thus effacing the counterbalancing effects of local heterogeneity. The result is polarization, even if individual interaction leads to convergence. The model thus suggests that digital media polarize through partisan sorting, creating a maelstrom in which more and more identities, beliefs, and cultural preferences become drawn into an all-encompassing societal division.

Deep models of superficial face judgments.

The diversity of human faces and the contexts in which they appear gives rise to an expansive stimulus space over which people infer psychological traits (e.g., trustworthiness or alertness) and other attributes (e.g., age or adiposity). Machine learning methods, in particular deep neural networks, provide expressive feature representations of face stimuli, but the correspondence between these representations and various human attribute inferences is difficult to determine because the former are high-dimensional vectors produced via black-box optimization algorithms. Here we combine deep generative image models with over 1 million judgments to model inferences of more than 30 attributes over a comprehensive latent face space. The predictive accuracy of our model approaches human interrater reliability, which simulations suggest would not have been possible with fewer faces, fewer judgments, or lower-dimensional feature representations. Our model can be used to predict and manipulate inferences with respect to arbitrary face photographs or to generate synthetic photorealistic face stimuli that evoke impressions tuned along the modeled attributes.

The contributions of positive outgroup and negative ingroup evaluation to implicit bias favoring outgroups.

People sometimes prefer groups to which they do not belong (outgroups) over their own groups (ingroups). Many long-standing theoretical perspectives assume that this outgroup favorability bias primarily reflects negative ingroup evaluations rather than positive outgroup evaluations. To examine the contributions of negative ingroup versus positive outgroup evaluations to outgroup bias, we examined participants' data (total n > 879,000) from Implicit Association Tests [A. G. Greenwald, D. E. McGhee, J. L. K. Schwartz, J. Pers. Soc. Psychol. 74, 1464-1480 (1998)] measuring intergroup attitudes across four social domains in exploratory and preregistered confirmatory analyses. Process modeling [F. R. Conrey, J. W. Sherman, B. Gawronski, K. Hugenberg, C. J. Groom, J. Pers. Soc. Psychol. 89, 469-487 (2005)] was applied to the responses of participants who demonstrated implicit outgroup bias to separately estimate the contributions of negative ingroup and positive outgroup evaluations. The outgroup biases of lower-status group members (i.e., Asian, Black, gay and lesbian, and older people) consistently reflected greater contributions of positive outgroup evaluations than negative ingroup evaluations. In contrast, the outgroup biases of higher-status group members (i.e., White, straight, and younger people) reflected a more varied pattern of evaluations. We replicated this pattern of results using explicitly measured intergroup evaluations. Taking these data together, the present research demonstrates a positive-negative asymmetry effect of outgroup bias, primarily among members of lower-status groups.