Worldwide divergence of values.

Social scientists have long debated the nature of cultural change in a modernizing and globalizing world. Some scholars predicted that national cultures would converge by adopting social values typical of Western democracies. Others predicted that cultural differences in values would persist or even increase over time.

Generalized morality culturally evolves as an adaptive heuristic in large social networks.

Why do people assume that a generous person should also be honest? Why do we even use words like "moral" and "immoral"? We explore these questions with a new model of how people perceive moral character. We propose that people vary in the extent to which they perceive moral character as "localized" (varying along many contextually embedded dimensions) versus "generalized" (varying along a single dimension from morally bad to morally good). This variation might be partly the product of cultural evolutionary adaptations to different kinds of social networks.

Exposure to automation explains religious declines.

The global decline of religiosity represents one of the most significant societal shifts in recent history. After millennia of near-universal religious identification, the world is experiencing a regionally uneven trend toward secularization. We propose an explanation of this decline, which claims that automation-the development of robots and artificial intelligence (AI)-can partly explain modern religious declines.

Algorithm-mediated social learning in online social networks.

Human social learning is increasingly occurring on online social platforms, such as Twitter, Facebook, and TikTok. On these platforms, algorithms exploit existing social-learning biases (i.e.

Exposure to robot preachers undermines religious commitment.

Over the last decade, robots continue to infiltrate the workforce, permeating occupations that once seemed immune to automation. This process seems to be inevitable because robots have ever-expanding capabilities. However, drawing from theories of cultural evolution and social learning, we propose that robots may have limited influence in domains that require high degrees of "credibility"; here we focus on the automation of religious preachers as one such domain.

Supernatural explanations across 114 societies are more common for natural than social phenomena.

Humans across the globe use supernatural beliefs to explain the world around them. This article explores whether cultural groups invoke the supernatural more to explain natural phenomena (for example, storms, disease outbreaks) or social phenomena (for example, murder, warfare). Quantitative analysis of ethnographic text across 114 geographically and culturally diverse societies found that supernatural explanations are more prevalent for natural than for social phenomena, consistent with theories that ground the origin of religious belief in a human tendency to perceive intent and agency in the natural world.

Enhanced Preprocessing Approach Using Ensemble Machine Learning Algorithms for Detecting Liver Disease.

There has been a sharp increase in liver disease globally, and many people are dying without even knowing that they have it. As a result of its limited symptoms, it is extremely difficult to detect liver disease until the very last stage. In the event of early detection, patients can begin treatment earlier, thereby saving their lives.

Catalyzing social change: Does concentration encourage action?

Countless social problems demand solutions, from climate change and gun control to poverty and systemic racism. But while some of these problems inspire action (e.g.

Valence-dependent mutation in lexical evolution.

A central goal of linguistics is to understand how words evolve. Past research has found that macro-level factors such as frequency of word usage and population size explain the pace of lexical evolution. Here we focus on cognitive and affective factors, testing whether valence (positivity-negativity) explains lexical evolution rates.

The rise of robots increases job insecurity and maladaptive workplace behaviors: Multimethod evidence.

Robots are transforming the nature of human work. Although human-robot collaborations can create new jobs and increase productivity, pundits often warn about how robots might replace humans at work and create mass unemployment. Despite these warnings, relatively little research has directly assessed how laypeople react to robots in the workplace.

Perception of strong social norms during the COVID-19 pandemic is linked to positive psychological outcomes.

Social norms can coordinate individuals and groups during collective threats. Pandemic-related social norms (e.g.

The new science of religious change.

Humans have believed in gods and spirits since the earliest days of the Holocene, and many people still believe in them today. Although the existence of religious belief has been a human constant, the nature and prevalence of religion has changed dramatically throughout human history. Here we describe the emerging science of religious change.

From Text to Thought: How Analyzing Language Can Advance Psychological Science.

Humans have been using language for millennia but have only just begun to scratch the surface of what natural language can reveal about the mind. Here we propose that language offers a unique window into psychology. After briefly summarizing the legacy of language analyses in psychological science, we show how methodological advances have made these analyses more feasible and insightful than ever before.

Tight cultures and vengeful gods: How culture shapes religious belief.

Billions of people from around the world believe in vengeful gods who punish immoral behavior. These punitive religious beliefs may foster prosociality and contribute to large-scale cooperation, but little is known about how these beliefs emerge and why people adopt them in the first place. We present a cultural-psychological model suggesting that cultural tightness-the strictness of cultural norms and normative punishment-helps to catalyze punitive religious beliefs by increasing people's motivation to punish norm violators.

The relationship between cultural tightness-looseness and COVID-19 cases and deaths: a global analysis.

Background: The COVID-19 pandemic is a global health crisis, yet certain countries have had far more success in limiting COVID-19 cases and deaths. We suggest that collective threats require a tremendous amount of coordination, and that strict adherence to social norms is a key mechanism that enables groups to do so. Here we examine how the strength of social norms-or cultural tightness-looseness-was associated with countries' success in limiting cases and deaths by October, 2020.

Association of high profile football matches in Europe with traffic accidents in Asia: archival study.

Objective: To investigate the association between popular football games played in Europe and the incidence of traffic accidents in Asia.

Design: Study based on 41 538 traffic accidents involving taxis in Singapore and 1 814 320 traffic accidents in Taiwan, combined with 12 788 European club football games over a seven year period.

Setting: Singapore and Taiwan.

The new trinity of religious moral character: the Cooperator, the Crusader, and the Complicit.

Does religion make people good or bad? We suggest that there are at least three distinct profiles of religious morality: the Cooperator, the Crusader, and the Complicit. Cooperators forego selfishness to benefit others, crusaders harm outgroups to bolster their own religious community, and the complicit use religion to justify selfish behavior and reduce blame. Different aspects of religion motivate each character: religious reverence makes people cooperators, religious tribalism makes people crusaders, and religious absolution makes people complicit.

The rise of COVID-19 cases is associated with support for world leaders.

COVID-19 has emerged as one of the deadliest and most disruptive events in recent human history. Drawing from political science and psychological theories, we examine the effects of daily confirmed cases in a country on citizens' support for the political leader through the first 120 d of 2020. Using three unique datasets which comprise daily approval ratings of head of government ( = 1,411,200) across 11 world leaders (Australia, Brazil, Canada, France, Germany, Hong Kong, India, Japan, Mexico, the United Kingdom, and the United States) and weekly approval ratings of governors across the 50 states in the United States ( = 912,048), we find a strong and significant positive association between new daily confirmed and total confirmed COVID-19 cases in the country and support for the heads of government.

Resource Stress Predicts Changes in Religious Belief and Increases in Sharing Behavior.

We examine and test alternative models for explaining the relationships between resource stress, beliefs that gods and spirits influence weather (to help or harm food supply or punish for norm violations), and customary beyond-household sharing behavior. Our model, the resource stress model, suggests that resource stress affects both sharing as well as conceptions of gods' involvement with weather, but these supernatural beliefs play no role in explaining sharing. An alternative model, the moralizing high god model, suggests that the relationship between resource stress and sharing is at least partially mediated by religious beliefs in moralizing high gods.

A global analysis of cultural tightness in non-industrial societies.

Human groups have long faced ecological threats such as resource stress and warfare, and must also overcome strains on coordination and cooperation that are imposed by growing social complexity. Tightness-looseness (TL) theory suggests that societies react to these challenges by becoming culturally tighter, with stronger norms and harsher punishment of deviant behaviour. TL theory further predicts that tightening is associated with downstream effects on social, political and religious institutions.

The cultural evolutionary trade-off of ritualistic synchrony.

From Australia to the Arctic, human groups engage in synchronous behaviour during communal rituals. Because ritualistic synchrony is widespread, many argue that it is functional for human groups, encouraging large-scale cooperation and group cohesion. Here, we offer a more nuanced perspective on synchrony's function.

Text analysis shows conceptual overlap as well as domain-specific differences in Christian and secular worldviews.

Theories differ over whether religious and secular worldviews are in competition or represent overlapping and compatible frameworks. Here we test these theories by examining homogeneity and overlap in Christian and non-religious people's explanations of the world. Christian and non-religious participants produced free text explanations of 54 natural and supernatural phenomena.

Conflict Changes How People View God.

Religion shapes the nature of intergroup conflict, but conflict may also shape religion. Here, we report four multimethod studies that reveal the impact of conflict on religious belief: The threat of warfare and intergroup tensions increase the psychological need for order and obedience to rules, which leads people to view God as more punitive. Studies 1 ( = 372) and 2 ( = 911) showed that people's concern about conflict correlates with belief in a punitive God.

Could a rising robot workforce make humans less prejudiced?

Automation is becoming ever more prevalent, with robot workers replacing many human employees. Many perspectives have examined the economic impact of a robot workforce, but here we consider its social impact: How will the rise of robot workers affect intergroup relations? Whereas some past research has suggested that more robots will lead to more intergroup prejudice, we suggest that robots could also reduce prejudice by highlighting commonalities between all humans. As robot workers become more salient, intergroup differences-including racial and religious differences-may seem less important, fostering a perception of common human identity (i.

Emotion semantics show both cultural variation and universal structure.

Many human languages have words for emotions such as "anger" and "fear," yet it is not clear whether these emotions have similar meanings across languages, or why their meanings might vary. We estimate emotion semantics across a sample of 2474 spoken languages using "colexification"-a phenomenon in which languages name semantically related concepts with the same word. Analyses show significant variation in networks of emotion concept colexification, which is predicted by the geographic proximity of language families.