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ABSTRACTWe investigate what processes may underlie heterogeneity in social preferences. We address this question by examining participants' decisions and associated response times across 12 mini‐ultimatum games. Using a finite mixture model and cross‐validating its classification with a response time analysis, we identified four groups of responders: one group takes little to no account of the proposed split or the foregone allocation and swiftly accepts any positive offer; two groups process primarily the objective properties of the allocations (fairness and kindness) and need more time the more properties need to be examined; and a fourth group, which takes more time than the others, appears to take into account what they would have proposed had they been put in the role of the proposer. We discuss implications of this joint decision–response time analysis. Copyright © 2013 John Wiley & Sons, Ltd.

AbstractAs climate change unfolds, extreme weather events are on the rise worldwide. According to experts, extreme weather risks already outrank those of terrorism and migration in likelihood and impact. But how well does the public understand weather risks and forecast uncertainty and thus grasp the amplified weather risks that climate change poses for the future? In a nationally representative survey (N = 1004; Germany), we tested the public's weather literacy and awareness of climate change using 62 factual questions. Many respondents misjudged important weather risks (e.g., they were unaware that UV radiation can be higher under patchy cloud cover than on a cloudless day) and struggled to connect weather conditions to their impacts (e.g., they overestimated the distance to a thunderstorm). Most misinterpreted a probabilistic forecast deterministically, yet they strongly underestimated the uncertainty of deterministic forecasts. Respondents with higher weather literacy obtained weather information more often and spent more time outside but were not more educated. Those better informed about climate change were only slightly more weather literate. Overall, the public does not seem well equipped to anticipate weather risks in the here and now and may thus also fail to fully grasp what climate change implies for the future. These deficits in weather literacy highlight the need for impact forecasts that translate what the weather may be into what the weather may do and for transparent communication of uncertainty to the public. Boosting weather literacy may help to improve the public's understanding of weather and climate change risks, thereby fostering informed decisions and mitigation support.

Why do grandparents invest so heavily in their grandchildren and what impact does this investment have on families? A multitude of factors influence the roles grandparents play in their families. Here, we present an interdisciplinary perspective of grandparenting incorporating theory and research from evolutionary biology, sociology and economics. Discriminative grandparental solicitude, biological relatedness and the impact of resource availability are three phenomena used to illustrate how these perspectives, within such a multi-level approach, add value by complementing not competing with each other. Changing demographics mean there is greater demand and opportunity for actively engaged grandparents to help their families, especially in times of need. Grandparents have been filling this emerging niche because in some societies the role of community and government never has, or increasingly cannot, meet the diverse needs of families. Built on an empirical foundation of descriptive and correlational research, grandparent research has rapidly entered a phase where the potential causal relationships between grandparents' roles and family health, well-being and structure can be scrutinised. Together, these investigations are producing high-quality evidence that ultimately can support informed public policy and service delivery decisions. We finish by detailing two examples of such research efforts that highlight opportunities for future research.

Um mit der Corona-Pandemie möglichst angemessen umgehen zu können, ist es wichtig, dass die Menschen hierzulande eine realistische Vorstellung davon haben, wie hoch ihr individuelles Risiko einer Erkrankung ist. Wie aktuelle Analysen der SOEP-CoV-Studie nun zeigen, sind sich die meisten Menschen in Deutschland durchaus bewusst, dass Faktoren wie das Lebensalter, Vorerkrankungen und der Beruf einen starken Einfluss auf ihr individuelles Risiko haben, lebensbedrohlich an Covid-19 zu erkranken. Gleichzeitig wird das durchschnittliche Risiko dafür deutlich überschätzt. Dies könnte durchaus dazu beitragen, dass die Bevölkerung die derzeitigen Schutzmaßnahmen wie das Abstandhalten und das Tragen von Masken auch bei geringen Neuinfektionszahlen beibehält. Nichtsdestoweniger ist die Politik gefordert, den Informationsstand und die Risikomündigkeit der Bevölkerung weiter zu stärken.

The coronavirus disease 2019 (COVID-19) pandemic has exposed scientific uncertainty in its raw form. When facts are uncertain, policy makers and health experts sometimes shy away from communicating scientific uncertainty, fearing that the uncertainty will generate mistrust. In Germany, for instance, the pandemic-related threat scenarios invoked have sometimes been devoid of uncertainty. Nevertheless, presenting uncertain aspects of the pandemic as certain may adversely affect citizens' trust and compliance with containment measures should those reports later prove invalid. We assessed people's preferences for health communications with varying degrees of scientific uncertainty in the context of the COVID-19 pandemic and explore factors associated with the preferred form of communication.

Public opinion is shaped in significant part by online content, spread via social media and curated algorithmically. The current online ecosystem has been designed predominantly to capture user attention rather than to promote deliberate cognition and autonomous choice; information overload, finely tuned personalization and distorted social cues, in turn, pave the way for manipulation and the spread of false information. How can transparency and autonomy be promoted instead, thus fostering the positive potential of the web? Effective web governance informed by behavioural research is critically needed to empower individuals online. We identify technologically available yet largely untapped cues that can be harnessed to indicate the epistemic quality of online content, the factors underlying algorithmic decisions and the degree of consensus in online debates. We then map out two classes of behavioural interventions—nudging and boosting— that enlist these cues to redesign online environments for informed and autonomous choice.

Individual judgments, feelings, and behaviors can spread from person to person in social networks, similarly to the propagation of infectious diseases. Despite major implications for many social phenomena, the underlying social-contagion processes are poorly understood. We examined how participants' perceptual judgments spread from one person to another and across diffusion chains. We gauged the speed, reach, and scale of social contagion. Judgment propagation tended to slow down with increasing social distance from the source. Crucially, it vanished beyond a social horizon of three to four people. These results advance the understanding of some of the mechanisms underlying social-contagion phenomena as well as their scope across domains as diverse as political mobilization, health practices, and emotions.

People rely on data-driven AI technologies nearly every time they go online, whether they are shopping, scrolling through news feeds, or looking for entertainment. Yet despite their ubiquity, personalization algorithms and the associated large-scale collection of personal data have largely escaped public scrutiny. Policy makers who wish to introduce regulations that respect people's attitudes towards privacy and algorithmic personalization on the Internet would greatly benefit from knowing how people perceive personalization and personal data collection. To contribute to an empirical foundation for this knowledge, we surveyed public attitudes towards key aspects of algorithmic personalization and people's data privacy concerns and behaviour using representative online samples in Germany (N = 1,065), Great Britain (N = 1,092), and the United States (N = 1,059). Our findings show that people object to the collection and use of sensitive personal information and to the personalization of political campaigning and, in Germany and Great Britain, to the personalization of news sources. Encouragingly, attitudes are independent of political preferences: People across the political spectrum share the same concerns about their data privacy and show similar levels of acceptance regarding personalized digital services and the use of private data for personalization. We also found an acceptability gap: People are more accepting of personalized services than of the collection of personal data and information required for these services. A large majority of respondents rated, on average, personalized services as more acceptable than the collection of personal information or data. The acceptability gap can be observed at both the aggregate and the individual level. Across countries, between 64% and 75% of respondents showed an acceptability gap. Our findings suggest a need for transparent algorithmic personalization that minimizes use of personal data, respects people's preferences on personalization, is easy to adjust, and does not extend to political advertising.

The weather forecast says that there is a "30% chance of rain," and we think we understand what it means. This quantitative statement is assumed to be unambiguous and to convey more information than does a qualitative statement like "It might rain tomorrow." Because the forecast is expressed as a single‐event probability, however, it does not specify the class of events it refers to. Therefore, even numerical probabilities can be interpreted by members of the public in multiple, mutually contradictory ways. To find out whether the same statement about rain probability evokes various interpretations, we randomly surveyed pedestrians in five metropolises located in countries that have had different degrees of exposure to probabilistic forecasts––Amsterdam, Athens, Berlin, Milan, and New York. They were asked what a "30% chance of rain tomorrow" means both in a multiple‐choice and a free‐response format. Only in New York did a majority of them supply the standard meteorological interpretation, namely, that when the weather conditions are like today, in 3 out of 10 cases there will be (at least a trace of) rain the next day. In each of the European cities, this alternative was judged as the least appropriate. The preferred interpretation in Europe was that it will rain tomorrow "30% of the time," followed by "in 30% of the area." To improve risk communication with the public, experts need to specify the reference class, that is, the class of events to which a single‐event probability refers.