Higher socioeconomic status does not predict decreased prosocial behavior in a field experiment.

Does higher socioeconomic status predict decreased prosocial behavior? Methodological issues such as the reliance of survey studies on self-reported measures of prosociality, the insufficient control of relative incentives in experiments, and the use of non-random samples, have prevented researchers from ruling out that there is a negative association between socioeconomic status (SES) and prosociality. Here, we present results from a field experiment on the willingness of unaware individuals of different SES to undertake an effortful prosocial task-returning a misdelivered letter. Specifically, using the rental or sale value of homes as indicators of SES, we randomly selected households of high and low SES and misdelivered envelopes to them. Despite controlling for numerous covariates and performing a series of ancillary tests, we fail to find any evidence that higher SES predicts decreased prosocial behavior. Instead, we find that misdelivered letters are substantially more likely to be returned from high rather than low SES households.

Predicting social tipping and norm change in controlled experiments.

The ability to predict when societies will replace one social norm for another can have significant implications for welfare, especially when norms are detrimental. A popular theory poses that the pressure to conform to social norms creates tipping thresholds which, once passed, propel societies toward an alternative state. Predicting when societies will reach a tipping threshold, however, has been a major challenge because of the lack of experimental data for evaluating competing models. We present evidence from a large-scale laboratory experiment designed to test the theoretical predictions of a threshold model for social tipping and norm change. In our setting, societal preferences change gradually, forcing individuals to weigh the benefit from deviating from the norm against the cost from not conforming to the behavior of others. We show that the model correctly predicts in 96% of instances when a society will succeed or fail to abandon a detrimental norm. Strikingly, we observe widespread persistence of detrimental norms even when individuals determine the cost for nonconformity themselves as they set the latter too high. Interventions that facilitate a common understanding of the benefits from change help most societies abandon detrimental norms. We also show that instigators of change tend to be more risk tolerant and to dislike conformity more. Our findings demonstrate the value of threshold models for understanding social tipping in a broad range of social settings and for designing policies to promote welfare.

Surveillance cues do not enhance altruistic behavior among anonymous strangers in the field.

The degree of altruistic behavior among strangers is an evolutionary puzzle. A prominent explanation is the evolutionary legacy hypothesis according to which an evolved reciprocity-based psychology affects behavior even when reciprocity is impossible, i.e., altruistic behavior in such instances is maladaptive. Empirical support for this explanation comes from laboratory experiments showing that surveillance cues, e.g., photographs of watching eyes, increase altruistic behavior. A competing interpretation for this evidence, however, is that the cues signal the experimenter's expectations and participants, aware of being monitored, intentionally behave more altruistically to boost their reputation. Here we report the first results from a field experiment on the topic in which participants are unaware they are being monitored and reciprocity is precluded. The experiment investigates the impact of surveillance cues on a textbook example of altruistic behavior-hand hygiene prior to treating a 'patient'. We find no evidence surveillance cues affect hand hygiene, despite using different measures of hand-hygiene quality and cues that have been previously shown to be effective. We argue that surveillance cues may have an effect only when participants have reasons to believe they are actually monitored. Thus they cannot support claims altruistic behavior between strangers is maladaptive.

Altruistic punishment does not increase with the severity of norm violations in the field.

The degree of human cooperation among strangers is a major evolutionary puzzle. A prominent explanation is that cooperation is maintained because many individuals have a predisposition to punish those violating group-beneficial norms. A critical condition for cooperation to evolve in evolutionary models is that punishment increases with the severity of the violation. Here we present evidence from a field experiment with real-life interactions that, unlike in lab experiments, altruistic punishment does not increase with the severity of the violation, regardless of whether it is direct (confronting a violator) or indirect (withholding help). We also document growing concerns for counter-punishment as the severity of the violation increases, indicating that the marginal cost of direct punishment increases with the severity of violations. The evidence suggests that altruistic punishment may not provide appropriate incentives to deter large violations. Our findings thus offer a rationale for the emergence of formal institutions for promoting large-scale cooperation among strangers.

Direct and indirect punishment among strangers in the field.

Many interactions in modern human societies are among strangers. Explaining cooperation in such interactions is challenging. The two most prominent explanations critically depend on individuals' willingness to punish defectors: In models of direct punishment, individuals punish antisocial behavior at a personal cost, whereas in models of indirect reciprocity, they punish indirectly by withholding rewards. We investigate these competing explanations in a field experiment with real-life interactions among strangers. We find clear evidence of both direct and indirect punishment. Direct punishment is not rewarded by strangers and, in line with models of indirect reciprocity, is crowded out by indirect punishment opportunities. The existence of direct and indirect punishment in daily life indicates the importance of both means for understanding the evolution of cooperation.

Altruistic punishment: what field data can (and cannot) demonstrate.

The rarity of altruistic punishment in small-scale societies should not be interpreted as evidence that altruistic punishment is not an important determinant of cooperation in general. While it is essential to collect field data on altruistic punishment, this kind of data has limitations. Laboratory experiments can help shed light on the role of altruistic punishment "in the wild."

Developing the next-generation climate system models: challenges and achievements.

Although climate models have been improving in accuracy and efficiency over the past few decades, it now seems that these incremental improvements may be slowing. As tera/petascale computing becomes massively parallel, our legacy codes are less suitable, and even with the increased resolution that we are now beginning to use, these models cannot represent the multiscale nature of the climate system. This paper argues that it may be time to reconsider the use of adaptive mesh refinement for weather and climate forecasting in order to achieve good scaling and representation of the wide range of spatial scales in the atmosphere and ocean. Furthermore, the challenge of introducing living organisms and human responses into climate system models is only just beginning to be tackled. We do not yet have a clear framework in which to approach the problem, but it is likely to cover such a huge number of different scales and processes that radically different methods may have to be considered. The challenges of multiscale modelling and petascale computing provide an opportunity to consider a fresh approach to numerical modelling of the climate (or Earth) system, which takes advantage of the computational fluid dynamics developments in other fields and brings new perspectives on how to incorporate Earth system processes. This paper reviews some of the current issues in climate (and, by implication, Earth) system modelling, and asks the question whether a new generation of models is needed to tackle these problems.