Systematic Differences in Impact across Publication Tracks at PNAS

Background: Citation data can be used to evaluate the editorial policies and procedures of scientific journals. Here we investigate citation counts for the three different publication tracks of the Proceedings of the National Academy of Sciences of the United States of America (PNAS). This analysis explores the consequences of differences in editor and referee selection, while controlling for the prestige of the journal in which the papers appear. Methodology/Principal Findings: We find that papers authored and ‘‘Contributed’ ’ by NAS members (Track III) are on average cited less often than papers that are ‘‘Communicated’ ’ for others by NAS members (Track I) or submitted directly via the standard peer review process (Track II). However, we also find that the variance in the citation count of Contributed papers, and to a lesser extent Communicated papers, is larger than for direct submissions. Therefore when examining the 10 % most-cited papers from each track, Contributed papers receive the most citations, followed by Communicated papers, while Direct submissions receive the least citations. Conclusion/Significance: Our findings suggest that PNAS ‘‘Contributed’ ’ papers, in which NAS–member authors select their own reviewers, balance an overall lower impact with an increased probability of publishing exceptional papers. This analysis demonstrates that different editorial procedures are associated with different levels of impact, even within the same prominent journal, and raises interesting questions about the most appropriate metrics for judging an editorial policy’

The Online Laboratory: Conducting Experiments in a Real Labor Market

Online labor markets have great potential as platforms for conducting experiments, as they provide immediate access to a large and diverse subject pool and allow researchers to conduct randomized controlled trials. We argue that online experiments can be just as valid---both internally and externally---as laboratory and field experiments, while requiring far less money and time to design and to conduct. In this paper, we first describe the benefits of conducting experiments in online labor markets; we then use one such market to replicate three classic experiments and confirm their results. We confirm that subjects (1) reverse decisions in response to how a decision-problem is framed, (2) have pro-social preferences (value payoffs to others positively), and (3) respond to priming by altering their choices. We also conduct a labor supply field experiment in which we confirm that workers have upward sloping labor supply curves. In addition to reporting these results, we discuss the unique threats to validity in an online setting and propose methods for coping with these threats. We also discuss the external validity of results from online domains and explain why online results can have external validity equal to or even better than that of traditional methods, depending on the research question. We conclude with our views on the potential role that online experiments can play within the social sciences, and then recommend software development priorities and best practices

Evolutionary game dynamics of controlled and automatic decision-making

We integrate dual-process theories of human cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model where agents who make decisions using either automatic or controlled processing compete with each other for survival. Agents using automatic processing act quickly and so are more likely to acquire resources, but agents using controlled processing are better planners and so make more effective use of the resources they have. Using the replicator equation, we characterize the conditions under which automatic or controlled agents dominate, when coexistence is possible, and when bistability occurs. We then extend the replicator equation to consider feedback between the state of the population and the environment. Under conditions where having a greater proportion of controlled agents either enriches the environment or enhances the competitive advantage of automatic agents, we find that limit cycles can occur, leading to persistent oscillations in the population dynamics. Critically, however, these limit cycles only emerge when feedback occurs on a sufficiently long time scale. Our results shed light on the connection between evolution and human cognition, and demonstrate necessary conditions for the rise and fall of rationality.Comment: 9 pages, 7 figure

Who cooperates in repeated games: The role of altruism, inequity aversion, and demographics

We explore the extent to which altruism, as measured by giving in a dictator game (DG), accounts for play in a noisy version of the repeated prisoner's dilemma. We find that DG giving is correlated with cooperation in the repeated game when no cooperative equilibria exist, but not when cooperation is an equilibrium. Furthermore, none of the commonly observed strategies are better explained by inequity aversion or efficiency concerns than money maximization. Various survey questions provide additional evidence for the relative unimportance of social preferences. We conclude that cooperation in repeated games is primarily motivated by long-term payoff maximization and that even though some subjects may have other goals, this does not seem to be the key determinant of how play varies with the parameters of the repeated game. In particular, altruism does not seem to be a major source of the observed diversity of play.Economic

Indirect reciprocity and the evolution of prejudicial groups

Prejudicial attitudes are widely seen between human groups, with significant consequences. Actions taken in light of prejudice result in discrimination, and can contribute to societal division and hostile behaviours. We define a new class of group, the prejudicial group, with membership based on a common prejudicial attitude towards the out-group. It is assumed that prejudice acts as a phenotypic tag, enabling groups to form and identify themselves on this basis. Using computational simulation, we study the evolution of prejudicial groups, where members interact through indirect reciprocity. We observe how cooperation and prejudice coevolve, with cooperation being directed in-group. We also consider the co-evolution of these variables when out-group interaction and global learning are immutable, emulating the possible pluralism of a society. Diversity through three factors is found to be influential, namely out-group interaction, out-group learning and number of sub-populations. Additionally populations with greater in-group interaction promote both cooperation and prejudice, while global rather than local learning promotes cooperation and reduces prejudice. The results also demonstrate that prejudice is not dependent on sophisticated human cognition and is easily manifested in simple agents with limited intelligence, having potential implications for future autonomous systems and human-machine interaction

The Dopamine Receptor D4 Gene (DRD4) and Self-Reported Risk Taking in the Economic Domain

Recent evidence suggests that individual variation in risk taking is partly due to genetic factors. We explore how self-reported risk taking in different domains correlates with variation in the dopamine receptor D4 gene (DRD4). Past studies conflict on the influence of DRD4 in relation to risk taking. A sample of 237 serious tournament contract bridge players, experts on risk taking in one domain, was genotyped for having a 7-repeat allele (7R+) or not (7R-) at RD4. No difference was found between 7R+ and 7R- individuals in general risk taking or in several other risk-related activities.

Winners Don't Punish

Economic

Dopamine and Risk Preferences in Different Domains

Individuals differ significantly in their willingness to take risks. Such differences may stem, at least in part, from individual biological (genetic) differences. We explore how risk-taking behavior correlates with different versions of the dopamine receptor D4 gene (DRD4), which has been implicated in previous studies of risk taking. We investigate risk taking in three contexts: economic risk taking as proxied by a financial gamble, self-reported general risk taking, and self-reported behavior in risk-related activities. Our participants are serious tournament bridge players with substantial experience in risk taking. Presumably, this sample is much less varied in its environment than a random sample of the population, making genetic based differences easier to detect. A prior study (Dreber et al. 2010) looked at risk taking by these individuals in their bridge decisions. Here we examine the riskiness of decisions they take in other contexts. We find evidence that individuals with a 7-repeat allele (7R+) of DRD4 take significantly more economic risk in an investment game than individuals without this allele (7R-). Interestingly, this positive relationship is driven by the men in our study, while the women show a negative but non-significant result. Even though the number of 7R+ women in our sample is low, our results may indicate a gender difference in how the 7R+ genotype affects behavior, a possibility that merits further study. Considering other risk measures, we find no difference between 7R+ and 7R- individuals in general risk taking or any of the risk-related activities. Overall, our results indicate that the dopamine system plays an important role in explaining individual differences in economic risk taking in men, but not necessarily in other activities involving risk.Risk preferences; Dopamine; Risk taking; Risk perception; DRD4