Search

Using an advice-taking paradigm, we investigated how people use information about the wisdom of the crowds when revising their judgments. We focused on two types of information: information about the size of the advisor crowd and information about the distribution of the judgments within the crowd. To test whether judges use these two types of information, we varied the size of the advisor crowd (two, four, or eight advisors) and orthogonally manipulated whether judges received advice in the form of a crowd estimate or in the form of the separate individual judgments. In a third condition, participants received the crowd estimate, but it was labeled as stemming from an individual. We found no evidence that judges used information about the size of the crowd, but they considered information about the distribution of the advice when revising their opinions. Compared with crowd estimates, receiving the individual judgments as advice led to less advice taking but not to substantial differences in post-advice accuracy. Exploratory analyses showed that judges receiving multiple pieces of advice heeded advice less when their initial judgments were closer to the center of the distribution of judgments. In those instances, their initial judgments were also the most accurate, so they stood to gain less from the advice. Receiving multiple pieces of advice also led to smaller confidence gains, suggesting that judges receiving crowd judgments as advice might underestimate the variance of the underlying individual judgments.

Additional co-authors: Ivan Ropovik, Balazs Aczel, Lena F. Aeschbach, Luca Andrighetto, Jack D. Arnal, Holly Arrow, Peter Babincak, Bence E. Bakos, Gabriel Banik, Ernest Baskin, Radomir Belopavlovic, Michael H. Bernstein, Michal Bialek, Nicholas G. Bloxsom, Bojana Bodroža, Diane B. V. Bonfiglio, Leanne Boucher, Florian Bruhlmann, Claudia C. Brumbaugh, Erica Casini, Yiling Chen, Carlo Chiorri, William J. Chopik, Oliver Christ, Antonia M. Ciunci, Heather M. Claypool, Sean Coary, Marija V. Cˇolic, W. Matthew Collins, Paul G. Curran, Chris R. Day, Anna Dreber, John E. Edlund, Filipe Falcao, Anna Fedor, Lily Feinberg, Ian R. Ferguson, Maire Ford, Michael C. Frank, Emily Fryberger, Alexander Garinther, Katarzyna Gawryluk, Kayla Ashbaugh, Mauro Giacomantonio, Steffen R. Giessner, Jon E. Grahe, Rosanna E. Guadagno, Ewa Halasa, Rias A. Hilliard, Joachim Huffmeier, Sean Hughes, Katarzyna Idzikowska, Michael Inzlicht, Alan Jern, William Jimenez-Leal, Magnus Johannesson, Jennifer A. Joy-Gaba, Mathias Kauff, Danielle J. Kellier, Grecia Kessinger, Mallory C. Kidwell, Amanda M. Kimbrough, Josiah P. J. King, Vanessa S. Kolb, Sabina Kolodziej, Marton Kovacs, Karolina Krasuska, Sue Kraus, Lacy E. Krueger, Katarzyna Kuchno, Caio Ambrosio Lage, Eleanor V. Langford, Carmel A. Levitan, Tiago Jesse Souza de Lima, Hause Lin, Samuel Lins, Jia E. Loy, Dylan Manfredi, Łukasz Markiewicz, Madhavi Menon, Brett Mercier, Mitchell Metzger, Venus Meyet, Jeremy K. Miller, Andres Montealegre, Don A. Moore, Rafal Muda, Gideon Nave, Austin Lee Nichols, Sarah A. Novak, Christian Nunnally, Ana Orlic, Anna Palinkas, Angelo Panno, Kimberly P. Parks, Ivana Pedovic, Emilian Pekala, Matthew R. Penner, Sebastiaan Pessers, Boban Petrovic, Thomas Pfeiffer, Damian Pienkosz, Emanuele Preti, Danka Puric, Tiago Ramos, Jonathan Ravid, Timothy S. Razza, Katrin Rentzsch, Juliette Richetin, Sean C. Rife, Anna Dalla Rosa, Kaylis Hase Rudy, Janos Salamon, Blair Saunders, Przemyslaw Sawicki, Kathleen Schmidt, Kurt Schuepfer, Thomas Schultze, Stefan Schulz-Hardt, Astrid Schutz, Ani N. Shabazian, Rachel L. Shubella, Adam Siegel, Ruben Silva, Barbara Sioma, Lauren Skorb, Luana Elayne Cunha de Souza, Sara Steegen, L. A. R. Stein, R. Weylin Sternglanz, Darko Stojilovic, Daniel Storage, Gavin Brent Sullivan, Barnabas Szaszi, Peter Szecsi, Orsolya Szoke, Attila Szuts, Manuela Thomae, Natasha D. Tidwell, Carly Tocco, Ann-Kathrin Torka, Francis Tuerlinckx, Wolf Vanpaemel, Leigh Ann Vaughn, Michelangelo Vianello, Domenico Viganola, Maria Vlachou, Ryan J. Walker, Sophia C. Weissgerber, Aaron L. Wichman, Bradford J. Wiggins, Daniel Wolf, Michael J. Wood, David Zealley, Iris Žeželj, Mark Zrubka, and Brian A. Nosek

As part of the Many Labs 5 project, we ran a replication of van Dijk, van Kleef, Steinel, and van Beest’s (2008) study examining the effect of emotions in negotiations. They reported that when the consequences of rejection were low, subjects offered fewer chips to angry bargaining partners than to happy partners. We ran this replication under three protocols: the protocol used in the Reproducibility Project: Psychology, a revised protocol, and an online protocol. The effect averaged one ninth the size of the originally reported effect and was significant only for the revised protocol. However, the difference between the original and revised protocols was not significant.

Recent research has shown that from early in development, children selectively form new beliefs in response to information supplied by others. However, little is known about the development of selective revision of existing beliefs in response to socially conveyed information. Such selective social belief revison has been extensively studied by social psychologists in the context of advice-taking. Here, we adapted the methods of this research tradition for studying selective advice-taking in young children and adults. Participants solved a perceptual judgment task, received advice, and subsequently made final decisions. The informational access (perceptual quality) of participants and advisor were experimentally manipulated. Adults revised their judgments systematically as a function of both their own and the advisor’s informational access while children based their adjustments only on their own informational access. Two follow-up experiments suggest, however, that this pattern of results in children reflected performance rather than competence limitations: In suitably modified tasks, children did consider both their own information and that of the advisor in their selective social belief revision.

Advice is a powerful means to improve peoples' judgments and decisions. Because advice quality is rarely apparent, decision-makers must infer it from the characteristics of the advisor or the advice itself. Here, we focus on a largely neglected advice characteristic that should signal quality: advice precision. In a preregistered, high-powered study (N = 195), we tested the effects of advice precision on advice taking. Drawing from past research and theorizing on anchor precision, we derived and tested two competing hypotheses for the relation of advice precision and advice taking—one predicting a monotone increase in advice taking when advice precision increases and the other predicting a backfiring effect of overly precise advice resulting in an inverted U-shape. Our results support the notion of a monotone, albeit not a strong monotone, relationship. Higher perceived advice quality correlated with individuals' advice taking. Consistent with the idea that advice precision serves as a cue for advice quality, the effect of advice precision on advice taking was statistically mediated by perceived advice quality. Although the mediation analysis does not allow for causal interpretation because we did not manipulate the mediating variable, it shows that the effect of advice precision on advice taking is not merely a demand effect. Implications of our findings for theory and practice are discussed.

Developmental research, like many fields, is plagued by low sample sizes and inconclusive findings. The problem is amplified by the difficulties associated with recruiting infant participants for research as well as the increased variability in infant responses. With sequential testing designs providing a viable alternative to paradigms facing such issues, the current study implemented a Sequential Bayes Factor (SBF) design on three findings in the developmental literature. In particular, using the framework described by Schonbrodt and colleagues (2017), we examined infants' sensitivity to mispronunciations of familiar words, their learning of novel word-object associations from cross-situational learning paradigms, and their assumption of mutual exclusivity in assigning novel labels to novel objects. We tested an initial sample of 20 participants in each study, incrementally increasing sample size by one and computing a Bayes Factor with each additional participant. In one study, we were able to obtain moderate evidence for the alternate hypotheses despite testing less than half the number of participants as in the original study. We did not replicate the findings of the cross-situational learning study. Indeed, the data were five times more likely under the null hypothesis, allowing us to conclude that infants did not recognize the trained word-object associations presented in the task. We discuss these findings in light of the advantages and disadvantages of using a SBF design in developmental research while also providing researchers with an account of how we implemented this design across multiple studies.

We investigated whether Deep Brain Stimulation (DBS) of the subthalamic nucleus (STN) influences social validation as measured by a Judge-Advisor task. In contrast to healthy controls and patients with their DBS OFF, patients with their stimulation switched on do not experience a gain of confidence after receiving competent advice.

As part of the Many Labs 5 project, we ran a replication of Van Dijk, Van Kleef, Steinel, & Van Beest’s (2008) study “A social functional approach to emotions in bargaining: When communicating anger pays and when it backfires,” which examined the effect of emotions in negotiations. Van Dijk et al. (2008) report that when the consequences of rejection were low, subjects offered fewer chips to angry bargaining partners when compared to happy partners. In the current study, we ran this replication under three protocols: the protocol used in the Replication Project (2015), a revised protocol, and an online protocol.

Replications in psychological science sometimes fail to reproduce prior findings. If replications use methods that are unfaithful to the original study or ineffective in eliciting the phenomenon of interest, then a failure to replicate may be a failure of the protocol rather than a challenge to the original finding. Formal pre-data collection peer review by experts may address shortcomings and increase replicability rates. We selected 10 replications from the Reproducibility Project: Psychology (RP:P; Open Science Collaboration, 2015) in which the original authors had expressed concerns about the replication designs before data collection and only one of which was “statistically significant” (p < .05). Commenters suggested that lack of adherence to expert review and low-powered tests were the reasons that most of these RP:P studies failed to replicate (Gilbert et al., 2016). We revised the replication protocols and received formal peer review prior to conducting new replications. We administered the RP:P and Revised protocols in multiple laboratories (Median number of laboratories per original study = 6.5; Range 3 to 9; Median total sample = 1279.5; Range 276 to 3512) for high-powered tests of each original finding with both protocols. Overall, Revised protocols produced similar effect sizes as RP:P protocols following the preregistered analysis plan (Δr = .002 or .014, depending on analytic approach). The median effect size for Revised protocols (r = .05) was similar to RP:P protocols (r = .04) and the original RP:P replications (r = .11), and smaller than the original studies (r = .37). The cumulative evidence of original study and three replication attempts suggests that effect sizes for all 10 (median r = .07; range .00 to .15) are 78% smaller on average than original findings (median r = .37; range .19 to .50), with very precisely estimated effects.

A Transparent game is a game-theoretic setting that takes action visibility into account. In each round, depending on the relative timing of their actions, players have a certain probability to see their partner’s choice before making their own decision. This probability is determined by the level of transparency. At the two extremes, a game with zero transparency is equivalent to the classical simultaneous game, and a game with maximal transparency corresponds to a sequential game. Despite the prevalence of intermediate transparency in many everyday interactions such scenarios have not been sufficiently studied. Here we consider a transparent iterated Prisoner’s dilemma (iPD) and use evolutionary simulations to investigate how and why the success of various strategies changes with the level of transparency. We demonstrate that non-zero transparency greatly reduces the set of successful memory-one strategies compared to the simultaneous iPD. For low and moderate transparency the classical “Win – Stay, Lose – Shift” (WSLS) strategy is the only evolutionary successful strategy. For high transparency all strategies are evolutionary unstable in the sense that they can be easily counteracted, and, finally, for maximal transparency a novel “Leader-Follower” strategy outperforms WSLS. Our results provide a partial explanation for the fact that the strategies proposed for the simultaneous iPD are rarely observed in nature, where high levels of transparency are common.

A Transparent game is a game-theoretic setting that takes action visibility into account. In each round, depending on the relative timing of their actions, players have a certain probability to see their partner’s choice before making their own decision. This probability is determined by the level of transparency. At the two extremes, a game with zero transparency is equivalent to the classical simultaneous game, and a game with maximal transparency corresponds to a sequential game. Despite the prevalence of intermediate transparency in many everyday interactions such scenarios have not been sufficiently studied. Here we consider a transparent iterated Prisoner’s dilemma (iPD) and use evolutionary simulations to investigate how and why the success of various strategies changes with the level of transparency. We demonstrate that non-zero transparency greatly reduces the set of successful memory-one strategies compared to the simultaneous iPD. For low and moderate transparency the classical “Win - Stay, Lose - Shift” (WSLS) strategy is the only evolutionary successful strategy. For high transparency all strategies are evolutionary unstable in the sense that they can be easily counteracted, and, finally, for maximal transparency a novel “Leader-Follower” strategy outperforms WSLS. Our results provide a partial explanation for the fact that the strategies proposed for the simultaneous iPD are rarely observed in nature, where high levels of transparency are common.

Group interaction can empower groups to outperform even their best members; unfortunately, such strong synergy is rare. The prototypical decision situation where synergy through interaction is possible is called a hidden profile (HP). The two main characteristics of these situations are that (1) each group member has new, unshared information that the other group members do not have, and (2) integrating this unshared information implies a different, better decision alternative than each member’s information alone. The hidden profile coding scheme is designed to code the initially shared and unshared information that is mentioned during the group discussion. The hidden profile coding scheme therefore aims to directly observe group decision processes that potentially lead to synergy.

Real-world agents, such as humans, animals and robots, observe each other during interactions and choose their own actions taking the partners’ ongoing behaviour into account. Yet, classical game theory assumes that players act either strictly sequentially or strictly simultaneously (without knowing the choices of each other). To account for action visibility and provide a more realistic model of interactions under time constraints, we introduce a new game-theoretic setting called transparent game, where each player has a certain probability to observe the choice of the partner before deciding on its own action. Using evolutionary simulations, we demonstrate that even a small probability of seeing the partner’s choice before one’s own decision substantially changes evolutionary successful strategies. Action visibility enhances cooperation in a Bach-or-Stravinsky game, but disrupts cooperation in a more competitive iterated Prisoner’s Dilemma. In both games, strategies based on the “Win–stay, lose–shift” and “Tit-for-tat” principles are predominant for moderate transparency, while for high transparency strategies of “Leader-Follower” type emerge. Our results have implications for studies of human and animal social behaviour, especially for the analysis of dyadic and group interactions.

Considering advice from others is a pervasive element of human social life. We used the judge-advisor paradigm to investigate the neural correlates of advice evaluation and advice integration by means of functional magnetic resonance imaging. Our results demonstrate that evaluating advice recruits the "mentalizing network," brain regions activated when people think about others' mental states. Important activation differences exist, however, depending upon the perceived competence of the advisor. Consistently, additional analyses demonstrate that integrating others' advice, i.e., how much participants actually adjust their initial estimate, correlates with neural activity in the centromedial amygdala in the case of a competent and with activity in visual cortex in the case of an incompetent advisor. Taken together, our findings, therefore, demonstrate that advice evaluation and integration rely on dissociable neural mechanisms and that significant differences exist depending upon the advisor's reputation, which suggests different modes of processing advice depending upon the perceived competence of the advisor.

Response to Minson and Mueller (2012) peerReviewed

At world level, the current official number of large camelids cannot be determined exactly (it is estimated to be more than 35 million heads), and the role of camels in the livestock economy is highly variable. The only reliable statistics are provided by FAO since 1961. According to these data, five different patterns of demographic changes have been observed. In countries marked by a regular or drastic decline of their camelid population, a tendency to re-increase has been in force since the beginning of the century, except in India. Generally, countries marked by a sharp recent increase in their large camelid population have implemented a census and readjusted their data. Many inconsistencies occur in available data, most notably cases arising from changes occurring in state status (for example secession of Eritrea, Soviet Union collapse). Moreover, large camelid stocks in Australia, in countries of new camel establishment (Western countries) and those related to the expansion of camel farming, notably in Africa, are not recorded in the international database. In addition, there is no distinction between dromedary and Bactrian data. The present large camelid population in the world is probably more than 40 million and could reach 60 million after 25 years from now if the current demographic trend is maintained.