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Showing papers in "Nature Human Behaviour in 2018"


Journal ArticleDOI
Daniel J. Benjamin1, James O. Berger2, Magnus Johannesson1, Magnus Johannesson3, Brian A. Nosek4, Brian A. Nosek5, Eric-Jan Wagenmakers6, Richard A. Berk7, Kenneth A. Bollen8, Björn Brembs9, Lawrence D. Brown7, Colin F. Camerer10, David Cesarini11, David Cesarini12, Christopher D. Chambers13, Merlise A. Clyde2, Thomas D. Cook14, Thomas D. Cook15, Paul De Boeck16, Zoltan Dienes17, Anna Dreber3, Kenny Easwaran18, Charles Efferson19, Ernst Fehr20, Fiona Fidler21, Andy P. Field17, Malcolm R. Forster22, Edward I. George7, Richard Gonzalez23, Steven N. Goodman24, Edwin J. Green25, Donald P. Green26, Anthony G. Greenwald27, Jarrod D. Hadfield28, Larry V. Hedges14, Leonhard Held20, Teck-Hua Ho29, Herbert Hoijtink30, Daniel J. Hruschka31, Kosuke Imai32, Guido W. Imbens24, John P. A. Ioannidis24, Minjeong Jeon33, James Holland Jones34, Michael Kirchler35, David Laibson36, John A. List37, Roderick J. A. Little23, Arthur Lupia23, Edouard Machery38, Scott E. Maxwell39, Michael A. McCarthy21, Don A. Moore40, Stephen L. Morgan41, Marcus R. Munafò42, Shinichi Nakagawa43, Brendan Nyhan44, Timothy H. Parker45, Luis R. Pericchi46, Marco Perugini47, Jeffrey N. Rouder48, Judith Rousseau49, Victoria Savalei50, Felix D. Schönbrodt51, Thomas Sellke52, Betsy Sinclair53, Dustin Tingley36, Trisha Van Zandt16, Simine Vazire54, Duncan J. Watts55, Christopher Winship36, Robert L. Wolpert2, Yu Xie32, Cristobal Young24, Jonathan Zinman44, Valen E. Johnson18, Valen E. Johnson1 
University of Southern California1, Duke University2, Stockholm School of Economics3, University of Virginia4, Center for Open Science5, University of Amsterdam6, University of Pennsylvania7, University of North Carolina at Chapel Hill8, University of Regensburg9, California Institute of Technology10, Research Institute of Industrial Economics11, New York University12, Cardiff University13, Northwestern University14, Mathematica Policy Research15, Ohio State University16, University of Sussex17, Texas A&M University18, Royal Holloway, University of London19, University of Zurich20, University of Melbourne21, University of Wisconsin-Madison22, University of Michigan23, Stanford University24, Rutgers University25, Columbia University26, University of Washington27, University of Edinburgh28, National University of Singapore29, Utrecht University30, Arizona State University31, Princeton University32, University of California, Los Angeles33, Imperial College London34, University of Innsbruck35, Harvard University36, University of Chicago37, University of Pittsburgh38, University of Notre Dame39, University of California, Berkeley40, Johns Hopkins University41, University of Bristol42, University of New South Wales43, Dartmouth College44, Whitman College45, University of Puerto Rico46, University of Milan47, University of California, Irvine48, Paris Dauphine University49, University of British Columbia50, Ludwig Maximilian University of Munich51, Purdue University52, Washington University in St. Louis53, University of California, Davis54, Microsoft55
TL;DR: The default P-value threshold for statistical significance is proposed to be changed from 0.05 to 0.005 for claims of new discoveries in order to reduce uncertainty in the number of discoveries.
Abstract: We propose to change the default P-value threshold for statistical significance from 0.05 to 0.005 for claims of new discoveries.

1,586 citations


Journal ArticleDOI
TL;DR: It is found that peer beliefs of replicability are strongly related to replicable, suggesting that the research community could predict which results would replicate and that failures to replicate were not the result of chance alone.
Abstract: Being able to replicate scientific findings is crucial for scientific progress. We replicate 21 systematically selected experimental studies in the social sciences published in Nature and Science between 2010 and 2015. The replications follow analysis plans reviewed by the original authors and pre-registered prior to the replications. The replications are high powered, with sample sizes on average about five times higher than in the original studies. We find a significant effect in the same direction as the original study for 13 (62%) studies, and the effect size of the replications is on average about 50% of the original effect size. Replicability varies between 12 (57%) and 14 (67%) studies for complementary replicability indicators. Consistent with these results, the estimated true-positive rate is 67% in a Bayesian analysis. The relative effect size of true positives is estimated to be 71%, suggesting that both false positives and inflated effect sizes of true positives contribute to imperfect reproducibility. Furthermore, we find that peer beliefs of replicability are strongly related to replicability, suggesting that the research community could predict which results would replicate and that failures to replicate were not the result of chance alone.

759 citations


Journal ArticleDOI
TL;DR: Findings from psychology and economics on subjective well-being across cultures are synthesized and identified to identify outstanding questions, priorities for future research and pathways to policy implementation.
Abstract: The empirical science of subjective well-being, popularly referred to as happiness or satisfaction, has grown enormously in the past decade. In this Review, we selectively highlight and summarize key researched areas that continue to develop. We describe the validity of measures and their potential biases, as well as the scientific methods used in this field. We describe some of the predictors of subjective well-being such as temperament, income and supportive social relationships. Higher subjective well-being has been associated with good health and longevity, better social relationships, work performance and creativity. At the community and societal levels, cultures differ not only in their levels of well-being but also to some extent in the types of subjective well-being they most value. Furthermore, there are both universal and unique predictors of subjective well-being in various societies. National accounts of subjective well-being to help inform policy decisions at the community and societal levels are now being considered and adopted. Finally we discuss the unknowns in the science and needed future research.

560 citations


Journal ArticleDOI
Daniel Lakens1, Federico Adolfi2, Federico Adolfi3, Casper J. Albers4, Farid Anvari5, Matthew A. J. Apps6, Shlomo Argamon7, Thom Baguley8, Raymond Becker9, Stephen D. Benning10, Daniel E. Bradford11, Erin Michelle Buchanan12, Aaron R. Caldwell13, Ben Van Calster14, Ben Van Calster15, Rickard Carlsson16, Sau-Chin Chen17, Bryan Chung18, Lincoln J. Colling19, Gary S. Collins6, Zander Crook20, Emily S. Cross21, Emily S. Cross22, Sameera Daniels, Henrik Danielsson23, Lisa M. DeBruine22, Daniel J. Dunleavy24, Brian D. Earp25, Michele I. Feist26, Jason D. Ferrell27, Jason D. Ferrell28, James G. Field29, Nicholas W. Fox30, Amanda Friesen31, Caio Gomes, Monica Gonzalez-Marquez32, James A. Grange33, Andrew P. Grieve, Robert Guggenberger34, James T. Grist19, Anne-Laura van Harmelen19, Fred Hasselman35, Kevin D. Hochard36, Mark R. Hoffarth37, Nicholas P. Holmes38, Michael Ingre39, Peder M. Isager23, Hanna K. Isotalus40, Christer Johansson41, Konrad Juszczyk42, David A. Kenny43, Ahmed A. Khalil3, Ahmed A. Khalil44, Ahmed A. Khalil45, Barbara Konat42, Junpeng Lao46, Erik Gahner Larsen47, Gerine M.A. Lodder4, Jiří Lukavský48, Christopher R. Madan38, David Manheim49, Stephen R. Martin50, Andrea E. Martin3, Andrea E. Martin20, Deborah G. Mayo51, Randy J. McCarthy52, Kevin McConway53, Colin McFarland, Amanda Q. X. Nio54, Gustav Nilsonne55, Gustav Nilsonne56, Gustav Nilsonne57, Cilene Lino de Oliveira58, Jean-Jacques Orban de Xivry14, Sam Parsons6, Gerit Pfuhl59, Kimberly A. Quinn60, John J. Sakon37, S. Adil Saribay61, Iris K. Schneider62, Manojkumar Selvaraju63, Zsuzsika Sjoerds15, Samuel G. Smith64, Tim Smits14, Jeffrey R. Spies65, Jeffrey R. Spies66, Vishnu Sreekumar67, Crystal N. Steltenpohl68, Neil Stenhouse11, Wojciech Świątkowski, Miguel A. Vadillo69, Marcel A.L.M. van Assen70, Marcel A.L.M. van Assen71, Matt N. Williams72, Samantha E Williams73, Donald R. Williams74, Tal Yarkoni27, Ignazio Ziano75, Rolf A. Zwaan39 
Eindhoven University of Technology1, National Scientific and Technical Research Council2, Max Planck Society3, University of Groningen4, Flinders University5, University of Oxford6, Illinois Institute of Technology7, Nottingham Trent University8, Bielefeld University9, University of Nevada, Las Vegas10, University of Wisconsin-Madison11, Missouri State University12, University of Arkansas13, Katholieke Universiteit Leuven14, Leiden University15, Linnaeus University16, Tzu Chi University17, University of British Columbia18, University of Cambridge19, University of Edinburgh20, Bangor University21, University of Glasgow22, Linköping University23, Florida State University24, Yale University25, University of Louisiana at Lafayette26, University of Texas at Austin27, St. Edward's University28, West Virginia University29, Rutgers University30, Indiana University31, RWTH Aachen University32, Keele University33, University of Tübingen34, Radboud University Nijmegen35, University of Chester36, New York University37, University of Nottingham38, Erasmus University Rotterdam39, University of Bristol40, Sahlgrenska University Hospital41, Adam Mickiewicz University in Poznań42, University of Connecticut43, Humboldt University of Berlin44, Charité45, University of Fribourg46, University of Kent47, Academy of Sciences of the Czech Republic48, RAND Corporation49, Baylor University50, Virginia Tech51, Northern Illinois University52, Open University53, King's College London54, Stockholm University55, Stanford University56, Karolinska Institutet57, Universidade Federal de Santa Catarina58, University of Tromsø59, DePaul University60, Boğaziçi University61, University of Cologne62, King Abdulaziz City for Science and Technology63, University of Leeds64, Center for Open Science65, University of Virginia66, National Institutes of Health67, University of Southern Indiana68, Autonomous University of Madrid69, Utrecht University70, Tilburg University71, Massey University72, Saint Louis University73, University of California, Davis74, Ghent University75
TL;DR: In response to recommendations to redefine statistical significance to P ≤ 0.005, it is proposed that researchers should transparently report and justify all choices they make when designing a study, including the alpha level.
Abstract: In response to recommendations to redefine statistical significance to P ≤ 0.005, we propose that researchers should transparently report and justify all choices they make when designing a study, including the alpha level.

296 citations


Journal ArticleDOI
TL;DR: The 25-year history of the developmental taxonomy of antisocial behaviour is recapped, concluding that it is standing the test of time in research, and making an impact on policy in early-years prevention and juvenile justice.
Abstract: Male antisocial behavior is concentrated in the adolescent period of the life course, as documented by the curve of crime over age. This article reviews recent evidence regarding the hypothesis that the age-crime curve conceals two groups with different causes. Life-course persistent males show extreme, pervasive, persistent antisocial behavior from early childhood to adulthood. They are hypothesized to be rare, with pathological risk factors and poor life outcomes. In contrast, adolescence-limited males show similar levels of antisocial behavior but primarily during the adolescent stage of development. They are hypothesized to be common and normative, whereas abstainers from offending are rare. This article recaps the taxonomy's 25-year history, concluding that it is standing the test of time in research, and making an impact on policy in early-years prevention and juvenile justice. Research is needed into how the taxonomy relates to neuroscience, health, genetics, and changes in modern crime, including digital crime.

249 citations


Journal ArticleDOI
TL;DR: It is proposed that profound human characteristics, including but not limited to sociality, are acquired at an early age, while social interactions provide key wiring instructions that determine brain development.
Abstract: It has long been assumed that social animals, such as humans, are born with a brain system that has evolved to support social affiliation. However, the evidence does not necessarily support this assumption. Alternatively, social animals can be defined as those who cannot survive alone and rely on members from their group to regulate their ongoing physiology (or allostasis). The rather simple evolutionary constraint of social dependency for survival can be sufficient to make the social environment vitally salient, and to provide the ultimate driving force for socially crafted brain development and learning. In this Perspective, we propose a framework for sociality and specify a set of hypotheses on the mechanisms of social development and underlying neural systems. The theoretical shift proposed here implies that profound human characteristics, including but not limited to sociality, are acquired at an early age, while social interactions provide key wiring instructions that determine brain development. Human infants need a social environment to survive as they rely on caregivers to maintain allostasis. This Perspective proposes that the need of others to regulate physiological changes determines brain development, not only in the social domain.

219 citations


Journal ArticleDOI
TL;DR: Global data from the Gallup World Poll is used to show that happiness does not rise indefinitely with income: globally, income satiation occurs at US$95,000 for life evaluation and US$60,000 to US$75,500 for emotional well-being, but there is substantial variation across world regions.
Abstract: Income is known to be associated with happiness 1 , but debates persist about the exact nature of this relationship 2,3 . Does happiness rise indefinitely with income, or is there a point at which higher incomes no longer lead to greater well-being? We examine this question using data from the Gallup World Poll, a representative sample of over 1.7 million individuals worldwide. Controlling for demographic factors, we use spline regression models to statistically identify points of ‘income satiation’. Globally, we find that satiation occurs at $95,000 for life evaluation and $60,000 to $75,000 for emotional well-being. However, there is substantial variation across world regions, with satiation occurring later in wealthier regions. We also find that in certain parts of the world, incomes beyond satiation are associated with lower life evaluations. These findings on income and happiness have practical and theoretical significance at the individual, institutional and national levels. They point to a degree of happiness adaptation 4,5 and that money influences happiness through the fulfilment of both needs and increasing material desires 6 .

206 citations


Journal ArticleDOI
TL;DR: Science makes a substantial contribution to the economy of developing countries such as Vietnam and its costs must be put into perspective, argues Quan-Hoang Vuong.
Abstract: Science makes a substantial contribution to the economy of developing countries such as Vietnam and its costs must be put into perspective, argues Quan-Hoang Vuong.

203 citations


Journal ArticleDOI
TL;DR: It is shown that individuals and communities can disguise themselves from detection online by standard social network analysis tools through simple changes to their social network connections.
Abstract: The Internet and social media have fuelled enormous interest in social network analysis. New tools continue to be developed and used to analyse our personal connections, with particular emphasis on detecting communities or identifying key individuals in a social network. This raises privacy concerns that are likely to exacerbate in the future. With this in mind, we ask the question ‘Can individuals or groups actively manage their connections to evade social network analysis tools?’ By addressing this question, the general public may better protect their privacy, oppressed activist groups may better conceal their existence and security agencies may better understand how terrorists escape detection. We first study how an individual can evade ‘node centrality’ analysis while minimizing the negative impact that this may have on his or her influence. We prove that an optimal solution to this problem is difficult to compute. Despite this hardness, we demonstrate how even a simple heuristic, whereby attention is restricted to the individual’s immediate neighbourhood, can be surprisingly effective in practice; for example, it could easily disguise Mohamed Atta’s leading position within the World Trade Center terrorist network. We also study how a community can increase the likelihood of being overlooked by community-detection algorithms. We propose a measure of concealment—expressing how well a community is hidden—and use it to demonstrate the effectiveness of a simple heuristic, whereby members of the community either ‘unfriend’ certain other members or ‘befriend’ some non-members in a coordinated effort to camouflage their community. Waniek and colleagues show that individuals and communities can disguise themselves from detection online by standard social network analysis tools through simple changes to their social network connections.

176 citations


Journal ArticleDOI
TL;DR: Consistent evidence is found that remaining in school causally reduced the risk of diabetes and mortality in all specifications, using a large dataset from the UK Biobank.
Abstract: Educated people are generally healthier, have fewer comorbidities and live longer than people with less education1–3. Much of the evidence about the effects of education comes from observational studies, which can be affected by residual confounding. Natural experiments, such as laws that increase the minimum school leaving age, are a potentially more robust source of evidence about the causal effects of education. Previous studies have exploited this natural experiment using population-level administrative data to investigate mortality, and surveys to investigate the effect on morbidity1, 2,4. Here, we add to the evidence using data from a large sample from the UK Biobank 5 . We exploit the raising of the minimum school leaving age in the UK in September 1972 as a natural experiment 6 . We used a regression discontinuity design to investigate the causal effects of remaining in school. We found consistent evidence that remaining in school causally reduced the risk of diabetes and mortality in all specifications. The authors exploit a 1972 policy that increased the minimum school leaving age to investigate the causal effects of staying in school on health. Using a large dataset, they find that remaining in school reduces the risk of diabetes and mortality.

175 citations


Journal ArticleDOI
TL;DR: Fehr and Schurtenberger show that the prevailing evidence supports the view that social norms are causal drivers of human cooperation and explain major cooperation-related regularities.
Abstract: A large literature shares the view that social norms shape human cooperation, but without a clean empirical identification of the relevant norms almost every behaviour can be rationalized as norm driven, thus rendering norms useless as an explanatory construct This raises the question of whether social norms are indeed causal drivers of behaviour and can convincingly explain major cooperation-related regularities Here, we show that the norm of conditional cooperation provides such an explanation, that powerful methods for its empirical identification exist and that social norms have causal effects Norm compliance rests on fundamental human motives (‘social preferences’) that also imply a willingness to punish free-riders, but normative constraints on peer punishment are important for its effectiveness and welfare properties If given the chance, a large majority of people favour the imposition of such constraints through the migration to institutional environments that enable the normative guidance of cooperation and norm enforcement behaviours Fehr and Schurtenberger show that the prevailing evidence supports the view that social norms are causal drivers of human cooperation and explain major cooperation-related regularities Norms also guide peer punishment and people have strong preferences for institutions that support norm formation

Journal ArticleDOI
TL;DR: Video games are increasingly exposing young players to randomized in-game reward mechanisms, purchasable for real money — so-called loot boxes, which may constitute a form of gambling.
Abstract: Video games are increasingly exposing young players to randomized in-game reward mechanisms, purchasable for real money — so-called loot boxes. Do loot boxes constitute a form of gambling?

Journal ArticleDOI
TL;DR: The authors provide a unified explanation of the N400 in a neural network model that avoids the commitments of traditional approaches to meaning in language and connects human language comprehension with recent deep learning approaches to language processing.
Abstract: The N400 component of the event-related brain potential has aroused much interest because it is thought to provide an online measure of meaning processing in the brain. However, the underlying process remains incompletely understood and actively debated. Here we present a computationally explicit account of this process and the emerging representation of sentence meaning. We simulate N400 amplitudes as the change induced by an incoming stimulus in an implicit and probabilistic representation of meaning captured by the hidden unit activation pattern in a neural network model of sentence comprehension, and we propose that the process underlying the N400 also drives implicit learning in the network. The model provides a unified account of 16 distinct findings from the N400 literature and connects human language comprehension with recent deep learning approaches to language processing.

Journal ArticleDOI
TL;DR: Modelling how humans search for rewards under limited search horizons finds evidence that Gaussian process function learning—combined with an optimistic upper confidence bound sampling strategy—provides a robust account of how people use generalization to guide search.
Abstract: From foraging for food to learning complex games, many aspects of human behaviour can be framed as a search problem with a vast space of possible actions. Under finite search horizons, optimal solutions are generally unobtainable. Yet, how do humans navigate vast problem spaces, which require intelligent exploration of unobserved actions? Using various bandit tasks with up to 121 arms, we study how humans search for rewards under limited search horizons, in which the spatial correlation of rewards (in both generated and natural environments) provides traction for generalization. Across various different probabilistic and heuristic models, we find evidence that Gaussian process function learning—combined with an optimistic upper confidence bound sampling strategy—provides a robust account of how people use generalization to guide search. Our modelling results and parameter estimates are recoverable and can be used to simulate human-like performance, providing insights about human behaviour in complex environments.

Journal ArticleDOI
TL;DR: It is shown that task-driven changes to hub and node connectivity increase modularity and improve cognitive performance, and this work finds evidence consistent with a mechanistic model in which connector hubs tune the connectivity of their neighbours to be more modular while allowing for task appropriate information integration across communities, which increases global modularities and cognitive performance.
Abstract: The human brain network is modular-comprised of communities of tightly interconnected nodes1. This network contains local hubs, which have many connections within their own communities, and connector hubs, which have connections diversely distributed across communities2,3. A mechanistic understanding of these hubs and how they support cognition has not been demonstrated. Here, we leveraged individual differences in hub connectivity and cognition. We show that a model of hub connectivity accurately predicts the cognitive performance of 476 individuals in four distinct tasks. Moreover, there is a general optimal network structure for cognitive performance-individuals with diversely connected hubs and consequent modular brain networks exhibit increased cognitive performance, regardless of the task. Critically, we find evidence consistent with a mechanistic model in which connector hubs tune the connectivity of their neighbors to be more modular while allowing for task appropriate information integration across communities, which increases global modularity and cognitive performance.

Journal ArticleDOI
TL;DR: A framework for understanding the best ways to support the three approaches to gender diversity across four interdependent domains is provided — from research teams to the broader disciplines in which they are embedded to research organizations and ultimately to the different societies that shape them through specific gender norms and policies.
Abstract: Gender diversity has the potential to drive scientific discovery and innovation. Here, we distinguish three approaches to gender diversity: diversity in research teams, diversity in research methods and diversity in research questions. While gender diversity is commonly understood to refer only to the gender composition of research teams, fully realizing the potential of diversity for science and innovation also requires attention to the methods employed and questions raised in scientific knowledge-making. We provide a framework for understanding the best ways to support the three approaches to gender diversity across four interdependent domains — from research teams to the broader disciplines in which they are embedded to research organizations and ultimately to the different societies that shape them through specific gender norms and policies. Our analysis demonstrates that realizing the benefits of diversity for science requires careful management of these four interdependent domains. Increasing gender diversity can bring about substantial benefits for research and society. Nielsen et al. propose a framework for increased diversity not only in the composition of teams, but also in research methods and in the questions targeted by research.

Journal ArticleDOI
TL;DR: In this article, the authors applied emerging tools from graph signal processing to examine whether BOLD signals measured at each point in time correspond to complex underlying anatomical networks in 28 individuals performing a perceptual task that probed cognitive flexibility.
Abstract: Cognitive flexibility describes the human ability to switch between modes of mental function to achieve goals. Mental switching is accompanied by transient changes in brain activity, which must occur atop an anatomical architecture that bridges disparate cortical and subcortical regions by underlying white matter tracts. However, an integrated perspective regarding how white matter networks might constrain brain dynamics during cognitive processes requiring flexibility has remained elusive. To address this challenge, we applied emerging tools from graph signal processing to examine whether BOLD signals measured at each point in time correspond to complex underlying anatomical networks in 28 individuals performing a perceptual task that probed cognitive flexibility. We found that the alignment between functional signals and the architecture of the underlying white matter network was associated with greater cognitive flexibility across subjects. By computing a concise measure using multi-modal neuroimaging data, we uncovered an integrated structure-function correlate of human behavior.

Journal ArticleDOI
TL;DR: It is revealed that mobility patterns evolve significantly yet smoothly, and that the number of familiar locations an individual visits at any point is a conserved quantity with a typical size of ~25, which helps improve state-of-the-art modelling of human mobility.
Abstract: Recent seminal works on human mobility have shown that individuals constantly exploit a small set of repeatedly visited locations1–3. A concurrent study has emphasized the explorative nature of human behaviour, showing that the number of visited places grows steadily over time4–7. How to reconcile these seemingly contradicting facts remains an open question. Here, we analyse high-resolution multi-year traces of ~40,000 individuals from 4 datasets and show that this tension vanishes when the long-term evolution of mobility patterns is considered. We reveal that mobility patterns evolve significantly yet smoothly, and that the number of familiar locations an individual visits at any point is a conserved quantity with a typical size of ~25. We use this finding to improve state-of-the-art modelling of human mobility4,8. Furthermore, shifting the attention from aggregated quantities to individual behaviour, we show that the size of an individual’s set of preferred locations correlates with their number of social interactions. This result suggests a connection between the conserved quantity we identify, which as we show cannot be understood purely on the basis of time constraints, and the ‘Dunbar number’9,10 describing a cognitive upper limit to an individual’s number of social relations. We anticipate that our work will spark further research linking the study of human mobility and the cognitive and behavioural sciences. Analysing high-resolution mobility traces from almost 40,000 individuals reveals that people typically revisit a set of 25 familiar locations day-to-day, but that this set evolves over time and is proportional to the size of their social sphere.

Journal ArticleDOI
TL;DR: It is argued, based on comparison with the available information for other members of the genus Homo, that the authors' species developed a new ecological niche, that of the ‘generalist specialist’, and how their species became the last surviving hominin on the planet is argued.
Abstract: Definitions of our species as unique within the hominin clade have tended to focus on differences in capacities for symbolism, language, social networking, technological competence and cognitive development. More recently, however, attention has been turned towards humans' unique ecological plasticity. Here, we critically review the growing archaeological and palaeoenvironmental datasets relating to the Middle-Late Pleistocene (300-12 thousand years ago) dispersal of our species within and beyond Africa. We argue, based on comparison with the available information for other members of the genus Homo, that our species developed a new ecological niche, that of the 'generalist specialist'. Not only did it occupy and utilize a diversity of environments, but it also specialized in its adaptation to some of these environmental extremes. Understanding this ecological niche provides a framework for discussing what it means to be human and how our species became the last surviving hominin on the planet.

Journal ArticleDOI
TL;DR: An alternative approach to the identification of personality types is developed, which is applied to four large data sets comprising more than 1.5 million participants and finds robust evidence for at least four distinct personality types, extending and refining previously suggested typologies.
Abstract: Understanding human personality has been a focus for philosophers and scientists for millennia1 It is now widely accepted that there are about five major personality domains that describe the personality profile of an individual2,3 In contrast to personality traits, the existence of personality types remains extremely controversial4 Despite the various purported personality types described in the literature, small sample sizes and the lack of reproducibility across data sets and methods have led to inconclusive results about personality types5,6 Here we develop an alternative approach to the identification of personality types, which we apply to four large data sets comprising more than 15 million participants We find robust evidence for at least four distinct personality types, extending and refining previously suggested typologies We show that these types appear as a small subset of a much more numerous set of spurious solutions in typical clustering approaches, highlighting principal limitations in the blind application of unsupervised machine learning methods to the analysis of big data

Journal ArticleDOI
TL;DR: Lowering significance thresholds will aggravate several biases caused by significance testing, and statistics reform should involve completely discarding ‘significance’ and the oversimplified reasoning it encourages, instead of just shifting thresholds.
Abstract: To the Editor — Benjamin et al.1 propose to redefine statistical significance with a trichotomy: what was once ‘highly significant’ (P < 0.005) becomes ‘significant’, what was once significant (P < 0.05) becomes ‘suggestive’, and what was ‘nonsignificant’ (P > 0.05) remains nonsignificant. Trichotomization is better than dichotomization, and we agree that P values around 0.05 convey only limited evidence against the tested hypothesis (which is usually a ‘null’ hypothesis of no effect)2. We also agree that P hacking, selective reporting and publication bias “are arguably the bigger problems”1 than false positives arising by chance. Nonetheless, imposing a more stringent significance threshold will aggravate those problems3. Benjamin et al. say that their proposal “should not be used to reject publications of novel findings with 0.005 < P < 0.05”. But rejections due to P > 0.05 will remain, and rejections due to P > 0.005 will now also occur, leading to more intense P hacking and selective reporting, with increased bias in reported effects (because estimates from studies that are selected for having P < 0.005 are usually more inflated than those selected for having P < 0.05)3,4. ‘Significance’ and ‘nonsignificance’ are too often equated with ‘falsity’ and ‘truth’ of hypotheses, reflecting overconfidence about mathematical results and ignoring unmodelled uncertainties2,3,5. We believe that the proposed trichotomy will increase such overconfidence in nonsignificance and thus retard scientific progress6: depending on the context, the increase in false-negative conclusions from using more stringent thresholds may far outweigh in number or cost the false positives so avoided. Worse, lowering the significance threshold will probably aggravate the misinterpretation of P > 0.05 or even P > 0.005 as ‘support’ for the null hypothesis, rather than as mere failure to refute it2,3,7,8. To avoid perpetuating problems caused by discrete decision rules applied to single studies, we argue that presentation decisions should not be based on any P value threshold at all2,3,8. Reliable scientific conclusions require information to be combined from multiple studies and lines of evidence. To allow valid inference from literature syntheses, results must be published regardless of statistical significance, with the P value presented as a continuous summary2,3,8 — for example, as an index of compatibility between the data and the model used to compute P, on a scale of 0 (completely incompatible) to 1 (completely compatible). The P value could even be replaced by a more intuitively scaled evidence measure, such as a likelihood ratio or a surprisal2 –log(P), which are unbounded above and thus difficult to misinterpret as hypothesis probabilities. Interval estimates are also essential, along with an indication of their bias sensitivity2. In sum, lowering significance thresholds will aggravate several biases caused by significance testing3. Thus, while P values can be useful, we think statistics reform should involve completely discarding ‘significance’ and the oversimplified reasoning it encourages2,3,8, instead of just shifting thresholds. Treating P values as continuous indices would emphasize that inferences do not “suddenly assume the mantle of reality”9 once a threshold is crossed. Any study that reports methods and data honestly should be freely accessible regardless of the P value or other statistical results — keeping in mind that selective reporting based on study outcomes is a recipe for misleading conclusions and distorted literature10. ❐

Journal ArticleDOI
TL;DR: By analysing the language of tweets around protests in Baltimore in 2015 and through behavioural laboratory experiments, Dehghani and colleagues find that moralization of protest issues leads to greater support for violence and increased incidence of violent protest.
Abstract: In recent years, protesters in the United States have clashed violently with police and counter-protesters on numerous occasions1-3. Despite widespread media attention, little scientific research has been devoted to understanding this rise in the number of violent protests. We propose that this phenomenon can be understood as a function of an individual's moralization of a cause and the degree to which they believe others in their social network moralize that cause. Using data from the 2015 Baltimore protests, we show that not only did the degree of moral rhetoric used on social media increase on days with violent protests but also that the hourly frequency of morally relevant tweets predicted the future counts of arrest during protests, suggesting an association between moralization and protest violence. To better understand the structure of this association, we ran a series of controlled behavioural experiments demonstrating that people are more likely to endorse a violent protest for a given issue when they moralize the issue; however, this effect is moderated by the degree to which people believe others share their values. We discuss how online social networks may contribute to inflations of protest violence.

Journal ArticleDOI
TL;DR: It is found that, although there is some evidence that non-cognitive skills are associated with improved academic, psychosocial and health outcomes, the evidence is weak and heterogeneous.
Abstract: Success in school and the labour market relies on more than high intelligence. Associations between "non-cognitive" skills in childhood, such as attention, self-regulation, and perseverance, and later outcomes have been widely investigated. In a systematic review of this literature, we screened 9553 publications, reviewed 554 eligible publications, and interpreted results from 222 better quality publications. Better quality publications comprised randomised experimental and quasi-experimental studies (EQIs), and observational studies that made reasonable attempts to control confounding. For academic achievement outcomes there were 26 EQI publications but only 14 were available for meta-analysis with effects ranging from 0.16 to 0.37SD. However, within sub-domains effects were heterogeneous. The 95% prediction interval for literacy was consistent with negative, null and positive effects (-0.13 to 0.79). Similarly heterogeneous findings were observed for psychosocial, cognitive and language, and health outcomes. Funnel plots of EQIs and observational studies showed asymmetric distributions and potential for small study bias. There is some evidence that non-cognitive skills associate with improved outcomes. However, there is potential for small study and publication bias that may over-estimate true effects, and heterogeneity of effect estimates spanned negative, null and positive effects. The quality of evidence from EQIs under-pinning this field is lower than optimal and more than a third of observational studies made little or no attempt to control confounding. Interventions designed to develop children's non-cognitive skills could potentially improve outcomes. The inter-disciplinary researchers interested in these skills should take a more strategic and rigorous approach to determine which interventions are most effective.

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TL;DR: Hilbe et al. synthesize recent theoretical work on zero-determinant and ‘rival’ versus ‘partner’ strategies in social dilemmas and describe the environments under which these contrasting selfish or cooperative strategies emerge in evolution.
Abstract: Reciprocity is a major factor in human social life and accounts for a large part of cooperation in our communities. Direct reciprocity arises when repeated interactions occur between the same individuals. The framework of iterated games formalizes this phenomenon. Despite being introduced more than five decades ago, the concept keeps offering beautiful surprises. Recent theoretical research driven by new mathematical tools has proposed a remarkable dichotomy among the crucial strategies: successful individuals either act as partners or as rivals. Rivals strive for unilateral advantages by applying selfish or extortionate strategies. Partners aim to share the payoff for mutual cooperation, but are ready to fight back when being exploited. Which of these behaviours evolves depends on the environment. Whereas small population sizes and a limited number of rounds favour rivalry, partner strategies are selected when populations are large and relationships stable. Only partners allow for evolution of cooperation, while the rivals' attempt to put themselves first leads to defection.

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TL;DR: The authors found that averaging consensus decisions was substantially more accurate than aggregating the initial independent opinions, and that combining as few as four consensus choices outperformed the wisdom of thousands of individuals.
Abstract: The aggregation of many independent estimates can outperform the most accurate individual judgement 1–3 . This centenarian finding 1,2 , popularly known as the 'wisdom of crowds' 3 , has been applied to problems ranging from the diagnosis of cancer 4 to financial forecasting 5 . It is widely believed that social influence undermines collective wisdom by reducing the diversity of opinions within the crowd. Here, we show that if a large crowd is structured in small independent groups, deliberation and social influence within groups improve the crowd’s collective accuracy. We asked a live crowd (N = 5,180) to respond to general-knowledge questions (for example, "What is the height of the Eiffel Tower?"). Participants first answered individually, then deliberated and made consensus decisions in groups of five, and finally provided revised individual estimates. We found that averaging consensus decisions was substantially more accurate than aggregating the initial independent opinions. Remarkably, combining as few as four consensus choices outperformed the wisdom of thousands of individuals. The collective wisdom of crowds often provides better answers to problems than individual judgements. Here, a large experiment that split a crowd into many small deliberative groups produced better estimates than the average of all answers in the crowd.

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TL;DR: The evolving universe of registered reports is mapped to assess their growth, implementation and shortcomings at journals across scientific disciplines.
Abstract: Registered reports present a substantial departure from traditional publishing models with the goal of enhancing the transparency and credibility of the scientific literature. We map the evolving universe of registered reports to assess their growth, implementation and shortcomings at journals across scientific disciplines.

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TL;DR: High arousal enables young people to better detect salient stimuli and in older people, arousal leads to increased processing of all stimuli, which can be explained by age-related changes in how the locus coeruleus–noradrenaline system interacts with cortical attention networks.
Abstract: In younger adults, arousal amplifies attentional focus to the most salient or goal-relevant information while suppressing other information. A computational model of how the locus coeruleus–noradrenaline system can implement this increased selectivity under arousal and a functional magnetic resonance imaging (fMRI) study comparing how arousal affects younger and older adults’ processing indicate that the amplification of salient stimuli and the suppression of non-salient stimuli are separate processes, with ageing affecting suppression without affecting amplification under arousal. In the fMRI study, arousal increased processing of salient stimuli and decreased processing of non-salient stimuli for younger adults. By contrast, for older adults, arousal increased processing of both low- and high-salience stimuli, generally increasing excitatory responses to visual stimuli. Older adults also showed a decline in locus coeruleus functional connectivity with frontoparietal networks that coordinate attentional selectivity. Thus, among older adults, arousal increases the potential for distraction from non-salient stimuli.

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TL;DR: The results imply that assortative mating involves multiple traits and affects the genomic architecture of loci that are associated with these traits, and that the consequence of mate choice can be detected from a random sample of genomes.
Abstract: Preference for mates with similar phenotypes; that is, assortative mating, is widely observed in humans1–5 and has evolutionary consequences6–8. Under Fisher's classical theory6, assortative mating is predicted to induce a signature in the genome at trait-associated loci that can be detected and quantified. Here, we develop and apply a method to quantify assortative mating on a specific trait by estimating the correlation (θ) between genetic predictors of the trait from single nucleotide polymorphisms on odd- versus even-numbered chromosomes. We show by theory and simulation that the effect of assortative mating can be quantified in the presence of population stratification. We applied this approach to 32 complex traits and diseases using single nucleotide polymorphism data from ~400,000 unrelated individuals of European ancestry. We found significant evidence of assortative mating for height (θ = 3.2%) and educational attainment (θ = 2.7%), both of which were consistent with theoretical predictions. Overall, our results imply that assortative mating involves multiple traits and affects the genomic architecture of loci that are associated with these traits, and that the consequence of mate choice can be detected from a random sample of genomes. A century after being predicted by theory, the authors detect and quantify the genomic signature of assortative mating in ~400,000 contemporary human genomes, and report new genetic evidence for assortative mating on height and educational attainment.

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TL;DR: It is found that ignoring assortativity and the joint distribution of influence and susceptibility leads traditional models to underestimate influence propagation, and empirically motivated influence maximization models that incorporate more realistic features of real-world social networks and predict substantially greater influence propagation compared with traditional models are specified.
Abstract: Social influence maximization models aim to identify the smallest number of influential individuals (seed nodes) that can maximize the diffusion of information or behaviours through a social network. However, while empirical experimental evidence has shown that network assortativity and the joint distribution of influence and susceptibility are important mechanisms shaping social influence, most current influence maximization models do not incorporate these features. Here, we specify a class of empirically motivated influence models and study their implications for influence maximization in six synthetic and six real social networks of varying sizes and structures. We find that ignoring assortativity and the joint distribution of influence and susceptibility leads traditional models to underestimate influence propagation by 21.7% on average, for a fixed seed set size. The traditional models and the empirical types that we specify here also identify substantially different seed sets, with only 19.8% overlap between them. The optimal seeds chosen under empirical influence models are relatively less well-connected and less central nodes, and they have more cohesive, embedded ties with their contacts. Hence, empirically motivated influence models have the potential to identify more realistic sets of key influencers in a social network and inform intervention designs that disseminate information or change attitudes and behaviours.

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TL;DR: Analyses of data from 211 independent, randomized controlled trials show that second-order normative beliefs—community members’ belief that saving energy helps the environment—play a critical role in promoting energy conservation.
Abstract: Sustaining large-scale public goods requires individuals to make environmentally friendly decisions today to benefit future generations1–6 Recent research suggests that second-order normative beliefs are more powerful predictors of behaviour than first-order personal beliefs7,8 We explored the role that second-order normative beliefs—the belief that community members think that saving energy helps the environment—play in curbing energy use We first analysed a data set of 211 independent, randomized controlled trials conducted in 27 US states by Opower, a company that uses comparative information about energy consumption to reduce household energy usage (pooled N = 16,198,595) Building off the finding that the energy savings varied between 081% and 255% across states, we matched this energy use data with a survey that we conducted of over 2,000 individuals in those same states on their first-order personal and second-order normative beliefs We found that second-order normative beliefs predicted energy savings but first-order personal beliefs did not A subsequent pre-registered experiment provides causal evidence for the role of second-order normative beliefs in predicting energy conservation above first-order personal beliefs Our results suggest that second-order normative beliefs play a critical role in promoting energy conservation and have important implications for policymakers concerned with curbing the detrimental consequences of climate change Analyses of data from 211 independent, randomized controlled trials (N = 16,198,595) show that second-order normative beliefs—community members’ belief that saving energy helps the environment—play a critical role in promoting energy conservation