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Children learn a lot from others, but the effectiveness of their social learning depends on the reliability of others' help. How do children adapt their future learning decisions based on the past reliability of receiving help? In two experiments, 4- to 6-year-olds (N = 60 each) interacted with a researcher who either followed through on promised help (Reliable condition) or failed to do so (Unreliable condition). Experiment 1 was inconclusive. However, with an improved design, Experiment 2 found that children in the Unreliable condition were more likely to forego a harder but more rewarding puzzle as their next task and choose an easier, less rewarding puzzle instead compared to those in the Reliable condition. Such decisions, while seemingly maladaptive at face value, likely reflect an adaptive response to the low likelihood of receiving help. These results extend our understanding of social learning across diverse ecological contexts.

Children vary in the extent to which their development is shaped by particular experiences (e.g. maltreatment, social support). This variation raises a question: Is there no single level of plasticity that maximizes biological fitness? One influential hypothesis states that when different levels of plasticity are optimal in different environmental states and the environment fluctuates unpredictably, natural selection may favor parents producing offspring with varying levels of plasticity. The current article presents a mathematical model assessing the logic of this hypothesis--specifically, it examines what conditions are required for natural selection to favor parents to bet-hedge by varying their offspring's plasticity. Consistent with existing theory from biology, results show that between-individual variation in plasticity cannot evolve when the environment only varies across space. If, however, the environment varies across time, selection can favor differential plasticity, provided fitness effects are large (i.e. variation in individuals' plasticity is correlated with substantial variation in fitness). Our model also generates a novel restriction: Differential plasticity only evolves when the cost of being mismatched to the environment exceeds the benefits of being well matched. Based on mechanistic considerations, we argue that bet-hedging by varying offspring plasticity, if it were to evolve, would be more likely instantiated via epigenetic mechanisms (e.g. pre- or postnatal developmental programming) than genetic ones (e.g. mating with genetically diverse partners). Our model suggests novel avenues for testing the bet-hedging hypothesis of differential plasticity, including empirical predictions and relevant measures. We also discuss several ways in which future work might extend our model.

A casual look at the literature in social cognition reveals a vast collection of biases, errors, violations of rational choice, and failures to maximize utility. One is tempted to draw the conclusion that the human mind is woefully muddled. We present a three-category evolutionary taxonomy of evidence of biases: biases are (a) heuristics, (b) error management effects, or (c) experimental artifacts. We conclude that much of the research on cognitive biases can be profitably reframed and understood in evolutionary terms. An adaptationist perspective suggests that the mind is remarkably well designed for important problems of survival and reproduction, and not fundamentally irrational. Our analysis is not an apologia intended to place the rational mind on a pedestal for admiration. Rather, it promises practical outcomes including a clearer view of the architecture of systems for judgment and decision making, and exposure of clashes between adaptations designed for the ancestral past and the demands of the present.

In the wake of the replication crisis, there have been calls to increase the clarity and precision of theory in the social sciences. Here, we argue that the effects of these calls may be limited due to incentives favoring ambiguous theory. Intentionally or not, scientists can exploit theoretical ambiguities to make support for a claim appear stronger than it is. Practices include theory stretching, interpreting an ambiguous claim more expansively to absorb data outside of the scope of the original claim, and post-hoc precision, interpreting an ambiguous claim more narrowly so it appears more precisely aligned with the data. These practices lead to the overestimation of evidence for the original claim and create the appearance of consistent support and progressive research programs, which may in turn be rewarded by journals, funding agencies, and hiring committees. Selection for ambiguous research can occur even when scientists act in good faith. Although ambiguity might be inevitable or even useful in the early stages of theory construction, scientists should aim for increased clarity as knowledge advances. Science benefits from transparently communicating about known ambiguities. To attain transparency about ambiguity, we provide a set of recommendations for authors, reviewers, and journals. We conclude with suggestions for research on how scientists use strategic ambiguity to advance their careers and the ways in which norms, incentives, and practices favor strategic ambiguity. Our paper ends with a simple mathematical model exploring the conditions in which high-ambiguity theories are favored over low-ambiguity theories, providing a basis for future analyses. Highlights: Current incentives favor strategic ambiguity (i.e., deploying ambiguity to achieve self-interested goals). Researchers exploit the flexibility that theoretical ambiguity affords, intentionally or not, using practices like theory stretching and post-hoc precision, which result in the overestimation of evidentiary support for theoretical claims. Scientists should aim for transparency when ambiguity is unavoidable in the short run and aim for increased clarity in the long run. We provide recommendations for authors, editors, and funders on how to restructure incentives to disfavor strategic ambiguity and favor clarity. [ABSTRACT FROM AUTHOR]

Sensitive periods are widespread in nature, but their evolution is not well understood. Recent mathematical modeling has illuminated the conditions favoring the evolution of sensitive periods early in ontogeny. However, sensitive periods also exist at later stages of ontogeny, such as adolescence. Here, we present a mathematical model that explores the conditions that favor sensitive periods at later developmental stages. In our model, organisms use environmental cues to incrementally construct a phenotype that matches their environment. Unlike in previous models, the reliability of cues varies across ontogeny. We use stochastic dynamic programming to compute optimal policies for a range of evolutionary ecologies and then simulate developmental trajectories to obtain mature phenotypes. We measure changes in plasticity across ontogeny using study paradigms inspired by empirical research: adoption and cross-fostering. Our results show that sensitive periods only evolve later in ontogeny if the reliability of cues increases across ontogeny. The onset, duration, and offset of sensitive periods—and the magnitude of plasticity—depend on the specific parameter settings. If the reliability of cues decreases across ontogeny, sensitive periods are favored only early in ontogeny. These results are robust across different paradigms suggesting that empirical findings might be comparable despite different experimental designs. [ABSTRACT FROM AUTHOR]

Sensitive periods, in which experiences have a large impact on phenotypic development, are most common early in ontogeny. Yet, they may also occur at later ontogenetic stages, such as adolescence. At present, however, we know little about why natural selection favours sensitive periods for some traits early in ontogeny and for others later in ontogeny. This article synthesizes recent mathematical models and empirical studies that explore sensitive periods beyond early ontogeny. Across mathematical models, we observe two general patterns. First, sensitive periods emerge beyond early ontogeny when an organism's uncertainty about the environment‐phenotype fit increases at later developmental stages. Second, sensitive periods emerge beyond early ontogeny when cues at later stages reduce this uncertainty more than earlier cues do. In the empirical literature, we observe that traits showing sensitive periods beyond early ontogeny tend to be social traits, particularly among mammals. Connecting theory to data, we hypothesize that mammals have evolved to expect reliable information from peers in adolescence to reduce uncertainty about the current and future social environment (e.g. social dominance, mate value). Finally, we highlight current gaps in our understanding and suggest future directions for strengthening bridges between empirical and theoretical studies of sensitive periods. Ultimately, we hope our synthesis will contribute towards an integrative science of sensitive periods across the biological and the social sciences. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]