Biology, Society, or Choice: How Do Non-Experts Interpret Explanations of Behaviour?

Explanations for human behaviour can be framed in many different ways, from the social-structural context to the individual motivation down to the neurobiological implementation. We know comparatively little about how people interpret these explanatory framings, and what they infer when one kind of explanation rather than another is made salient. In four experiments, UK general-population volunteers read vignettes describing the same behaviour, but providing explanations framed in different ways. In Study 1, we found that participants grouped explanations into 'biological', 'psychological' and 'sociocultural' clusters. Explanations with different framings were often seen as incompatible with one another, especially when one belonged to the 'biological' cluster and the other did not. In Study 2, we found that exposure to a particular explanatory framing triggered inferences beyond the information given. Specifically, psychological explanations led participants to assume the behaviour was malleable, and biological framings led them to assume it was not. In Studies 3A and 3B, we found that the choice of explanatory framing can affect people's assumptions about effective interventions. For example, presenting a biological explanation increased people's conviction that interventions like drugs would be effective, and decreased their conviction that psychological or socio-political interventions would be effective. These results illuminate the intuitive psychology of explanations, and also potential pitfalls in scientific communication. Framing an explanation in a particular way will often generate inferences in the audience-about what other factors are not causally important, how easy it is to change the behaviour, and what kinds of remedies are worth considering-that the communicator may not have anticipated and might not intend.

Shifting the Level of Selection in Science.

Criteria for recognizing and rewarding scientists primarily focus on individual contributions. This creates a conflict between what is best for scientists' careers and what is best for science. In this article, we show how the theory of multilevel selection provides conceptual tools for modifying incentives to better align individual and collective interests. A core principle is the need to account for indirect effects by shifting the level at which selection operates from individuals to the groups in which individuals are embedded. This principle is used in several fields to improve collective outcomes, including animal husbandry, team sports, and professional organizations. Shifting the level of selection has the potential to ameliorate several problems in contemporary science, including accounting for scientists' diverse contributions to knowledge generation, reducing individual-level competition, and promoting specialization and team science. We discuss the difficulties associated with shifting the level of selection and outline directions for future development in this domain.

An evolutionary model of sensitive periods when the reliability of cues varies across ontogeny.

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.

Sensitive periods, but not critical periods, evolve in a fluctuating environment: a model of incremental development.

Sensitive periods, during which the impact of experience on phenotype is larger than in other periods, exist in all classes of organisms, yet little is known about their evolution. Recent mathematical modelling has explored the conditions in which natural selection favours sensitive periods. These models have assumed that the environment is stable across ontogeny or that organisms can develop phenotypes instantaneously at any age. Neither assumption generally holds. Here, we present a model in which organisms gradually tailor their phenotypes to an environment that fluctuates across ontogeny, while receiving cost-free, imperfect cues to the current environmental state. We vary the rate of environmental change, the reliability of cues and the duration of adulthood relative to ontogeny. We use stochastic dynamic programming to compute optimal policies. From these policies, we simulate levels of plasticity across ontogeny and obtain mature phenotypes. Our results show that sensitive periods can occur at the onset, midway through and even towards the end of ontogeny. In contrast with models assuming stable environments, organisms always retain residual plasticity late in ontogeny. We conclude that critical periods, after which plasticity is zero, are unlikely to be favoured in environments that fluctuate across ontogeny.

Honest signaling in academic publishing.

Academic journals provide a key quality-control mechanism in science. Yet, information asymmetries and conflicts of interests incentivize scientists to deceive journals about the quality of their research. How can honesty be ensured, despite incentives for deception? Here, we address this question by applying the theory of honest signaling to the publication process. Our models demonstrate that several mechanisms can ensure honest journal submission, including differential benefits, differential costs, and costs to resubmitting rejected papers. Without submission costs, scientists benefit from submitting all papers to high-ranking journals, unless papers can only be submitted a limited number of times. Counterintuitively, our analysis implies that inefficiencies in academic publishing (e.g., arbitrary formatting requirements, long review times) can serve a function by disincentivizing scientists from submitting low-quality work to high-ranking journals. Our models provide simple, powerful tools for understanding how to promote honest paper submission in academic publishing.

Integration involves a trade-off between fertility and status for World War II evacuees.

Understanding how refugees integrate into host societies has broad implications for researchers interested in intergroup conflict and for governments concerned with promoting social cohesion. Using detailed records tracking the movements and life histories of Finnish evacuees during World War II, we find that evacuees who intermarry are more likely to be educated, work in professional occupations, marry someone higher in social status and remain in the host community. Evacuees who intermarry before the war have fewer children, whereas those who marry into their host community after the war have more children. These results indicate that life-history and assimilation outcomes depend on key differences between pre-war environments-when migrants are living in their own communities-and post-war environments-when migrants are living in the host community. Overall, this suggests that integration involves a trade-off between reproduction and status such that evacuees who integrate gain social status, whereas those who maintain stronger bonds with their natal communities have higher fertility. We discuss these results within the framework of social capital, intergroup conflict and life-history theory and suggest how they can inform our understanding of evolutionary adaptations that affect tribalism.

Enriching behavioral ecology with reinforcement learning methods.

This article focuses on the division of labor between evolution and development in solving sequential, state-dependent decision problems. Currently, behavioral ecologists tend to use dynamic programming methods to study such problems. These methods are successful at predicting animal behavior in a variety of contexts. However, they depend on a distinct set of assumptions. Here, we argue that behavioral ecology will benefit from drawing more than it currently does on a complementary collection of tools, called reinforcement learning methods. These methods allow for the study of behavior in highly complex environments, which conventional dynamic programming methods do not feasibly address. In addition, reinforcement learning methods are well-suited to studying how biological mechanisms solve developmental and learning problems. For instance, we can use them to study simple rules that perform well in complex environments. Or to investigate under what conditions natural selection favors fixed, non-plastic traits (which do not vary across individuals), cue-driven-switch plasticity (innate instructions for adaptive behavioral development based on experience), or developmental selection (the incremental acquisition of adaptive behavior based on experience). If natural selection favors developmental selection, which includes learning from environmental feedback, we can also make predictions about the design of reward systems. Our paper is written in an accessible manner and for a broad audience, though we believe some novel insights can be drawn from our discussion. We hope our paper will help advance the emerging bridge connecting the fields of behavioral ecology and reinforcement learning.

The evolution of sensitive periods in a model of incremental development.

Sensitive periods, in which experience shapes phenotypic development to a larger extent than other periods, are widespread in nature. Despite a recent focus on neural-physiological explanation, few formal models have examined the evolutionary selection pressures that result in developmental mechanisms that produce sensitive periods. Here, we present such a model. We model development as a specialization process during which individuals incrementally adapt to local environmental conditions, while receiving a constant stream of cost-free, imperfect cues to the environmental state. We compute optimal developmental programmes across a range of ecological conditions and use these programmes to simulate developmental trajectories and obtain distributions of mature phenotypes. We highlight four main results. First, matching the empirical record, sensitive periods often result from experience or from a combination of age and experience, but rarely from age alone. Second, individual differences in sensitive periods emerge as a result of stochasticity in cues: individuals who obtain more consistent cue sets lose their plasticity at faster rates. Third, in some cases, experience shapes phenotypes only at a later life stage (lagged effects). Fourth, individuals might perseverate along developmental trajectories despite accumulating evidence suggesting the alternate trajectory is more likely to match the ecology.

A mathematical model of the evolution of individual differences in developmental plasticity arising through parental bet-hedging.

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.

Explaining group-level traits requires distinguishing process from product.

Smaldino is right to argue that we need a richer theory of group-level traits. He is wrong, however, in limiting group-level traits to units of cultural selection, which require explanations based on group selection. Traits are best understood when explanations focus on both process (i.e., selection) and product (i.e., adaptation). This approach can distinguish group-level traits that arise through within-group processes from those that arise through between-group processes.

Bridging developmental systems theory and evolutionary psychology using dynamic optimization.

Interactions between evolutionary psychologists and developmental systems theorists have been largely antagonistic. This is unfortunate because potential synergies between the two approaches remain unexplored. This article presents a method that may help to bridge the divide, and that has proven fruitful in biology: dynamic optimization. Dynamic optimization integrates developmental systems theorists' focus on dynamics and contingency with the 'design stance' of evolutionary psychology. It provides a theoretical framework as well as a set of tools for exploring the properties of developmental systems that natural selection might favor, given particular evolutionary ecologies. We also discuss limitations of the approach.

Balancing sampling and specialization: an adaptationist model of incremental development.

Development is typically a constructive process, in which phenotypes incrementally adapt to local ecologies. Here, we present a novel model in which natural selection shapes developmental systems based on the evolutionary ecology, and these systems adaptively guide phenotypic development. We assume that phenotypic construction is incremental and trades off with sampling cues to the environmental state. We computed the optimal developmental programmes across a range of evolutionary ecological conditions. Using these programmes, we simulated distributions of mature phenotypes. Our results show that organisms sample the environment most extensively when cues are moderately, not highly, informative. When the developmental programme relies heavily on sampling, individuals transition from sampling to specialization at different times in ontogeny, depending on the consistency of their sampled cue set; this finding suggests that stochastic sampling may result in individual differences in plasticity itself. In addition, we find that different selection pressures may favour similar developmental mechanisms, and that organisms may incorrectly calibrate development despite stable ontogenetic environments. We hope our model will stimulate adaptationist research on the constructive processes guiding development.

Two wrongs don't make a right: the initial viability of different assessment rules in the evolution of indirect reciprocity.

Indirect reciprocity models are meant to correspond to simple moral systems, in which individuals assess the interactions of third parties in order to condition their cooperative behavior. Despite the staggering number of possible assessment rules in even the simplest of these models, previous research suggests that only a handful are evolutionarily stable against invasion by free riders. These successful assessment rules fall into two categories, one which positively judges miscreants when they refuse to help other miscreants, the other which does not. Previous research has not, however, demonstrated that all of these rules can invade an asocial population--a requirement for a complete theory of social evolution. Here, I present a general analytical model of indirect reciprocity and show that the class of assessment rules which positively judges a refusal to help scofflaws cannot invade a population of defectors, whereas the other class can. When rare, assessment rules which positively judge a refusal to help bad people produce a poor correlation between reputation and behavior. It is this correlation that generates the assortment crucial in sustaining cooperation through indirect reciprocity. Only assessment rules that require good deeds to achieve a good reputation guarantee a strong correlation between behavior and reputation.

Individual Differences in Developmental Plasticity May Result From Stochastic Sampling.

The ability to adjust developmental trajectories based on experience is widespread in nature, including in humans. This plasticity is often adaptive, tailoring individuals to their local environment. However, it is less clear why some individuals are more sensitive to environmental influences than others. Explanations include differences in genes and differences in prior experiences. In this article, we present a novel hypothesis in the latter category. In some developmental domains, individuals must learn about the state of their environment before adapting accordingly. Because sampling environmental cues is a stochastic process, some individuals may receive a homogeneous sample, resulting in a confident estimate about the state of the world-these individuals specialize early. Other individuals may receive a heterogeneous, uninformative set of cues-those individuals will keep sampling. As a consequence, individual variation in plasticity may result from different degrees of confidence about the state of the environment. After developing the hypothesis, we conclude by discussing three empirical predictions.

Development: evolutionary ecology's midwife.

We agree with Henrich et al. that documenting cultural universality and variability provides an indispensable window into human nature. We want to stress the mediating role development plays between evolution and culture. Moving beyond the mere documentation of universality or variability, developmental approaches can provide mechanistic explanations, linking ecology to phenotype. Combining phylogeny and adaptationism, evolutionary approaches can explain the properties of developmental systems.

Indirect reciprocity can stabilize cooperation without the second-order free rider problem.

Models of large-scale human cooperation take two forms. 'Indirect reciprocity' occurs when individuals help others in order to uphold a reputation and so be included in future cooperation. In 'collective action', individuals engage in costly behaviour that benefits the group as a whole. Although the evolution of indirect reciprocity is theoretically plausible, there is no consensus about how collective action evolves. Evidence suggests that punishing free riders can maintain cooperation, but why individuals should engage in costly punishment is unclear. Solutions to this 'second-order free rider problem' include meta-punishment, mutation, conformism, signalling and group-selection. The threat of exclusion from indirect reciprocity can sustain collective action in the laboratory. Here, we show that such exclusion is evolutionarily stable, providing an incentive to engage in costly cooperation, while avoiding the second-order free rider problem because punishers can withhold help from free riders without damaging their reputations. However, we also show that such a strategy cannot invade a population in which indirect reciprocity is not linked to collective action, thus leaving unexplained how collective action arises.

A tale of two defectors: the importance of standing for evolution of indirect reciprocity.

Indirect reciprocity occurs when the cooperative behavior between two individuals is contingent on their previous behavior toward others. Previous theoretical analysis indicates that indirect reciprocity can evolve if individuals use an image-scoring strategy. In this paper, we show that, when errors are added, indirect reciprocity cannot be based on an image-scoring strategy. However, if individuals use a standing strategy, then cooperation through indirect reciprocity is evolutionarily stable. These two strategies differ with respect to the information to which they attend. While image-scoring strategies only need attend to the actions of others, standing strategies also require information about intent. We speculate that this difference may shed light on the evolvability of indirect reciprocity. Additionally, we show that systems of indirect reciprocity are highly sensitive to the availability of information. Finally, we present a model which shows that if indirect reciprocity were to evolve, selection should also favor trusting behavior in relations between strangers.