The prevalence of divorce in both parental and grandparental generations has led to a rise in the number of children who now have families that include both biological and step-grandparents. Despite the thorough examination of biological grandparents’ contributions in the recent literature, there remains a scarcity of studies focusing on the investment of step-grandparents. Using population-based data from a sample of 2494 parents in Germany, we assessed grandparental investment through financial support and assistance with childcare of grandparents (N = 4238) and step-grandparents (N = 486). The study revealed that step-grandparents provided lower levels of investment in their grandchildren compared with biological grandparents. Furthermore, the study identified that a longer duration of co-residence between step-grandparents and parents earlier in life did not correspond to an increase or decrease in step-grandparental investment. However, investment by separated biological grandparents increased with the increasing length of co-residence with parents. In line with the scarce literature on step-grandparental investment, these findings indicate that mating effort may be the most important motivation for step-grandparental investment.

The standard theory of rationality posits that agents order preferences according to average utilities associated with different choices. Expected utility theory has repeatedly failed as a predictive theory, as reflected in a growing literature in behavioural economics. Evolutionary theorists have suggested that seemingly irrational behaviours in contemporary contexts may have once served important functions, but existing work linking fitness and choice has not adequately addressed the challenges of constructing an evolutionary theory of decision making. In particular, fitness itself is not a reasonable metric for decision making since its timescale exceeds the lifespan of the decision-maker. Consequently, organisms use proximate systems that work on appropriate timescales and are amenable to feedback and learning. We develop an evolutionary principal–agent model in which individuals utilize a set of proximal choice variables to account for the non-linear dependence of these variables on consumption. While this is insufficient to maximize fitness in the presence of environmental stochasticity, maximum fitness can be achieved by adopting pessimistic probability weightings compatible with the rank-dependent expected utility family of choice models. In particular, pessimistic probability weighting emerges naturally in an evolutionary framework because of extreme intolerance to zeros in multiplicative growth processes.

The transition to sedentary agricultural societies in northern China fuelled considerable demographic growth from 5000 to 2000 BC. In this article, we draw together archaeobotanical, zooarchaeological and bioarchaeological data and explore the relationship between several aspects of this transition, with an emphasis on the millet-farming productivity during the Yangshao period and how it facilitated changes in animal husbandry and consolidation of sedentism. We place the period of domestication (the evolution of non-shattering, initial grain size increase and panicle development) between 8300 and 4300 BC. The domestication and post-domestication of foxtail (Setaria italica) and broomcorn (Panicum miliaceum) millet increased their productivity substantially, with much greater rate of change than for rice (Oryza sativa). However, millets are significantly less productive per hectare than wet rice farming, a point reflected in the greater geographical expanse of northern Neolithic millet cultures (5000–3000 BC) in comparison with their Yangtze rice-growing counterparts. The domestication of pigs in the Yellow River region is evidenced by changes in their morphology after 6000 BC, and a transition to a millet-based diet c. 4500–3500 BC. Genetic data and isotopic data from dogs indicate a similar dietary transition from 6000 to 4000 BC, leading to new starch-consuming dog breeds. Significant population increase associated with agricultural transitions arose predominately from the improvement of these crops and animals following domestication, leading to the formation of the first proto-urban centres and the demic-diffusion of millet agriculture beyond central northern China between 4300–2000 BC.

Evolutionary perspectives on menopause have focused on explaining why early reproductive cessation in females has emerged and why it is rare throughout the animal kingdom, but less attention has been given to exploring patterns of diversity in age at natural menopause. In this paper, we aim to generate new hypotheses for understanding human patterns of diversity in this trait, defined as age at final menstrual period. To do so, we develop a multilevel, interdisciplinary framework, combining proximate, physiological understandings of ovarian ageing with ultimate, evolutionary perspectives on ageing. We begin by reviewing known patterns of diversity in age at natural menopause in humans, and highlight issues in how menopause is currently defined and measured. Second, we consider together ultimate explanations of menopause timing and proximate understandings of ovarian ageing. We find that ovarian ageing is highly constrained by ageing of the follicle – the somatic structure containing the oocyte – suggesting that menopause timing might be best understood as a by-product of ageing rather than a facultative adaptation. Third, we investigate whether the determinants of somatic senescence also underpin menopause timing. We show that diversity in age at menopause can be, at least partly, explained by the genetic, ecological and life-history determinants of somatic ageing. The public health implications of rethinking menopause as the by-product rather than the catalyst of biological ageing are discussed.

Gender role ideology, i.e. beliefs about how genders should behave, is shaped by social learning. Accordingly, if perceptions about the beliefs of others are inaccurate this may impact trajectories of cultural change. Consistent with this premise, recent studies report evidence of a tendency to overestimate peer support for inequitable gender norms, especially among men, and that correcting apparent ‘norm misperception’ promotes transitions to relatively egalitarian beliefs. However, supporting evidence largely relies on self-report measures vulnerable to social desirability bias. Consequently, observed patterns may reflect researcher measurement error rather than participant misperception. Addressing this shortcoming, we examine men's gender role ideology using both conventional self-reported and a novel wife-reported measure of men's beliefs in an urbanising community in Tanzania. We confirm that participants overestimate peer support for gender inequity. However, the latter measure, which we argue more accurately captures men's true beliefs, implies that this tendency is relatively modest in magnitude and scope. Overestimation was most pronounced among men holding relatively inequitable beliefs, consistent with misperception of peer beliefs reinforcing inequitable norms. Furthermore, older and poorly educated men overestimated peer support for gender inequity the most, suggesting that outdated and limited social information contribute to norm misperception in this context.

While humans are highly cooperative, they can also behave spitefully. Yet spite remains understudied. Spite can be normatively driven and while previous experiments have found some evidence that cooperation and punishment may spread via social learning, no experiments have considered the social transmission of spiteful behaviour. Here we present an online experiment where, following an opportunity to earn wealth, we asked participants to choose an action towards an anonymous partner across a full spectrum of social behaviour, from spite to altruism. In accordance with cultural evolutionary theory, participants were presented with social information that varied in source and content. Across six conditions, we informed participants that either the majority or the highest earner had chosen to behave spitefully, neutrally or altruistically. We found an overall tendency towards altruism, but at lower levels among those exposed to spite compared with altruism. We found no difference between social information that came from the majority or the highest earner. Exploratory analysis revealed that participants’ earnings negatively correlated with altruistic behaviour. Our results contrast with previous literature that report high rates of spite in experimental samples and a greater propensity for individuals to copy successful individuals over the majority.

Hunter–gatherer populations underwent a mass extinction in the Neolithic, and in present times face challenges such as explicit sedentarisation policies. An exception is in Nepal, where the nomadic Raute people receive monthly governmental individual payments. One consequence of the money transfers has been a significant increase in alcohol consumption, with nearly all individuals drinking industrially produced alcohol. Here we investigate the Raute demography based on a full census of 144 individuals. We show that the Raute exhibit the short life expectancies typical of other hunter–gatherer populations from Africa, Asia and America. Bayesian survival trajectory analysis demonstrated that heavy drinking by either parent substantially reduces offspring survival to age 15. Bayesian regressions revealed a significant effect of heavy drinking on maternal fertility by decreasing the number of living children and reducing the proportion of live children at the end of maternal reproductive life. Although the absence of data prior to monetary support precludes a direct assessment of long-term demographic trends, relatively stable population sizes over the last decades and a fertility rate close to the replacement rate rule out an imminent population crash. Further studies are required to elucidate the Rautes’ origins and relationship with other nomadic people in the region.

Models of frequency-dependent social learning posit that individuals respond to the commonality of behaviours without additional variables modifying this. Such strategies bring important trade-offs, e.g. conformity is beneficial when observing people facing the same task but harmful when observing those facing a different task. Instead of rigidly responding to frequencies, however, social learners might modulate their response given additional information. To see, we ran an incentivised experiment where participants played either a game against nature or a coordination game. There were three types of information: (a) choice frequencies in a group of demonstrators; (b) an indication of whether these demonstrators learned in a similar or different environment; and (c) an indication about the reliability of this similarity information. Similarity information was either reliably correct, uninformative or reliably incorrect, where reliably correct and reliably incorrect treatments provided participants with equivalent earning opportunities. Participants adjusted their decision-making to all three types of information. Adjustments, however, were asymmetric, with participants doing especially well when conforming to demonstrators who were reliably similar to them. The overall response, however, was more fluid and complex than this one case. This flexibility should attenuate the trade-offs commonly assumed to shape the evolution of frequency-dependent social learning strategies.

Loanword analysis is a unique contribution of historical linguistics to our understanding of prehistoric cultural interfaces. As language reflects the lives of its speakers, the substantiation of loanwords draws on the composite evidence from linguistic as well as auxiliary data from archaeology and genetics through triangulation. The Bronze Age of Central Asia is in principle linguistically mute, but a host of recent independent observations that tie languages, cultures and genetics together in various ways invites a comprehensive reassessment of six highly diagnostic loanwords (‘seven’, ‘name/fame’, ‘sister-in-law’, ‘honey’, ‘metal’ and ‘horse’) that are associated with the Bronze Age. Moreover, they are shared between Indo-European, Uralic, Turkic and sometimes Old Chinese. The successful identification of the interfaces for these loanwords can help settle longstanding debates on languages, migrations and the items themselves. Each item is analysed using the comparative method with reference to the archaeological record to assess the plausibility of a transfer. I argue that the six items can be dated to have entered Central and East Asian languages from immigrant Indo-European languages spoken in the Afanasievo and Andronovo cultures, including a novel source for the ‘horse’ in Old Chinese.

Knowledge and behaviour are transmitted from one individual to another through social learning and eventually disseminated across the population. People often learn useful behaviours socially through selective bias rather than random selection of targets. Prestige bias, or the tendency to selectively imitate prestigious individuals, has been considered an important factor in influencing human behaviour. Although its importance in human society and culture has been recognised, the formulation of prestige bias is less developed than that of other social learning biases. To examine the effects of prestige bias on cultural evolution theoretically, it is imperative to formulate prestige and investigate its basic properties. We reviewed two definitions: one based on first-order cues, such as the demonstrator's appearance and job title, and the other based on second-order cues, such as people's behaviour towards the demonstrator (e.g. people increasingly pay attention to prestigious individuals). This study builds a computational model of prestige bias based on these two definitions and compares the cultural evolutionary dynamics they generate. Our models demonstrate the importance of distinguishing between the two types of formalisation, because they can have different influences on cultural evolution.

During infectious disease outbreaks, individuals may adopt protective measures like vaccination and physical distancing in response to awareness of disease burden. Prior work showed how feedbacks between epidemic intensity and awareness-based behaviour shape disease dynamics. These models often overlook social divisions, where population subgroups may be disproportionately impacted by a disease and more responsive to the effects of disease within their group. We develop a compartmental model of disease transmission and awareness-based protective behaviour in a population split into two groups to explore the impacts of awareness separation (relatively greater in- vs. out-group awareness of epidemic severity) and mixing separation (relatively greater in- vs. out-group contact rates). Using simulations, we show that groups that are more separated in awareness have smaller differences in mortality. Fatigue (i.e. abandonment of protective measures over time) can drive additional infection waves that can even exceed the size of the initial wave, particularly if uniform awareness drives early protection in one group, leaving that group largely susceptible to future infection. Counterintuitively, vaccine or infection-acquired immunity that is more protective against transmission and mortality may indirectly lead to more infections by reducing perceived risk of infection and therefore vaccine uptake. Awareness-based protective behaviour, including awareness separation, can fundamentally alter disease dynamics.

Social media summary: Depending on group division, behaviour based on perceived risk can change epidemic dynamics & produce large later waves.

The human sciences should seek generalisations wherever possible. For ethical and scientific reasons, it is desirable to sample more broadly than ‘Western, educated, industrialised, rich, and democratic’ (WEIRD) societies. However, restricting the target population is sometimes necessary; for example, young children should not be recruited for studies on elderly care. Under which conditions is unrestricted sampling desirable or undesirable? Here, we use causal diagrams to clarify the structural features of measurement error bias and target population restriction bias (or ‘selection restriction’), focusing on threats to valid causal inference that arise in comparative cultural research. We define any study exhibiting such biases, or confounding biases, as weird (wrongly estimated inferences owing to inappropriate restriction and distortion). We explain why statistical tests such as configural, metric and scalar invariance cannot address the structural biases of weird studies. Overall, we examine how the workflows for causal inference provide the necessary preflight checklists for ambitious, effective and safe comparative cultural research.

The analysis of ‘moderation’, ‘interaction’, ‘mediation’ and ‘longitudinal growth’ is widespread in the human sciences, yet subject to confusion. To clarify these concepts, it is essential to state causal estimands, which requires the specification of counterfactual contrasts for a target population on an appropriate scale. Once causal estimands are defined, we must consider their identification. I employ causal directed acyclic graphs and single world intervention graphs to elucidate identification workflows. I show that when multiple treatments exist, common methods for statistical inference, such as multi-level regressions and statistical structural equation models, cannot typically recover the causal quantities we seek. By properly framing and addressing causal questions of interaction, mediation, and time-varying treatments, we can expose the limitations of popular methods and guide researchers to a clearer understanding of the causal questions that animate our interests.

Causal inference requires contrasting counterfactual states under specified interventions. Obtaining these contrasts from data depends on explicit assumptions and careful, multi-step workflows. Causal diagrams are crucial for clarifying the identifiability of counterfactual contrasts from data. Here, I explain how to use causal directed acyclic graphs (DAGs) to determine if and how causal effects can be identified from non-experimental observational data, offering practical reporting tips and suggestions to avoid common pitfalls.

Causal inference lies at the core of many scientific endeavours. Yet answering causal questions is challenging, especially when studying culture as a causal force. Against this backdrop, this paper reviews research designs and statistical tools that can be used – together with strong theory and knowledge about the context of study – to identify the causal impact of culture on outcomes of interest. We especially discuss how overlooked strategies in cultural evolutionary studies can allow one to approximate an ideal experiment wherein culture is randomly assigned to individuals or entire groups (instrumental variables, regression discontinuity design, and epidemiological approach). In doing so, we also review the potential outcome framework as a tool to engage in causal reasoning in the cultural evolutionary field.

Psychological and cultural evolutionary accounts of human sociality propose that beliefs in punitive and monitoring gods that care about moral norms facilitate cooperation. While there is some evidence to suggest that belief in supernatural punishment and monitoring generally induce cooperative behaviour, the effect of a deity's explicitly postulated moral concerns on cooperation remains unclear. Here, we report a pre-registered set of analyses to assess whether perceiving a locally relevant deity as moralistic predicts cooperative play in two permutations of two economic games using data from up to 15 diverse field sites. Across games, results suggest that gods’ moral concerns do not play a direct, cross-culturally reliable role in motivating cooperative behaviour. The study contributes substantially to the current literature by testing a central hypothesis in the evolutionary and cognitive science of religion with a large and culturally diverse dataset using behavioural and ethnographically rich methods.