John Andrew Bunce

Objectives: Comparing children's growth across the world and at different moments in history can yield insight into both health challenges and healthy morphological variation in humans. A difficulty of such comparative analyses is that, in marginalized populations, there are often logistical complications to obtaining repeat measures of individual children's height and weight. The problem is even more acute for historical populations: bioarcheological datasets comprise single measures of individuals at death. Additionally, for both contemporary and historical populations, there is often non‐trivial uncertainty about children's ages. Both of these factors complicate estimation of growth trajectories. Here we evaluate the degree to which we can accurately estimate a population‐mean growth trajectory using only a small number of (randomly) uncertain measurements, like those that compose many contemporary and bioarcheological datasets. Materials and Methods: We recently derived a causal model of human growth from fundamental principles of metabolism and allometry, permitting exploration of genetic and environmental contributions to children's growth. Here, we fit this model in a Bayesian framework to simulated cross‐sectional and longitudinal datasets of varying size, where age is uncertain. Results: For large‐scale comparisons, reasonably accurate population‐mean growth trajectories may be obtained from single height measures of 100 children of a given sex and a range of ages. However, detailed analyses of pubertal growth spurts and the metabolic and allometric parameters underlying growth require longitudinal datasets. Discussion: We conclude that this new model and estimation strategy constitute a potentially useful toolkit for comparing mean growth trajectories across contemporary and historical populations.

Background and objectives: Comparing children’s growth across the world and at different moments in history can yield insight into both health challenges and healthy morphological variation in our species. A difficulty of such comparative analyses is that, in marginalized populations, there are often logistical complications to obtaining repeat measures of individual children’s height and weight. The problem is even more acute for historical populations: bioarchaeological datasets comprise single measures of individuals at death. Additionally, for both contemporary and historical populations, there is often non-trivial uncertainty about children’s ages. Both of these factors complicate estimation of growth trajectories. Here we evaluate the degree to which we can accurately estimate a population-mean growth trajectory using only a small number of (randomly) uncertain measurements, like those that compose many contemporary and bioarchaeological datasets. Methodology: We recently derived a causal model of human growth from fundamental principles of metabolism and allometry, permitting exploration of genetic and environmental contributions to children’s growth. Here, we fit this model in a Bayesian framework to simulated cross-sectional and longitudinal datasets of varying size, where age is uncertain. Results: We show that, for large-scale comparative purposes, reasonably accurate population-mean growth trajectories may be obtained from single height measures of 100 children. However, detailed analyses of pubertal growth spurts and the metabolic and allometric parameters underlying growth require more extensive longitudinal datasets. Conclusions and implications: We conclude that this new model and estimation strategy constitute a potentially useful toolkit for comparing mean growth trajectories across contemporary and historical populations.

Existing models of human growth provide limited insight into underlying mechanisms responsible for inter-individual and inter-population variation in children’s growth trajectories. Building on general theories linking growth to metabolic rates, we develop a causal parametric model of height and weight growth incorporating a representation of human body allometry and a process-partitioned representation of ontogeny. This model permits separation of metabolic causes of growth variation, potentially influenced by nutrition and disease, from allometric factors, potentially under stronger genetic control. We estimate model parameters using a Bayesian multilevel statistical design applied to temporally dense height and weight measurements of U.S. children, and temporally sparse measurements of Indigenous Amazonian children. This facilitates a comparison of the contributions of metabolism and allometry to observed cross-cultural variation in the growth trajectories of the two populations, and permits simulation of the effects of healthcare interventions on growth. This theoretical model provides a new framework for exploring the causes of growth variation in our species, while potentially guiding the development of appropriate, and desired, healthcare interventions in societies confronting growth-related health challenges, such as malnutrition and stunting.

To address claims of human exceptionalism, we determine where humans fit within the greater mammalian distribution of reproductive inequality. We show that humans exhibit lower reproductive skew (i.e., inequality in the number of surviving offspring) among males and smaller sex differences in reproductive skew than most other mammals, while nevertheless falling within the mammalian range. Additionally, female reproductive skew is higher in polygynous human populations than in polygynous nonhumans mammals on average. This patterning of skew can be attributed in part to the prevalence of monogamy in humans compared to the predominance of polygyny in nonhuman mammals, to the limited degree of polygyny in the human societies that practice it, and to the importance of unequally held rival resources to women’s fitness. The muted reproductive inequality observed in humans appears to be linked to several unusual characteristics of our species—including high levels of cooperation among males, high dependence on unequally held rival resources, complementarities between maternal and paternal investment, as well as social and legal institutions that enforce monogamous norms.

The education of Indigenous children in non-Indigenous (e.g., "Western") school environments is at the forefront of debates about the sustainability and loss of valued Indigenous cultural traits and identities, though systematic study of the topic is rare. Here, using longitudinal structured interviews and participant observation among Indigenous Matsigenka children attending Mestizo-run secondary schools in the Peruvian Amazon, we provide the first empirical evidence of the magnitude of the shift in students' cultural norms toward those of their teachers, particularly in intensively-supervised boarding school environments. We highlight several mechanisms that may mediate this effect, and a potential short-term strategy to enhance the maintenance of cultural norms valued by Indigenous peoples exercising their right to Western-style education.

Existing models of human growth provide little insight into the mechanisms responsible for inter-individual and inter-population variation in children’s growth trajectories. Building on general theories linking growth to metabolic rates, we develop causal parametric models of height and weight growth incorporating a novel representation of human body allometry and a phase-partitioned representation of ontogeny. These models permit separation of metabolic causes of growth variation, potentially influenced by diet and disease, from allometric factors, potentially under strong genetic control. We estimate model parameters using a Bayesian multilevel statistical design applied to temporally-dense height and weight measurements of U.S. children, and temporally-sparse measurements of Indigenous Amazonian children. This facilitates a comparison of the metabolic and allometric contributions to observed cross-cultural variation in the growth trajectories of the two populations. These theoretical growth models constitute an initial step toward a better understanding of the causes of growth variation in our species, while potentially guiding the development of appropriate, and desired, healthcare interventions in societies confronting growth-related health challenges. Short Summary New causal models of human growth facilitate cross-cultural comparisons of metabolism and allometry.

This chapter is now published online here: https://academic.oup.com/edited-volume/45648/chapter/414125786?login=true Much cultural variation in humans is structured by ethnic identity, which entails perceptions of covariance between easily observable markers, difficult-to-observe norms, and, often, (potentially mythical) ancestry. The dynamics of ethnic identity entail changes in the distributions of these perceptions in a population over time. Here, we review the scope of ethnicity, the adaptive nature of ethnic psychology, the dynamics of ethnic perceptions, the consequences of ethnicity for other cultural dynamics, and challenges for future research.

In much contemporary political discourse, valued cultural characteristics are threatened by interaction with culturally distinct others, such as immigrants or a hegemonic majority. Such interaction often fosters cross-cultural competence (CCC), the ability to interact successfully across cultural boundaries. However, most theories of cultural dynamics ignore CCC, making cultural diversity incompatible with mutually beneficial inter-group interaction, and contributing to fears of cultural loss. Here, interview-based field methods at an Amazonian ethnic boundary demonstrate the prevalence of CCC. These data motivate a new theoretical mathematical model, incorporating competing developmental paths to CCC and group identity valuation, that illuminates how a common strategy of disempowered minorities can counter-intuitively sustain cultural diversity within a single generation: Given strong group identity, minorities in a structurally unequal, integrative society can maintain their distinctive cultural norms by learning those of the majority. Furthermore, rather than a rejection of, or threat to, majority culture, the valuation of a distinctive minority identity can characterize CCC individuals committed to extensive, mutually beneficial engagement with the majority as members of an integrative, multi-cultural society.

The intensifying pace of research based on cross-cultural studies in the social sciences necessitates a discussion of the unique challenges of multi-sited research. Given an increasing demand for social scientists to expand their data collection beyond WEIRD (Western, educated, industrialized, rich and democratic) populations, there is an urgent need for transdisciplinary conversations on the logistical, scientific and ethical considerations inherent to this type of scholarship. As a group of social scientists engaged in cross-cultural research in psychology and anthropology, we hope to guide prospective cross-cultural researchers through some of the complex scientific and ethical challenges involved in such work: (a) study site selection, (b) community involvement and (c) culturally appropriate research methods. We aim to shed light on some of the difficult ethical quandaries of this type of research. Our recommendation emphasizes a community-centred approach, in which the desires of the community regarding research approach and methodology, community involvement, results communication and distribution, and data sharing are held in the highest regard by the researchers. We argue that such considerations are central to scientific rigour and the foundation of the study of human behaviour.

This article has now been published open-access as: Bunce, JA (2021) Cultural diversity in unequal societies sustained through cross-cultural competence and identity valuation. Humanities and Social Sciences Communications 8: 238. It is available here: https://www.nature.com/articles/s41599-021-00916-5