Daniel Redhead

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Published

2023-10-20

I’m Daniel Redhead and I’m an incoming assistant professor in Sociology at the University of Groningen. I was trained as an undergraduate in Archaeology and Anthropology at Durham University in the UK, and completed a Masters in Evolutionary Anthropology again at Durham. I then moved into a psychology PhD programme at the University of Essex, where I began to develop and apply dynamical models and longitudinal social network analysis to understand how individuals gain and maintain social status over time. Following this, I became a postdoctoral researcher, and then group leader, in the Department of Human Behavior, Ecology and Culture at the Max Planck Institute for Evolutionary Anthropology. Here, I have been conducting large-scale cross-cultural research on social networks and inequality in small-scale subsistence communities around the world, and have also developed methods and software for collecting, managing and analyzing social network data.

Project Title

Social structure and the evolutionary ecology of inequality

Social transition(s) addressed

Inequality pervades all societies. In some societies we observe substantial levels of inequality, with a small set of individuals having disproportionate access to a group’s material, informational and social resources. In other settings, such resources are more equally distributed between group members. This project aims to understand how inequality in material wealth–and social inequality–emerge and are sustained across different cultural and ecological settings. More specifically, the project will examine whether certain ecological pressures structure the ways in which individuals interact and form cooperative relationships in rural, small-scale subsistence societies around the world. The project will further show how the structure of these networks of cooperation can produce, or constrain inequality. Many of these societies are undergoing major demographic and economic transitions, and determining the pathways to greater, or lesser, inequality is crucial for understanding the trajectories these societies will take.

Behavioral change(s) addressed

This research project is focused on understanding how social behaviours–that is, the formation of cooperative relationships (e.g., friendships) or interactions (e.g., sharing of material resources, co-labouring or food sharing)–adapt to the local ecological pressures that a society faces (e.g., modes of subsistence, resource abundance), and how such adaptive responses structure the levels of inequality observed across societies. Findings from this project will help us to better understand how ecological or demographic transitions can impact (and potentially reflect) fundamental changes in the social/organizational structure of these societies–such as the changing roles of cooperation within and between households. Ultimately, these findings not only have the potential to guide targeted interventions for reducing inequality in such societies, but can inform us about how and why certain social and economic policies or interventions on inequality have failed in industrialized societies. In doing this, these findings will provide a platform for devising policies that are calibrated to local cultural and ecological contexts.

Theoretical approach

This research project will integrate theory from across the social, behavioural and evolutionary sciences to examine how the interplay between ecological factors and social structure allows inequality to be sustained in a society. Theory in ecology, economics and cultural evolution has proposed that the emergence of subsistence practices that produce material goods that are relatively stable across time, and are defensible, provides the optimal setting for inequality. This, coupled with variation in resource abundance on patches of land that individuals occupy and endow to offspring, can produce differential access to material resources–allowing the rich to get richer, and producing a dynamic where those in patches were resources are less abundant become dependent on wealthier others. The proposed ecological and cultural conditions in which such subsistence practices (e.g., small-scale agriculture) are variable, and both the economic and social consequences of inequality are broad. While much work on inequality has provided important advances as to the micro-level processes (e.g., educational attainment), and macro-level factors (e.g., institutions governing wealth redistribution) that govern the level of inequality in large-scale, industrialized societies, the role of social networks is the largest gap in our understanding of inequality. This gap has been caused by a) limitations associated with large-scale, industrialized samples typically used in the field, b) a lack of data from culturally- and ecologically-distinct societies, and c) constraints and biases of network measurements, which scale poorly and lead to partial observations of the social networks in a society. This project aims to address this gap through large-scale comparative research that collects fine-grained interaction and economic data in rural, preindustrial societies.

Empirical research strategies

Broadly, the research project will leverage new data collection tools that I am developing to produce comparative longitudinal data on social networks, material wealth, economic behaviour and social status from ~10 small-scale subsistence societies around the world. This will be done through a combination of structured questionnaires/interviews, behavioural economic games and exhaustive household economic inventories.

Alongside this, the project will see the development of new methods and tools for social network analysis, which will be packaged into easy-to-use software. These tools have the potential to advance the ways that we collect social network data in small-scale subsistence societies–providing a computational framework for automated data collection and processing that will make the project’s empirical research feasible and effective. Answering the project’s core research questions will also require bespoke models of network dynamics that reliably capture the data generation processes, and adjust for the biases associated with the measurement instruments implemented throughout the project.

Possibilities for inter- and transdisciplinary collaboration

The project is inherently interdisciplinary, synthesizing both theory and methods from the social, behavioural and evolutionary sciences. Given this, the project provides the perfect platform for interdisciplinary collaboration, and would certainly be strengthened with input from researchers working in sociology, economics, anthropology, cultural evolution and behavioural ecology. In particular, I would welcome collaborations that would sharpen the project’s theoretical motivation–and treatment of existing work–on theory on social structure and material wealth inequality from a sociological and economic perspective. Alongside this, any input on the most optimal approaches for calculating estimates of material wealth from (noisy) household economic inventories would definitely be appreciated.