The article discusses the importance of incorporating local knowledge and strategies into sustainable climate change adaptation. The authors examined 90 societies from the ethnographic record to document the coping mechanisms and contingency plans used by societies around the world in response to natural hazards. They classified coping mechanisms into four types: technological, subsistence, economic, and religious. The study finds that most societies employ multiple types of coping mechanisms and that technological coping mechanisms are most common in response to fast-onset hazards, while religious coping mechanisms are most common in response to slow-onset hazards. The study also finds that religious and nonreligious coping strategies are not mutually exclusive and are often used in conjunction with each other.

The second and third parts of this book classify the economic systems of foraging and agricultural societies in the SCCS based on correlations between their institutions of property an distribution. These economic types are then examined for relationships with other social, political, demographic, and environmental factors in order to draw tentative conclusions regarding the origins of the Agricultural and Industrial Revolutions. The fourth part of the book uses cross-national data to examine similar associations in industrial/service economies, and is not included here.

The article examines whether cultural groups tend to use supernatural beliefs more to explain natural phenomena or social phenomena. Analysis of ethnographic text from 114 diverse societies reveals that supernatural explanations are more common for natural phenomena, consistent with the theory that humans tend to perceive intent and agency in the natural world. However, supernatural explanations of social phenomena were more prevalent in urbanized societies with greater social complexity and anonymity. The study highlights how people use supernatural beliefs to explain their world and how this varies across small-scale and urbanized communities.

The present study aims to assess the reliability of Simmons' (1937) database of 109 variables coded for 71 societies. Simmons' data was evaluated against matching societies and variables from Murdock's (1967) Ethnographic Atlas. The ultimate purpose of Rudmin's analysis is to identify the features of societies that are correlated with the private ownership of property. To do so, Simmons' reliable variables are tested against four measures of property ownership, two from Simmons and two from Murdock. Rudmin discusses results and speculates why certain clusters of societal variables correlate with private property ownership.

The authors examine correlations between slavery and variables that can potentially be detected archaeologically. The authors do not test specific hypotheses, but aim to explore the variables in a broader sense. As such, the authors use a grounded theory approach to data analysis in order to examine trends that emerge from the data itself.

This study develops a model of the conditions under which a societies switch from a anarchy to a hierarchy. Empirical results suggest that the presence of police, technological sophistication, population density, and food storage are positively associated with the presence of a territorial hierarchy.

This article aims to answer the question: Does the imagery of composite beings, also known as monsters, appear cross-culturally? The authors use the Standard Cross-Cultural Sample to test whether these mythical figures are universal and which sociocultural variables might be related to their presence or absence. To do so, they use the ten measures of cultural complexity by Murdock and Provost (1973): writing and records, fixity of residence, agriculture, urbanization, technological specialization, land transport, money, density of population, level of political integration, and social stratification. The results show that the concept of "monsters" is common among cultures, but not universal. Additionally, the presence of composite beings is related to all the measures of cultural complexity. Finally, the authors wanted to test which variables are more relevant. They use a machine learning method (decision trees and random forests), which suggests that the most important variables are social stratification and higher inter-group contact facilitated by land vehicles.

The authors develop and empirically test a model in which exogamy is negatively predicted by community size, due to decreasing heterogeneity from endogenous marriages in small settlements, and positively predicted by disparity in productivity between communities which is 'smoothed out' by transfer of community members through exogamous marriages. Support for both predictions is found, which is used to argue that cultural traits like marriage customs are heavily influenced by population-environment relationships.

This study examines pairwise differences between similar cultures in order to minimize cultural variation within the SCCS and reveal possible correlates of cultural complexity. Results suggest that one measure of complexity (government above the community level) is significantly associated with several other variables.

This study presents a theory of land inheritance that "focuses on the incentives that land inheritence rules create for potential heirs" and tests this theory on a cross-cultural sample.