Found 1930 Hypotheses across 193 Pages (0.009 seconds)
  1. Technological complexity is positively associated with risk of resource failure (1).Collard, Mark - Risk, mobility or population size?: Drivers of technological richness among ..., 2013 - 6 Variables

    This paper builds off previous research into the effect of population size and resource risk on complexity of subsistence technology by investigating the relationship between these independent variables and total number of material items and techniques used by various western North American hunter-gatherer groups. This tally of total technological complexity is found to be insignificantly related to population size or residential mobility; however, there is a significant correlation in the expected direction between technological complexity and one measure of resource risk (mean annual temperature during driest month). Tying this finding to previous analyses of subsistence technologies, the authors theorize that environmental risk is a pervasive driver of technological ingenuity and cultural evolution.

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  2. Risk in subsistence strategies is associated with implement diversity.Read, Dwight - An Interaction Model for Resource Implement Complexity Based on Risk and Num..., 2008 - 6 Variables

    In this paper, the authors analyzed data on 20 hunter-gatherer groups in order to understand the factors that influence the diversity and elaborateness of their tool assemblages. They used data collected by a variety of ethnographers to draw inferences about the complexity of implement assemblages and how it is affected by ecological constraints, modes of resource procurement, group movement, and population size. Regression analysis showed that the two strongest predictors of implement complexity were growth season (GS) (as a proxy for risk) and the number of annual residential moves (NMV). With the understanding that NMV and GS are likely not independent, the authors created addition and interaction models to understand how these variables may work in tandem to influence implement diversity and elaborateness. The results show that a shorter growing season (higher risk) and a lower number of moves are correlated with greater implement complexity. This analysis also divided the hunter-gatherers into two subgroups: a subgroup characterized by higher diversity of complex implements and more elaborate individual implements than predicted by the model, and a subgroup characterized by lower diversity and less elaborateness than predicted. These subgroups were found to correspond with the distinction between foragers (groups that move more-or-less as a unit while gathering) and collectors (groups that gather (logistically from a more-or-less fixed settlement), with the higher diversity subgroup being made up mostly of collectors and the lower diversity subgroup being made up mostly of foragers. Finally, the authors suggest that under conditions where population growth leads to increased density, foraging strategies will tend to shift to collector strategies in conjunction with increased elaborateness of implements to exploit resources with greater intensity.

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  3. Net primary productivity is correlated with number of specializations.Ben-Oren, Yotam - Cultural specialization as a double-edged sword: division into specialized g..., 2023 - 2 Variables

    This article presents a model of cultural evolution simulating the accumulation of tools in specialized and non-specialized populations under different demographic and environmental scenarios. The model predicts that the relationship between population size and repertoire size is nonlinear and can differ between non-specialized and specialized populations. For small population sizes, the non-specialized populations maintain knowledge better and therefore reach higher average repertoire sizes. In large populations, specialized populations can reach higher average repertoire sizes. This is because non-specialized population's total repertoire size is limited by the capacity of individuals to accumulate knowledge of different skills, while in specialized populations, each individual needs to know only a fraction of the population's repertoire. However, the model also predicts that specialized populations are more susceptible to information loss due to their subdivision of knowledge, and this can be amplified by demographic and environmental factors. The authors also use ethnographic data to analyze the relationship between population size and degree of craft specialization of societies, and how this may be influenced by ecological factors.

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  4. Risk in subsistence strategies is associated with implement elaborateness.Read, Dwight - An Interaction Model for Resource Implement Complexity Based on Risk and Num..., 2008 - 7 Variables

    In this paper, the authors analyzed data on 20 hunter-gatherer groups in order to understand the factors that influence the diversity and elaborateness of their tool assemblages. They used data collected by a variety of ethnographers to draw inferences about the complexity of implement assemblages and how it is affected by ecological constraints, modes of resource procurement, group movement, and population size. Regression analysis showed that the two strongest predictors of implement complexity were growth season (GS) (as a proxy for risk) and the number of annual residential moves (NMV). With the understanding that NMV and GS are likely not independent, the authors created addition and interaction models to understand how these variables may work in tandem to influence implement diversity and elaborateness. The results show that a shorter growing season (higher risk) and a lower number of moves are correlated with greater implement complexity. This analysis also divided the hunter-gatherers into two subgroups: a subgroup characterized by higher diversity of complex implements and more elaborate individual implements than predicted by the model, and a subgroup characterized by lower diversity and less elaborateness than predicted. These subgroups were found to correspond with the distinction between foragers (groups that move more-or-less as a unit while gathering) and collectors (groups that gather (logistically from a more-or-less fixed settlement), with the higher diversity subgroup being made up mostly of collectors and the lower diversity subgroup being made up mostly of foragers. Finally, the authors suggest that under conditions where population growth leads to increased density, foraging strategies will tend to shift to collector strategies in conjunction with increased elaborateness of implements to exploit resources with greater intensity.

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  5. Risk of resource failure will influence toolkit structure (4).Collard, Mark - Causes of toolkit variation among hunter-gatherers: a test of four competing..., 2005 - 3 Variables

    This study tests four hypotheses that propose potential environmental and social predictors of toolkit size and complexity among hunter-gatherers. Hypotheses predicting relationships between population size, residential mobility, type of food resources and toolkit structure are not supported. Risk of resource failure is the only variable that is significantly associated with toolkit structure.

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  6. "Holding population density constant, forager groups should increase the time they spend within a habitat as the rate of resource growth in a habitat declines (434)"Freeman, Jacob - Intensification, tipping points, and social change in a coupled forager-reso..., 2012 - 4 Variables

    The authors present a bioeconomic model of hunter-gatherer foraging effort to quantitatively represent forager intensification. Using cross-cultural data, the model is evaluated as a means to better understand variation in residential stability and resource ownership.

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  7. The net primary productivity of agriculturalists’ will be greater than that of foragers’ land.Porter, Claire C. - How marginal are forager habitats?, 2007 - 2 Variables

    This article examines the quality of forager habitats to determine whether agriculturalists occupy the most productive areas while modern forager groups are relegated to poor habitats. Findings indicate that there are slight but insignificant differences in the net primary productivity of foragers’ land and agriculturalists’ land. Further analysis of types of agriculturalists suggest that horticulturalists live in the most productive habitats, followed by intensive agriculturalists and finally pastoralists.

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  8. Direct fire boiling vessel fabric type will be associated with potential evapotransportation and net aboveground productivity (243).Nelson, Kit - Environment, cooking strategies and containers, 2010 - 3 Variables

    This article examines cooking strategies and cooking containers cross-culturally. Focusing on stone boiling and direct fire cooking, the authors find that geographic location and climate (particularly temperature, rainfall, and evapotranspiration) will be associated with cooking strategy. Container fabric type was also examined, and was found to be associated with cooking strategy, climatic variables, and subsistence type.

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  9. The net primary productivity of intensive agriculturalists land will be greater than that of pastoralists and horticulturalists.Porter, Claire C. - How marginal are forager habitats?, 2007 - 2 Variables

    This article examines the quality of forager habitats to determine whether agriculturalists occupy the most productive areas while modern forager groups are relegated to poor habitats. Findings indicate that there are slight but insignificant differences in the net primary productivity of foragers’ land and agriculturalists’ land. Further analysis of types of agriculturalists suggest that horticulturalists live in the most productive habitats, followed by intensive agriculturalists and finally pastoralists.

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  10. Seasonal time pressure--as indicated by number of dry months--will be associated with decreased female participation in agriculture (574).Burton, Michael L. - Sexual division of labor in agriculture, 1984 - 2 Variables

    Authors Michael Burton and Douglas White present and test an ecological model for the process of agricultural intensification that aims to explain variance in (and the reduction in) female contribution to agriculture. The model synthesizes and expands upon findings put forth by previous studies in order to create a more comprehensive design. Results suggest that the strongest predictors of female contribution to agriculture are the number of dry months, the importance of domesticated animals to subsistence, and the use of the plow in farming. Crop type, although a weaker predictor, is also supported.

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