Found 3235 Hypotheses across 324 Pages (0.004 seconds)
  1. Environmental productivity will be positively associated with land ownershipKavanaugh, Patrick - Drivers of global variation in land ownership, 2021 - 2 Variables

    Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.

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  2. Population density will be positively associated with property ownershipKavanaugh, Patrick - Drivers of global variation in land ownership, 2021 - 2 Variables

    Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.

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  3. Reliance on domestication will be positively associated with property ownershipKavanaugh, Patrick - Drivers of global variation in land ownership, 2021 - 2 Variables

    Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.

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  4. Use of intensive agriculture will be positively associated with property ownershipKavanaugh, Patrick - Drivers of global variation in land ownership, 2021 - 2 Variables

    Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.

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  5. Permanency of settlement patterns will be positively associated with land ownershipKavanaugh, Patrick - Drivers of global variation in land ownership, 2021 - 2 Variables

    Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.

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  6. Coastal distance will be negatively associated with property ownership.Kavanaugh, Patrick - Drivers of global variation in land ownership, 2021 - 2 Variables

    Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.

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  7. Unpredictability of resources will be negatively associated with property ownershipKavanaugh, Patrick - Drivers of global variation in land ownership, 2021 - 2 Variables

    Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.

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  8. Nearest neighbor's property system will have a positive association with property ownershipKavanaugh, Patrick - Drivers of global variation in land ownership, 2021 - 2 Variables

    Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.

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  9. Mountainous terrain will have a positive association with property ownershipKavanaugh, Patrick - Drivers of global variation in land ownership, 2021 - 2 Variables

    Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.

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  10. The presence of horses, food storage, and formal resource ownership will each be negatively associated with a lack of class stratificationHooper, Paul L. - Gains to cooperation drive the evolution of egalitarianism, 2021 - 4 Variables

    This article is mainly concerned with understanding the motivators toward egalitarianism through modeling via a game that combined elements from both hawk-dove and prisoners dilemma. While most of the article is focused on this model, the researchers also tested their hypotheses cross-culturally on a sample of forager societies. In both cases, they found evidence that the benefits of cooperation drove egalitarianism.

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