American Sociological Association

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  1. Nuclear War in the Rivalry Phase of the Modern World-System

    Large-scale war is a world-system phenomenon of the rivalry phase. Such conflicts have once again become a concern, and nuclear weapons make these prospects especially dangerous. This is particularly problematic since several world-systems perspectives suggest the chances for war will be greatest in the period from 2030 to 2050. I review the logic of rivalry, the reasons for the endurance of nuclear weapons, old and new nuclear strategies, and the processes that may pose the greatest existential dangers.
  2. Intrastate Dynamics in the Context of Hegemonic Decline: A Case Study of China’s Arms Transfer Regime

    The decline of a hegemon can create openings for lesser powers to expand their influence in the world-system. Is this what China is currently attempting to do? This paper contributes to this on-going debate by examining China’s arms transfer activities from a historical perspective. Using data from the Stockholm International Peace Research Institute arms transfer database and the World Military Expenditures and Arms Transfers database, I argue that the Chinese arms transfer regime has evolved through three phases.
  3. Research Note: Measuring the Impacts of Colonialism: A New Data Set for the Countries of Africa and Asia

    We present a new dataset with 15 indicators for the political, economic and social impact of colonialism. This dataset and our four indices for the impact of colonialism create for the first time the opportunity to compare directly the levels of colonial transformation for a sample of 83 African and Asian countries. Some of our exploratory findings on the interrelation of the dimensions show that in British colonies political domination was in general less direct and less violent. Plantation colonies experienced more investment in infrastructure and more violence during decolonization.
  4. The Moral Limits of Predictive Practices: The Case of Credit-Based Insurance Scores

    Corporations gather massive amounts of personal data to predict how individuals will behave so that they can profitably price goods and allocate resources. This article investigates the moral foundations of such increasingly prevalent market practices. I leverage the case of credit scores in car insurance pricing—an early and controversial use of algorithmic prediction in the U.S. consumer economy—to unpack the premise that predictive data are fair to use and to understand the conditions under which people are likely to challenge that moral logic.