Chapter Nabladot Analysis of Hybrid Theories in International Relations

Scientific research in International Relations has produced a growing corpus of empirically grounded formal theoretical models of phenomena ranging from deterrence to systemic polarity, from conditions of peace to the onset of war. Many of these important theories contain a mix of continuous and discrete dimensions, causal variables, and parameters. Analysis and understanding of this fundamental and intriguing class of theories containing functions with a mix of continuous and discrete variables has puzzled generations of social scientists and applied mathematicians. This challenging and longstanding puzzle now has a solution. Here we demonstrate how the recently created calculus with nabladot operators is beginning to uncover previously unknown properties of hybrid international phenomena. Results include new concepts and precise principles on causal relationships, previously unknown political features, and fundamental properties of probabilistic causality, demonstrated through nabladot analysis of international events, crisis dynamics, and warfare

A Methodology for Complex Social Simulations

Social simulation - an emerging field of computational social science - has progressed from simple toy models to increasingly realistic models of complex social systems, such as agent-based models where heterogeneous agents interact with changing natural or artificial environments. These larger, multidisciplinary projects require a scientific research methodology distinct from, say, simpler social simulations with more limited scope, intentionally minimal complexity, and typically under a single investigator. This paper proposes a methodology for complex social simulations - particularly inter- and multi-disciplinary socio-natural systems with multi-level architecture - based on a succession of models akin to but distinct from the late Imre Lakatos' notion of a 'research programme'. The proposed methodology is illustrated through examples from the Mason-Smithsonian project on agent-based models of the rise and fall of polities in Inner Asia. While the proposed methodology requires further development, so far it has proven valuable for advancing the scientific objectives of the project and avoiding some pitfalls.Agent-Based Modeling Methodology, M2M, Social Simulation, Computational Social Science, Social Complexity, Inner Asia

Intergroup Conflict Escalation Leads to More Extremism

Empirical findings in the intergroup conflict literature show that individuals’ beliefs that mark differentiation from out-groups become radicalized as intergroup tensions escalate. They also show that this differentiation is proportional to tension escalation. In this paper, we are interested to develop an agent-based model which captures these findings in order to explore the effect of perceived intergroup conflict escalation on the average number of emergent extremists and opinion clusters in the population. The proposed model builds on the 2-dimensional bounded confidence model proposed by Huet et al (2008). The results show that the average number of extremists has a negative correlation with intolerance threshold and positive correlation with the amount of opinion movement when two agents are to reject each other’s belief. In other words, the more tensions exist between groups, the more individuals getting extremists. We also found that intergroup conflict escalation leads to lower opinion diversity in the population compared with normal situations

Manifesto of computational social science

The increasing integration of technology into our lives has created unprecedented volumes of data on society’s everyday behaviour. Such data opens up exciting new opportunities to work towards a quantitative understanding of our complex social systems, within the realms of a new discipline known as Computational Social Science. Against a background of financial crises, riots and international epidemics, the urgent need for a greater comprehension of the complexity of our interconnected global society and an ability to apply such insights in policy decisions is clear. This manifesto outlines the objectives of this new scientific direction, considering the challenges involved in it, and the extensive impact on science, technology and society that the success of this endeavour is likely to bring about

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Invariance and universality in social agent-based simulations

Agent-based simulation models have a promising future in the social sciences, from political science to anthropology, economics, and sociology. To realize their full scientific potential, however, these models must address a set of key problems, such as the number of interacting agents and their geometry, network topology, time calibration, phenomenological calibration, structural stability, power laws, and other substantive and methodological issues. This paper discusses and highlights these problems and outlines some solutions