Theory-based Measurement of Varieties of Power Using a Novel Semi-supervised IRT Model

国家权力的概念被用来解释一切，从开始或结束战争的决定，到贸易政策，再到国家在自己境内做出的决定。然而，尽管这一概念很普遍，也很重要，但要以任何一致的方式衡量权力，一直是一个挑战。哪一组特征可能会迫使一个国家顺应其他国家的偏好？我们能否提前测量这些特征，以便更好地预测国家在回应本国和其他国家的绝对和相对权力时的行为？这样的预测对确保国防安全至关重要。该项目将对为此目的收集的各种数据来源使用新的半监督机器学习技术，从而产生一套理论上知情的权力衡量标准。这套措施将有助于政策制定者评估国家之间的权力动态，帮助决策和加强安全。科学界和政策界都使用了广泛的权力理论概念，最突出的是硬权力和软权力。然而，对功率的测量通常只捕捉到它的一些理论用途，同时包括可能与所讨论的功率使用无关的方面。例如，当国际关系学者讨论“权力”时，他们可能指的是非常具体的权力类型，他们的结论、措施和模式可能不会延续到其他类型。例如，军事力量已经通过军队的规模和国家能力综合指数(CINC)得分来运作，但在软实力因素发挥作用的情况下，这两者都不太可能作为衡量标准。该项目在测量功率的能力方面提供了几项改进。首先，它提供了一系列理论上知情的权力类型衡量标准。其次，它收集了一个庞大的来源数据集，为这些不同的权力衡量标准提供信息。第三，它提供了一种灵活的工具--一种半监督机器学习算法，利用改进的贝叶斯项目反应理论模型--透明地构建替代的权力衡量标准。这为跨背景持续评估不同类型权力在国际关系中的作用的研究打开了大门，并允许利益相关者就与他们最相关的权力方面进行清晰的沟通。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The concept of state power has been invoked to explain everything from decisions to begin or end wars to trade policy to decisions nations make within their own borders. Yet, despite the prevalence and importance of the concept, it has been challenging to measure power in any consistent manner. What set of characteristics might compel a nation to go along with the preferences of other nations? And can we measure those characteristics ahead of time, in order to better predict the behavior of states as they respond to their own and other states’ absolute and relative power? Such predictions are essential to securing the national defense. This project will produce a theoretically-informed set of measures of power by using new semi-supervised machine learning techniques on a wide range of data sources gathered for the purpose. That set of measures will aid policy-makers in assessing the power dynamics between states, helping decision-making and enhancing security.In both scientific and policy circles, a wide range of theoretical conceptions of power are employed, most notably hard and soft power. Measurements of power, however, typically only capture some of its theoretical uses, while at the same time including aspects that might be unrelated to the use of power in question. When international relations scholars discuss “power,” for instance, they could be referring to very specific types of power, and their conclusions, measures, and models may not carry over to other types. For example, military power has been operationalized by the size of the army and the Composite Index of National Capability (CINC) score, but neither are likely useful as measures when elements of soft power are in play. This project offers several improvements in the ability to measure power. One, it provides a series of theoretically-informed measures of types of power. Two, it gathers a large dataset of sources that inform those different measures of power. Three, it provides a flexible tool—a semi-supervised machine learning algorithm making use of a modified Bayesian Item Response Theory model—to transparently construct alternate measures of power. That opens the door to studies that consistently assess across contexts the role of different types of power in international relations and allows stakeholders to communicate clearly about the aspects of power most relevant to them.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.