Counterfactuals seek to alter some feature or event of the pass and by means of a chain of causal logic show how the present might, or would, be different. Counterfactual inquiry—or control of counterfactual situations—is essential to any causal claim. More importantly, counterfactual thought experiments are essential, to the construction of analytical frameworks. Policymakers routinely use then by to identify problems, work their way through problems, and select responses. Good foreign-policy analysis must accordingly engage and employ counterfactuals.
There are two generic types of counterfactuals: minimal-rewrite counterfactuals and miracle counterfactuals. They have relevance when formulating propositions and probing contingency and causation. There is also a set of protocols for using both kinds of counterfactuals toward these ends, and it illustrates the uses and protocols with historical examples. Policymakers invoke counterfactuals frequently, especially with regard to foreign policy, to both choose policies and defend them to key constituencies. They use counterfactuals in a haphazard and unscientific manner, and it is important to learn more about how they think about and employ counterfactuals to understand foreign policy.
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Counterfactuals and Foreign Policy Analysis
Richard Ned Lebow
Article
Pro-Government Militias and Conflict
Sabine C. Carey, Neil J. Mitchell, and Adam Scharpf
Pro-government militias are a prominent feature of civil wars. Governments in Ukraine, Russia, Syria, and Sudan recruit irregular forces in their armed struggle against insurgents. The United States collaborated with Awakening groups to counter the insurgency in Iraq, just as colonizers used local armed groups to fight rebellions in their colonies. A now quite wide and established cross-disciplinary literature on pro-government nonstate armed groups has generated a variety of research questions for scholars interested in conflict, political violence, and political stability: Does the presence of such groups indicate a new type of conflict? What are the dynamics that drive governments to align with informal armed groups and that make armed groups choose to side with the government? Given the risks entailed in surrendering a monopoly of violence, is there a turning point in a conflict when governments enlist these groups? How successful are these groups? Why do governments use these nonstate armed actors to shape foreign conflicts, whether as insurgents or counterinsurgents abroad? Are these nonstate armed actors always useful to governments or perhaps even an indicator of state failure? How do pro-government militias affect the safety and security of civilians?
The enduring pattern of collaboration between governments and pro-government armed groups challenges conventional theory and the idea of an evolutionary process of the modern state consolidating the means of violence. Research on these groups and their consequences began with case studies, and these continue to yield valuable insights. More recently, survey work and cross-national quantitative research have contributed to our knowledge. This mix of methods is opening new lines of inquiry for research on insurgencies and the delivery of the core public good of effective security.
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Q Methodology in Research on Political Decision Making
Steven R. Brown
Q methodology was introduced in 1935 and has evolved to become the most elaborate philosophical, conceptual, and technical means for the systematic study of subjectivity across an increasing array of human activities, most recently including decision making. Subjectivity is an inescapable dimension of all decision making since we all have thoughts, perspectives, and preferences concerning the wide range of matters that come to our attention and that enter into consideration when choices have to be made among options, and Q methodology provides procedures and a rationale for clarifying and examining the various viewpoints at issue. The application of Q methodology commonly begins by accumulating the various comments in circulation concerning a topic and then reducing them to a smaller set for administration to select participants, who then typically rank the statements in the Q sample from agree to disagree in the form of a Q sort. Q sorts are then correlated and factor analyzed, giving rise to a typology of persons who have ordered the statements in similar ways. As an illustration, Q methodology was administered to a diverse set of stakeholders concerned with the problems associated with the conservation and control of large carnivores in the Northern Rockies. Participants nominated a variety of possible solutions that each person then Q sorted from those solutions judged most effective to those judged most ineffective, the factor analysis of which revealed four separate perspectives that are compared and contrasted. A second study demonstrates how Q methodology can be applied to the examination of single cases by focusing on two members of a group contemplating how they might alter the governing structures and culture of their organization. The results are used to illustrate the quantum character of subjective behavior as well as the laws of subjectivity. Discussion focuses on the broader role of decisions in the social order.
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The Search for Real-World Media Effects on Political Decision Making
Thomas J. Leeper
Empirical media effects research involves associating two things: measures of media content or experience and measures of audience outcomes. Any quantitative evidence of correlation between media supply and audience response—combined with assumptions about temporal ordering and an absence of spuriousness—is taken as evidence of media effects. This seemingly straightforward exercise is burdened by three challenges: the measurement of the outcomes, the measurement of the media and individuals’ exposure to it, and the tools and techniques for associating the two.
While measuring the outcomes potentially affected by media is in many ways trivial (surveys, election outcomes, and online behavior provide numerous measurement devices), the other two aspects of studying the effects of media present nearly insurmountable difficulties short of ambitious experimentation. Rather than find solutions to these challenges, much of collective body of media effects research has focused on the effort to develop and apply survey-based measures of individual media exposure to use as the empirical basis for studying media effects. This effort to use survey-based media exposure measures to generate causal insight has ultimately distracted from the design of both causally credible methods and thicker descriptive research on the content and experience of media. Outside the laboratory, we understand media effects too little despite this considerable effort to measure exposure through survey questionnaires.
The canonical approach for assessing such effects: namely, using survey questions about individual media experiences to measure the putatively causal variable and correlating those measures with other measured outcomes suffers from substantial limitations. Experimental—and sometimes quasi-experimental—methods provide definitely superior causal inference about media effects and a uniquely fruitful path forward for insight into media and their effects. Simultaneous to this, however, thicker forms of description than what is available from close-ended survey questions holds promise to give richer understanding of changing media landscape and changing audience experiences. Better causal inference and better description are co-equal paths forward in the search for real-world media effects.
