Although the US government has been using remotely piloted aircraft (RPA), more commonly referred to as drones, to conduct military strikes against terrorists and insurgents since at least 2001, only around 2011 did media outlets and polling organizations began assessing the attitudes of Americans towards the use of drones as a weapon of war. Initially, public support for drone strikes was robust with nearly 70 percent of Americans expressing approval. As the discussion of drone strikes intensified however, public support declined over 10 percentage points.
Only a handful of studies have examined public opinion and drone strikes, and all have focused exclusively on explaining support. This study seeks to fill this gap in the literature and explain opposition to drone strikes. The primary argument put forth in this dissertation is that people’s beliefs determine their opinions, and their morality determines their beliefs. Although independent opinion formation is often considered a cognitive process, I argue that, at least in the case of drone strikes, the opinion formation process is largely an affective one.
By examining media coverage and elite discourse surrounding drone strikes, I isolate three narratives which I believe communicate certain messages to the public regarding drone strikes. I argue that the messages produced by elite discourse and disseminated by the media to the public are only influential on opinion formation once they have been converted to beliefs. I further argue that conversion of message to belief is largely dependent on individual moral attitudes.
To test my arguments, I conduct a survey-experiment using subjects recruited from Arizona State University’s School of Politics and Global Studies student subject pool. My research findings lead to two key conclusions. First, opposition to drone strikes is largely the product of the belief(s) that drone strikes are not necessary for protecting the United States from terrorist attack, and that drone strikes kill more civilians than do strikes from conventional aircraft. Second, whether an individual expresses support or opposition to drone strikes, moral attitudes are a relatively good predictor of both beliefs and disposition.
The majority of trust research has focused on the benefits trust can have for individual actors, institutions, and organizations. This “optimistic bias” is particularly evident in work focused on institutional trust, where concepts such as procedural justice, shared values, and moral responsibility have gained prominence. But trust in institutions may not be exclusively good. We reveal implications for the “dark side” of institutional trust by reviewing relevant theories and empirical research that can contribute to a more holistic understanding. We frame our discussion by suggesting there may be a “Goldilocks principle” of institutional trust, where trust that is too low (typically the focus) or too high (not usually considered by trust researchers) may be problematic. The chapter focuses on the issue of too-high trust and processes through which such too-high trust might emerge. Specifically, excessive trust might result from external, internal, and intersecting external-internal processes. External processes refer to the actions institutions take that affect public trust, while internal processes refer to intrapersonal factors affecting a trustor’s level of trust. We describe how the beneficial psychological and behavioral outcomes of trust can be mitigated or circumvented through these processes and highlight the implications of a “darkest” side of trust when they intersect. We draw upon research on organizations and legal, governmental, and political systems to demonstrate the dark side of trust in different contexts. The conclusion outlines directions for future research and encourages researchers to consider the ethical nuances of studying how to increase institutional trust.
In an effort to understand the factors involved in the decisions to adopt a local drone use policy, this dissertation leverages qualitative methods to analyze the policy process leading to local decisions. The study capitalizes on rich contextual data gathered from a variety of sources for select cities in Orange and Los Angeles Counties. Specifically, this study builds a conceptual framework from policy innovation literature and applies it in the form of content analysis. This initial effort is used to identify the catalysts for policy discussion and the specific innovation mechanisms that support or detract from the decision to adopt a local drone use ordinance. Then, qualitative comparative analysis is used to determine which configuration of factors, identified during the content analysis, contribute to the causal path of policy adoption. Among other things, the results highlight the role that uncertainty plays in the policy process. Cities that adopt a drone use ordinance have low levels of uncertainty, high numbers of registered drone users, and at least two neighboring cities that also have drone use policies. This dissertation makes a modest contribution to policy innovation research, highlights how a configurational analysis technique can be applied to policy adoption decisions, and contains several recommendations for regulating drone use at the local level.