Diffuse threats : US counterterrorism as an anxious affective infrastructure

dc.contributor.advisorGunn, Joshua, 1973-
dc.contributor.advisorCloud, Dana L.
dc.contributor.committeeMemberDavis, Diane
dc.contributor.committeeMemberBrowne, Simone
dc.contributor.committeeMemberJarvis, Sharon
dc.contributor.committeeMemberBrummett, Barry
dc.creatorRitchie, Marnie Margaret
dc.creator.orcid0000-0002-0767-3326
dc.date.accessioned2018-10-17T14:37:35Z
dc.date.available2018-10-17T14:37:35Z
dc.date.created2018-08
dc.date.issued2018-10-09
dc.date.submittedAugust 2018
dc.date.updated2018-10-17T14:37:35Z
dc.description.abstractThe infrastructure of US national security has never been more bloated and obfuscatory, US leaders insist that terroristic threats have never been more real and dangerous, and the US War on Terror wages in more nations than ever before. Arguably since the color-coded Homeland Security Advisory System, our post-9/11 terrorism predicament tasks us with modulating our state of alertness to meet the level of mass threat. One of national and local threat rhetoric’s most important functions is to manage public anxiety surrounding the potential for rogue citizen and noncitizen terrorists to attack the homeland. This project isolates a new object of homeland security governance revealed by these affective manipulations: the diffusion of terroristic threats. Homeland security rhetoric manipulates public anxiety about threats’ capacity to spread. This project thus charts US counterterrorism as an affective infrastructure of anxiety. It defines an affective infrastructure of anxiety as a subterranean network of intermittent interruptions in sense. Within the past 14 years, a predominant rhetorical maneuver to counter threat diffusion has become intelligence fusion, defined as the conversion of public suspicions into actionable knowledge through the homeland security institution of the local “fusion center.” Through ethnographic interviews and observations, this project investigates the interoperations of fusion in Texas. The ethnography reveals a host of threat matrixes, pressure points, sore subjects, anguish, failures, stupidities, and surveillance measures that comprise the local and national anxious infrastructure of US counterterrorism. It shows that the rhetorical manipulation of anxiety is an essential component of local and national homeland security strategies. To attend to anxiety within intelligence fusion, this project develops a method for closely reading affect called “sleuthing.” This method reclaims both suspicion and close reading within the rhetorical tradition for the purpose of describing the extra-linguistic. Making space for affect in rhetorical theory is challenging but essential. Affect tasks us with rethinking fundamental postulations about the coherence of texts, the role of the responsible rhetorician, and the force of persuasion. Most importantly, affect theory can show how homeland security operates through racial phobia. This project represents the first full-length study of race, policing, and surveillance in the context of local intelligence fusion. The project’s goal is to read the far-reaching effects of homeland security’s newest transformations, especially considering recent intensifications in the War on Terror. To do so, one must see homeland security not just as a technical infrastructure but a quivering mass of connected affects.
dc.description.departmentCommunication Studies
dc.format.mimetypeapplication/pdf
dc.identifierdoi:10.15781/T2F766S31
dc.identifier.urihttp://hdl.handle.net/2152/68943
dc.subjectRhetoric
dc.subjectAffect
dc.subjectAnxiety
dc.subjectHomeland security
dc.subjectWar on Terror
dc.subjectIntelligence fusion
dc.subjectInfrastructures
dc.subjectClose reading
dc.subjectSleuthing
dc.titleDiffuse threats : US counterterrorism as an anxious affective infrastructure
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentCommunication Studies
thesis.degree.disciplineCommunication Studies
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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