Causes and Consequences of Police Militarization Edward Eugene Lawson, Jr
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University of South Carolina Scholar Commons Theses and Dissertations Spring 2019 Causes and Consequences of Police Militarization Edward Eugene Lawson, Jr. Follow this and additional works at: https://scholarcommons.sc.edu/etd Part of the Political Science Commons Recommended Citation Lawson, Jr., E. E.(2019). Causes and Consequences of Police Militarization. (Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/5152 This Open Access Dissertation is brought to you by Scholar Commons. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. CAUSES AND CONSEQUENCES OF POLICE MILITARIZATION by Edward Eugene Lawson, Jr. Bachelor of Arts University of South Carolina, Upstate 2013 Master of Arts University of South Carolina 2018 Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Political Science College of Arts and Sciences University of South Carolina 2019 Accepted by: Christopher Witko, Major Professor Susan Miller, Committee Member Kirk Randazzo, Committee Member John Burrow, Committee Member Cheryl L. Addy, Vice Provost and Dean of the Graduate School © Copyright by Edward Eugene Lawson, Jr., 2019 All Rights Reserved. ii ABSTRACT After the 2014 shooting of Michael Brown, and many other incidents of police violence that followed, the militarization of policing and the use of violence by police became the subjects of contentious debate among the public, policymakers, and scholars. Research on these subjects necessary to inform the debate has been lacking. This work examines the causes and effects of police militarization in the United States. Specifically, I argue that militarization is a response to perceived threat from minority racial groups, but the rela- tionship between racial demographics and militarization is curvilinear. Militarized begin to see themselves as soldiers fighting on the front line of a war rather than public servants, which causes goal divergence between the public and police. Although the public expects police to only use lethal force in extreme circumstances, militarized police use lethal force against civilians more quickly, resulting in more civilian deaths. Police departments should respond to more frequent civilian deaths by implementing policy solutions, such as body- worn cameras, that theoretically allow for easier monitoring of police behavior and over- come the principal-agent problem. iii TABLE OF CONTENTS ABSTRACT .................................... iii LIST OF TABLES .................................. vii LIST OF FIGURES ................................. x CHAPTER 1 INTRODUCTION ........................... 1 CHAPTER 2 A THEORY OF MILITARIZATION AND OPERATIONALIZATION OF MAJOR CONCEPTS .............................. 4 2.1 Introduction . 4 2.2 Defining Militarization . 5 2.3 A Theory of Militarization . 8 2.4 Measuring Militarization . 11 2.5 Tracking Civilian Deaths By Police . 14 2.6 Fatal Encounters: Crowdsourcing Civilian Deaths . 18 2.7 Figures . 22 CHAPTER 3 RACIAL THREAT AND CRITICAL MASS: A CURVILINEAR EFFECT OF RACE ON POLICE MILITARIZATION . 23 3.1 Introduction . 23 3.2 Racial Hierarchy and the Role of Police . 26 3.3 Racial Threat and Police Militarization . 29 iv 3.4 Critical Mass: a Non-Linear Effect of Racial Threat? . 33 3.5 Data and Methods . 36 3.6 Results . 43 3.7 Specific Tipping Point Mechanism . 45 3.8 Conclusion . 47 3.9 Tables . 50 3.10 Figures . 54 CHAPTER 4 POLICE MILITARIZATION AND THE USE OF LETHAL FORCE . 57 4.1 Introduction . 57 4.2 The Militarization of Police . 59 4.3 Police Militarization and Using Lethal Force . 62 4.4 Data and Methods . 66 4.5 Results . 73 4.6 Conclusion . 76 4.7 Tables . 78 4.8 Figures . 80 CHAPTER 5 WATCHING THE WATCHERS: POLICE VIOLENCE AND BODY-WORN CAMERAS 81 5.1 Introduction . 81 5.2 The Principal-Agent Problem of Police Violence . 84 5.3 Self-Awareness and Deterrence Constraining Police Behavior . 87 5.4 The State of Research on Body-Worn Cameras . 90 5.5 Data and Methods . 94 v 5.6 Results . 98 5.7 Conclusion . 101 5.8 Tables . 104 5.9 Figures . 107 CHAPTER 6 CONCLUSION ............................ 110 BIBLIOGRAPHY .................................. 113 APPENDIX A SUPPLEMENTAL MATERIALS FOR CHAPTER 3 . 135 A.1 Alternative Model Specifications . 135 A.2 Alternative DV Transformations . 136 A.3 Appendix A Tables . 138 APPENDIX B SUPPLEMENTAL MATERIALS FOR CHAPTER 4 . 148 B.1 Alternative Transformation of Militarization . 148 B.2 Alternative Model Specifications . 150 B.3 Endogeneity . 151 B.4 Alternative Time Scale . 152 B.5 Appendix B Tables . 153 APPENDIX C SUPPLEMENTAL MATERIALS FOR CHAPTER 5 . 168 C.1 Alternative Model Specifications - Hypothesis 1 . 168 C.2 Alternative Model Specifications - Hypothesis 2 . 169 C.3 Appendix C Tables . 171 vi LIST OF TABLES Table 3.1 Chapter 3 Summary Statistics . 50 Table 3.2 ZINB Regressions, General Threat model . 51 Table 3.3 ZINB Regressions, Specific Threat model . 52 Table 3.4 Tests of Specific Threat Mechanisms . 53 Table 4.1 Chapter 4 Summary Statistics . 78 Table 4.2 ZINB Regression, effect of militarization on deaths . 79 Table 5.1 Chapter 5 Summary Statistics . 104 Table 5.2 Heckman Probit, effect of deaths on probability of applying for grant . 105 Table 5.3 NB Regression, effect of receiving grant on future deaths . 106 Table A.1 NB Regressions, General and Specific Threat models . 138 Table A.2 Poisson Regressions, General and Specific Threat models . 139 Table A.3 ZIP Regression, General Threat model . 140 Table A.4 ZIP Regression, Specific Threat model . 141 Table A.5 Hurdle Regression, General Threat model . 142 Table A.6 Hurdle Regression, Specific Threat model . 143 Table A.7 OLS Regressions, General and Specific Threat models . 144 Table A.8 Logit with binary militarization dependent variable . 145 Table A.9 OLS Regressions with logged militarization dependent variable . 146 vii Table A.10 NB Regressions, General threat model only . 147 Table B.1 ZINB Regression with natural log of militarization . 153 Table B.2 ZINB Regression with the total number of items received . 154 Table B.3 ZINB Regression, received high value item as militarization . 155 Table B.4 ZINB Regression, received high-value item (alternative level) as mil- itarization . 156 Table B.5 ZINB Regression with the total number of items received and a high- value item dummy variable . 157 Table B.6 ZINB Regression with the total number of items received and an al- ternate high-value item dummy variable . 158 Table B.7 ZINB Regression with SWAT team dummy variable . 159 Table B.8 NB Regression, effect of militarization on civilian deaths . 160 Table B.9 ZIP Regression, effect of militarization on civilian deaths . 161 Table B.10 Poisson Regression, effect of militarization on civilian deaths . 162 Table B.11 Regression with two-way random effects, effect of militarization on civilian deaths . 163 Table B.12 OLS Regression, effect of militarization on civilian deaths . 164 Table B.13 OLS Regression, effect of civilian deaths on future militarization . 165 Table B.14 Regression with two-way random effects, effect of civilian deaths on future militarization . 166 Table B.15 ZINB Regression with annual averages . 167 Table C.1 Scobit Regression, effect of deaths on probability of receiving grant, uncensored observations only . 171 Table C.2 Logit Regression, effect of deaths on probability of receiving grant, uncensored observations only . 172 viii Table C.3 Probit Regression, effect of deaths on probability of receiving grant, uncensored observations only . 173 Table C.4 Logit Regression, effect of deaths on probability of receiving grant, all observations . 174 Table C.5 Probit Regression, effect of deaths on probability of receiving grant, all observations . 175 Table C.6 Logit Regression, effect of deaths on probability of applying for grant . 176 Table C.7 Probit Regression, effect of deaths on probability of applying for grant . 177 Table C.8 Poisson Regression, effect of receiving grant on future deaths . 178 Table C.9 ZINB Regression, effect of receiving grant on future deaths . 179 Table C.10 ZIP Regression, effect of receiving grant on future deaths . 180 Table C.11 NB Regression, effect of receiving grant on future deaths, uncensored observations only . 181 Table C.12 Poisson Regression, effect of receiving grant on future deaths, uncen- sored observations only . 182 ix LIST OF FIGURES Figure 2.1 Total value of military hardware received by law enforcement agen- cies (in 10,000 2016 dollars) . 22 Figure 3.1 Predicted militarization (in 10,000s) by percent Non-White . 54 Figure 3.2 Predicted militarization (in 10,000s) by percent Black . 55 Figure 3.3 Predicted militarization (in 10,000s) by percent Latino/a . 56 Figure 4.1 Predicted number of suspect deaths at varying levels of militariza- tion, with 95% confidence intervals (in gray). 80 Figure 5.1 Marginal effects of variables on Pr(Applied) . 107 Figure 5.2 Marginal effects of variables on Pr(Received | Applied) . 108 Figure 5.3 Average civilian deaths, by grant status, 2014-2016 . 109 x CHAPTER 1 INTRODUCTION In August, 2014, a police officer in Ferguson, MO, outside St. Louis, shot and killed 18 year old Michael Brown, who was unarmed and reportedly had his hands in the air when the officer shot him multiple times (“Angry crowd gathers after Missouri police shoot teen” 2014). Protesters took to the streets after the shooting to demonstrate their disapproval of what they seemed to believe was an incident of excessive force by a police officer. Later, a grand jury refused to indict the officer for any crimes (Desmond-Harris and Lind 2014). Even now, five years later, the details of what precipitated the shooting remain unclear, but the incident brought the topics of police militarization and use of force to the forefront of public discussion. Michael Brown’s death inspired a national movement advocating police reform (Sanburn 2014)..