The Impact of Surveillance Technology on the Behaviors Of

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The Impact of Surveillance Technology on the Behaviors Of THE IMPACT OF SURVEILLANCE TECHNOLOGY ON THE BEHAVIORS OF MUNICIPAL POLICE DEPARTMENTS Sinan Ulkemen, B.S., M.P.A. Dissertation Prepared for the Degree of DOCTOR OF PHILOSOPHY UNIVERSITY OF NORTH TEXAS December 2009 APPROVED: Robert L. Bland, Major Professor and Chair of the Department of Public Administration Simon A. Andrew, Committee Member Abraham D. Benavides, Committee Member Eric J. Fritsch, Committee Member Thomas L. Evenson, Dean of College of Public Affairs and Community Service Michael Monticino, Dean of the Robert B. Toulouse School of Graduate Studies Ulkemen, Sinan. The Impact of Surveillance Technology on the Behaviors of Municipal Police Departments. Doctor of Philosophy (Public Administration and Management), December 2009, 212 pages, 19 tables, references, 97 titles. Citizen complaints about inappropriate use of force indicate negative police- public relations, unresponsive police services, and the unresponsiveness of police management to citizens’ concerns. However, the effective delivery of key policing services depends on the performance of individual police officers. Surveillance technology can monitor and control the behavior of officers, ensuring that police officers provide high quality policing services that meet the needs of citizens. Examples of surveillance technology such as in-car cameras and CCTV can be used as an administrative tool to respond to citizen complaints by police chief executives. This research examines the effect of surveillance technology on the behavior of municipal police departments that is operationalized as the number of citizen complaints that were filed against municipal police departments. This research also examines the impact of surveillance technology on dismissed and sustained complaints by using 511 large municipal police departments in the U.S. from Law Enforcement Management and Administrative Statistics (LEMAS) 2003 dataset. Three different models are developed to evaluate the impact of in-car cameras and CCTV on the citizen complaints and their dispositions. Two ordinary least square regression (OLS) models and a Heckman selection model are used to analyze the data. The Heckman selection model is utilized to correct for selection bias in truncated data for sustained complaints after log transformation. The results suggest that the use of surveillance technology by the police is necessary, but insufficient, in reducing the number of complaints. The finding suggests that videotaped evidence, recorded by surveillance technology, increased the number of convictions of accused officers in municipal police departments. The analysis also suggests that municipal police departments that used CCTV only in 2003 received a higher number of citizen complaints, in comparison to municipal police departments without CCTV, both in 2000 and 2003. No evidence was found to indicate that surveillance technology has a positive impact on the percentage of dismissed complaints. Copyright 2009 by Sinan Ulkemen ii ACKNOWLEDGMENTS This study would not be possible without the scholarship awarded by the Turkish National Police. I would like to thank the Turkish National Police for giving me this opportunity to further my education and I thank the Turkish taxpayers for sponsoring my studies in the U.S. I would like to thank the members of my committee for sharing their time, expertise, and most importantly their patience with me. I owe a special thank to my chair Dr. Bob Bland, who was so kind leading me to correct directions. Also, his leadership was unique. I would also like to take this opportunity and express my deepest gratitude to Dr. Simon Andrew, whose continuous help and research skills made this research possible. I also thank Dr. Abraham Benavides and Dr. Eric Fritsch for their time and assistance. I thank Dr. Matthew J. Hickman for being available for my questions and for saving my time by sharing his dataset. I would like to extend my thanks the sworn officers with the municipal police departments of the U.S., Jimmy Perdue, Tom Woods, Michael Beutner, and Sean Kirk for their support and help in completing this study. I would also like to thank my mother for her encouragement, patience and assistance in my education and career. She came to the U.S. to support my studies. Finally, I would like to express my gratitude to my wife Ayse Gul, and to my children iii Asude and Hakan. Thank you for your love and I am appreciative of the sacrifices you made. iv TABLE OF CONTENTS Page LIST OF TABLES..................................................................................................... viii Chapter 1. INTRODUCTION TO STUDY ......................................................................... 1 Surveillance Technology and “Inappropriate Use of Force” Research Questions Conceptual Framework Significance of the Study Organization of Following Chapters 2. LITERATURE REVIEW................................................................................... 18 Introduction The Importance of Surveillance Technology in Law Enforcement Controlling the Behavior of Law Enforcement Officers and Police Accountability The Use of Surveillance Technology in Policing Closed-Circuit Television (CCTV) Video Cameras in Police Cars How Video Cameras in Patrol Cars Work The Rodney King Incident and the Christopher Commission The Effects of Surveillance Technology on the Behavior of both Citizen and Officers Ensuring Officers’ Compliance and In-Car Cameras Ensuring Citizens Compliance and In-Car Cameras Unintentional False Allegations Monitoring Versus Professionalism Limitations of In-Car Cameras in Predicting Police Misconduct Surveillance Technology Research The Research on Citizen Complaints about Police Abuse of Power Example Cases about Police Use of Inappropriate Force Theoretical Background Principal-Agent Theory v Routine Activity Theory Hypotheses Summary 3. METHODOLOGY ............................................................................................. 90 Research Design Data Sources Municipal Police Departments Model Specification Operationalization of the Variables Dependent Variable: Behavior of Municipal Police Departments Independent Variables: Surveillance Technology Control Variables: Organizational Structure, Administrative Controls, and Environmental Characteristics 4. DATA ANALYSIS AND DIAGNOSTIC TESTS ............................................ 121 Descriptive Statistics Dependent Variables Detecting Potential Selection Bias: Mean t-test Analysis of Heckman Selection Model Independent Variables Control Variables Comparing Usage of Surveillance Technology Experience of Municipal Police Departments with Usage of In-Car Cameras Correlation Coefficient 5. EMPIRICAL FINDINGS AND DISCUSSION ................................................ 147 The Impact of Surveillance Technology on Force Complaints Comparing Usage Categories of Surveillance Technology Experiences of Municipal Police Departments with Use of Surveillance Technology The Impact of Surveillance Technology on Dismissed Complaints The Impact of Surveillance Technology on Sustained Complaints Comparing Usage of Categories of Surveillance Technology Experiences of Municipal Police Departments vi with Use of Surveillance Technology Control Variables Organizational Factors Administrative Controls Environmental Factors Conclusion 6. CONCLUSION AND RECOMMENDATIONS .............................................. 185 General Findings and Discussion Major Contributions Limitations of the Study Recommendations for Future Research BIBLIOGRAPHY...................................................................................................... 205 vii LIST OF TABLES Table Page 3.1 Frequency Distribution of Law Enforcement Agencies ........................ 94 3.2 Operationalizing Municipal Police Department Behaviors: Frequency of Citizen Complaints and Dispositions ............................. 104 3.3 Municipal Police Departments Having Surveillance Cameras (Frequency, 2003) ................................................................. 107 3.4 Predicted Outcomes of the Association ................................................. 118 3.5 Variable Definition and Data Description ............................................. 119 4.1 Dependent Variables: Descriptive Statistics .......................................... 122 4.2 Comparing Mean Differences of Valid and Missing Cases: Citizen Complaints per 100 Officers (logged) ......................... 128 4.3 Comparing Mean Differences of Valid and Missing Cases: Percentage of Dismissed Citizen Complaints per .................... 129 4.4 Comparing Mean Differences of Valid and Missing Cases: Percentage of Sustained Citizen Complaints (logged) ............. 129 4.5 Descriptive Statistics ............................................................................. 133 4.6 Descriptive Statistics (Skewness and Kurtosis) ..................................... 134 4.7 Number of Police Departments with Surveillance Technologies by Types (2003) ............................................................. 138 viii 4.8 Comparing Frequency of Surveillance Technology Usage between 2000 and 2003 ............................................................ 141 4.9 Municipal Police Departments with In-car Cameras in 2000 and 2003 .................................................................................. 142 4.10 Municipal Police Departments with CCTV in 2000 and 2003 .............. 143 4.11 Correlation Matrix ................................................................................
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