Masterarbeit, 2019
89 Seiten, Note: A*
This Master's Thesis aims to explore the opportunities and challenges of implementing predictive policing technologies in German police institutions. It investigates the theoretical foundations of predictive policing methods, examines their practical application in Germany, and compares German approaches with those in the USA. The empirical part uses expert interviews to analyze the real-world implications of these technologies.
1 INTRODUCTION: This introductory chapter sets the stage for the thesis by discussing the changing landscape of criminal prosecution in the age of big data. It establishes the context of predictive policing within German law enforcement, highlighting the current state of research and the motivations behind the research question. The chapter concludes by outlining the structure of the thesis.
2 THEORETICAL BACKGROUND: This chapter delves into the theoretical underpinnings of predictive policing. It defines key terminology, explores the objectives and applications of these technologies, and traces the chronological development of policing strategies, comparing Germany's approach to that of the USA. A significant portion is dedicated to explaining the core techniques used in predictive policing: Hot-Spot techniques, Near-Repeat approaches, and Risk-Terrain Analysis. The chapter provides a comprehensive overview of the theoretical framework upon which the empirical research is based.
3 EMPIRICAL WORK: This chapter details the empirical methodology employed in the thesis. It outlines the use of guided expert interviews as the primary data collection method, describing the qualitative implementation, participant selection, and the hypothesis-testing framework. The chapter explains in detail the process of data collection and the methodological choices made to ensure the rigor and reliability of the research findings. The adapted category scheme of Meuser and Nagel for evaluating the interview results is also discussed.
4 DISCUSSION: OPPORTUNITIES AND CHALLENGES: This chapter presents the interpretation of the results obtained from the expert interviews. It addresses the research question directly, outlining both the opportunities and challenges related to the implementation of predictive policing in Germany. The analysis focuses on the practical implications and societal impact of these technologies, considering potential benefits and drawbacks.
Predictive Policing, crime prevention, data analysis, forecasting technology, Hot-Spot policing, Near-Repeat analysis, Risk-Terrain Modeling, qualitative research, expert interviews, Germany, USA, opportunities, challenges, Big Data, policing strategies, ethical considerations.
This Master's Thesis explores the opportunities and challenges of implementing predictive policing technologies within German police institutions. It investigates the theoretical foundations, practical application in Germany, compares German and US approaches, and analyzes real-world implications using expert interviews.
Key themes include the theoretical foundations of predictive policing techniques (Hot-Spot, Near-Repeat, Risk-Terrain Analysis), the application and implementation of predictive policing in German police forces, a comparison of approaches in Germany and the USA, and an analysis of the opportunities and challenges associated with its use in Germany, including expert opinions on effectiveness and societal impact.
The thesis is structured into four chapters: 1. Introduction (setting the context and research question), 2. Theoretical Background (defining terminology, exploring objectives and applications, and comparing German and US approaches), 3. Empirical Work (detailing the methodology of guided expert interviews and data analysis), and 4. Discussion: Opportunities and Challenges (interpreting results, answering the research question, and outlining opportunities and challenges).
The empirical research utilized guided expert interviews as the primary data collection method. The chapter details the qualitative implementation, participant selection, hypothesis-testing framework, and methodological choices to ensure rigor and reliability. The adapted category scheme of Meuser and Nagel for evaluating interview results is also discussed.
The thesis presents an interpretation of results from expert interviews, directly addressing the research question by outlining both the opportunities and challenges related to implementing predictive policing in Germany. The analysis focuses on practical implications and societal impact, considering potential benefits and drawbacks.
Key terms include Predictive Policing, crime prevention, data analysis, forecasting technology, Hot-Spot policing, Near-Repeat analysis, Risk-Terrain Modeling, qualitative research, expert interviews, Germany, USA, opportunities, challenges, Big Data, policing strategies, and ethical considerations.
The thesis contributes to the understanding of predictive policing implementation in a specific context (Germany), comparing it to a well-established system (USA), and providing a nuanced perspective on the opportunities and challenges of such technologies, incorporating real-world expert opinions.
Further details on this research can be found within the full text of the Master's Thesis itself (access details would need to be provided separately).
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