Systematic Social Observation of the Police in the 21st Century 3031314816, 9783031314810

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SpringerBriefs in Criminology John McCluskey · Craig D. Uchida · Yinthe Feys · Shellie E. Solomon

Systematic Social Observation of the Police in the 21st Century

SpringerBriefs in Criminology

SpringerBriefs in Criminology present concise summaries of cutting edge research across the fields of Criminology and Criminal Justice. It publishes small but impactful volumes of between 50-125 pages, with a clearly defined focus. The series covers a broad range of Criminology research from experimental design and methods, to brief reports and regional studies, to policy-related applications. The scope of the series spans the whole field of Criminology and Criminal Justice, with an aim to be on the leading edge and continue to advance research. The series will be international and cross-disciplinary, including a broad array of topics, including juvenile delinquency, policing, crime prevention, terrorism research, crime and place, quantitative methods, experimental research in criminology, research design and analysis, forensic science, crime prevention, victimology, criminal justice systems, psychology of law, and explanations for criminal behavior. SpringerBriefs in Criminology will be of interest to a broad range of researchers and practitioners working in Criminology and Criminal Justice Research and in related academic fields such as Sociology, Psychology, Public Health, Economics and Political Science.

John McCluskey • Craig D. Uchida Yinthe Feys • Shellie E. Solomon

Systematic Social Observation of the Police in the 21st Century

John McCluskey Department of Criminal Justice Rochester Institute of Technology Rochester, NY, USA Yinthe Feys Faculty of Law and Criminology Ghent University Ghent, Belgium

Craig D. Uchida Justice and Security Strategies, Inc. Manhattan Beach, CA, USA Shellie E. Solomon Justice and Security Strategies, Inc. Hollywood, FL, USA

ISSN 2192-8533     ISSN 2192-8541 (electronic) SpringerBriefs in Criminology ISBN 978-3-031-31481-0    ISBN 978-3-031-31482-7 (eBook) https://doi.org/10.1007/978-3-031-31482-7 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

From February 3 to February 5, 2020, Dr. John McCluskey was invited to provide a three-day lecture on the application of systematic social observation (SSO) methodology in Ghent, Belgium. This course was co-organized by Dra. Yinthe Feys as there was a lack of observational courses in the doctoral training program. This course allowed Yinthe to receive proper training in SSOs and set up her own SSO project as part of her PhD. In the academic literature, a comprehensive and clear overview of the SSO method was lacking at the time of the aforementioned SSO project. To fill this gap, Yinthe took the initiative to write an academic article on this matter, outlining the different steps to be taken in such a project. She then contacted Dr. McCluskey to collaborate on this, resulting in discussions on what to include in such an overview and which format to publish it in. Eventually, this resulted in a productive collaboration that expanded to include Drs. Craig Uchida and Shellie Solomon, also experts in SSO methodology. A SpringerBriefs book was considered the perfect outlet for our ideas and thoughts. This book outlines the history of SSO, its advantages and disadvantages, and the type of research projects that fit with the method. A number of chapters focus on different modalities of SSO (i.e., in-person SSO and image or video-based SSO) and the application of SSO to place-based criminology. A compelling discussion regarding the future of SSO research and policing is provided at the end of this SpringerBriefs. Throughout the book, tips and tricks concerning how to prepare for, perform, and report on SSO are provided. Overall, we believe this book adds value to the current literature as there is currently no overview offering a detailed and systematic overview of the current state-of-the-art on SSOs. This work offers clear guidance on the different steps to be taken when performing SSOs and reference from which

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Preface

potential users may launch further inquiry into the details and commitments required for a successful SSO project. Rochester, NY, USA Manhattan Beach, CA, USA Ghent, Belgium Hollywood, FL, USA

John McCluskey Craig D. Uchida Yinthe Feys Shellie E. Solomon

Acknowledgments

This book could not have been accomplished without the help of many different persons. Colleagues have offered help and insights which inform this book in several ways. In 2020, Drs. David Makin and Dale Willits provided insights into their ongoing work at Washington State University using body-camera footage as data and sparked our interest in codifying lessons learned for the larger field. Drs. William Terrill and Logan Somers generously lent time to a structured conversation regarding their experiences in coding sequential use of force data from videos in a project at Arizona State University. Drs. Robert Worden and Sarah McLean, along with Hannah Cochran and Beau Holladay, offered insights from their experiences with data coded in a large-scale project studying supervision and procedural justice at the Finn Institute in Albany, NY. Drs. Oral “Nick” Robertson and Cynthia Perez McCluskey read drafts of chapters and offered editorial and substantive comment throughout the project. John McCluskey’s work on this project was supported in part by the RIT Paul A. and Francena L.  Miller Research Fellowship from the College of Liberal Arts. We wish to thank Prof. Dr. Antoinette Verhage (Ghent University), as Yinthe Fey’s supervisor, for supporting the application of the SSO method in her PhD and providing feedback on the how-to chapter of this book. For Dr. Uchida, the in-person and video-based systematic social observations in the Los Angeles Police Department (LAPD) were conducted with the unwavering support of Chief Charlie Beck, Chief Information Officer Maggie Goodrich, and Deputy Chief Sean Malinowski (all retired at this time). We also thank our funders for this effort: The Bureau of Justice Assistance (Grant No. 2019-BC-BX-K001) awarded to the CNA Corporation with Justice & Security Strategies, Inc. (JSS) and Arizona State University (ASU) as sub-recipients and the National Institute of Justice (Grant No. 2014-R2-CX-0101). BJA and NIJ are components of the U.S. Department of Justice Office of Justice Programs. Points of view or opinions contained herein do not necessarily represent the official position or policies of the U.S. Department of Justice.

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Acknowledgments

For Dr. Solomon, she would like to acknowledge the contributions of her dissertation advisors, Dr. Hans Nelen, Dr. Cathal O’Donoghue, Dr. Franziska Gassmann, and Dr. Mindel van de Laar from the United Nations University  – Maastricht Economic and Social Research Institute on Innovation and Technology. Funding for the environment-based systematic social observations was provided by The Children’s Trust of Miami Dade County. Special thanks to Modesto Abety and Dr. K. Lori Hanson of The Children's Trust and Betty Alonso at ConnectFamilias.

Overview

This book focuses on systematic social observation (SSO) methodology by identifying the different steps to be undertaken when performing SSO (a how-to-guide), its benefits and disadvantages, challenges associated with using SSO, when to use it, etc. Discussions are provided on different aspects related to the method (e.g., access to the field or footage), including ethical considerations. After outlining the history of SSO in police research and criminology, the general features of the method are discussed, outlining when SSOs can be a useful addition to other research methods. We then focus on three different modalities of SSO research: in-­ person SSO (IPSSO), video-based SSO (VBSSO), and environment-based SSO (EBSSO). Clear guidance is provided on the different steps to be taken in an SSO project, from preparing such a project to finally reporting about it. Comparisons between IPSSO and VBSSO are provided. The concluding chapter sets forth a discussion of the future of SSO methodology in terms of technology and possible reach into new questions for criminal justice, criminology, and police managers. The primary audience of this book are researchers and students interested in conducting SSO; however, we would argue that police departments, as learning organizations, could benefit from launching SSO projects to answer important questions aimed, for example, at understanding how officers handle certain situations, or how training affects the handling of situations. A detailed presentation of the method and the steps it involves is currently absent in the literature. This book fills this gap and aids researchers in understanding choices and tradeoffs when conducting SSOs. It will also assist researchers in outlining their research frame (e.g., research questions, in person SSO vs. VBSSO). Finally, given the burgeoning proliferation of body-worn cameras, the book introduces researchers to this new tool for launching inquiries in policing using SSO-­ derived research techniques.

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Contents

1

Introduction����������������������������������������������������������������������������������������������    1 1.1 The Current State of Policing and Police Research��������������������������    1 1.1.1 What We Don’t Know About Policing����������������������������������    1 1.1.2 Back to the Future����������������������������������������������������������������    2 1.2 An Overview of the Text������������������������������������������������������������������    3 1.2.1 The SSO Method in Context������������������������������������������������    3 1.2.2 The Logic and Flow of the Monograph��������������������������������    4 References��������������������������������������������������������������������������������������������������    5

2

 The SSO Method in Police Research and Criminology������������������������    7 2.1 Introduction��������������������������������������������������������������������������������������    7 2.2 Origins and Context for SSO������������������������������������������������������������    7 2.3 Definition of SSO������������������������������������������������������������������������������    9 2.4 Major Studies Using SSO ����������������������������������������������������������������    9 2.5 Trends in Police-Based SSO Research: Using Technology��������������   10 2.6 SSO of Neighborhoods and Places ��������������������������������������������������   11 2.7 Linking EBSSO to Theories of Crime and Police Behavior������������   13 2.8 Conclusion����������������������������������������������������������������������������������������   14 References��������������������������������������������������������������������������������������������������   14

3

Developing and Conducting an SSO Study: A How-to-Guide for Social Science Research ��������������������������������������������������������������������   17 3.1 Determining the Research Frame������������������������������������������������������   17 3.1.1 Research Topic and Context�������������������������������������������������   17 3.1.2 Methodology ������������������������������������������������������������������������   20 3.2 Practical Preparation ������������������������������������������������������������������������   21 3.2.1 Cooperation and Agreements������������������������������������������������   21 3.2.2 Ethical Clearance������������������������������������������������������������������   22 3.3 Preparing Fieldwork: Instruments and Training ������������������������������   25 3.3.1 Codebook and Procedures����������������������������������������������������   26 3.3.2 Training��������������������������������������������������������������������������������   30 3.4 Piloting����������������������������������������������������������������������������������������������   31 xi

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3.5 Collecting Data ��������������������������������������������������������������������������������   32 3.5.1 Planning and Sampling ��������������������������������������������������������   32 3.5.2 Taking Notes ������������������������������������������������������������������������   34 3.5.3 Debriefing ����������������������������������������������������������������������������   36 3.5.4 Leaving the Field������������������������������������������������������������������   37 3.6 Processing Data��������������������������������������������������������������������������������   38 3.6.1 Creating Narratives ��������������������������������������������������������������   39 3.6.2 Coding����������������������������������������������������������������������������������   40 3.7 Analyzing Data ��������������������������������������������������������������������������������   41 3.8 Reporting Findings���������������������������������������������������������������������������   42 3.9 Conclusion����������������������������������������������������������������������������������������   43 References��������������������������������������������������������������������������������������������������   44 4

 Video-Based SSO and Body-Camera Data��������������������������������������������   47 4.1 Data Sources for VBSSO������������������������������������������������������������������   48 4.1.1 Camera Perspectives and Public Data����������������������������������   48 4.1.2 Police BWC Video as Data ��������������������������������������������������   49 4.2 Establishing File Processing Behind Departmental BWC Archives��������������������������������������������������������������������������������������������   50 4.2.1 Aspects of BWC Archival Management That May Lead to Missing or Incomplete Data������������������������������������   50 4.2.2 Identification Approaches to Ascertain BWC Available Within an Archive ����������������������������������������������������������������   52 4.3 Sampling Strategies��������������������������������������������������������������������������   53 4.3.1 Current Research Approaches����������������������������������������������   53 4.3.2 Possible Sampling Strategies������������������������������������������������   54 4.3.3 Machine Learning and Prospective Augmentation of Sampling Approaches ������������������������������������������������������   55 4.4 Access Locations and Human Subjects Protection��������������������������   56 4.4.1 Data Access��������������������������������������������������������������������������   56 4.4.2 Human Subject Protections and Institutional Review����������   57 4.5 Code Development, Training, Unit of Analysis, and Issues of Reliability������������������������������������������������������������������������������������������   58 4.5.1 Code Development and Training������������������������������������������   58 4.5.2 Units of Analysis and Coding Patterns ��������������������������������   59 4.5.3 Training, Reliability of Codes, and Reliability of Coders������������������������������������������������������������������������������   61 4.5.4 Coder Over-Identification ����������������������������������������������������   62 4.6 A Comparison of VBSSO and IPSSO����������������������������������������������   63 4.6.1 Video and Audio Channel Adequacy as a Record of “What Happened?” ����������������������������������������������������������   63 4.6.2 Comparing IPSSO and VBSSO in Terms of Evidentiary Coding Items������������������������������������������������   64

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4.7 Example of a General Data and Sampling Plan to Address a Research Question��������������������������������������������������������������������������   66 4.7.1 The Context for a Multi-organization Study of De-escalation Using VBSSO��������������������������������������������   66 4.7.2 Enumerating Police–Citizen Contacts for Sampling Uses of Force������������������������������������������������������������������������   67 4.7.3 Enumerating Police–Citizen Contacts for Cases That Have a Likelihood of Force Usage���������������������������������������   68 4.7.4 Enumerating Police–Citizen Contacts for Cases with a Very Low Likelihood of Force Usage������������������������   68 4.7.5 Project Technology ��������������������������������������������������������������   69 4.8 Conclusion����������������������������������������������������������������������������������������   70 References��������������������������������������������������������������������������������������������������   72 5

 Environment-Based Systematic Social Observation and Police Research����������������������������������������������������������������������������������������������������   75 5.1 Introduction��������������������������������������������������������������������������������������   75 5.2 Neighborhood Context, Definition, and Units of Analysis ��������������   77 5.2.1 Neighborhood Definitions����������������������������������������������������   77 5.2.2 Units of Analysis and Identification of Areas to Study��������   78 5.3 Theory and Purpose of EBSSO��������������������������������������������������������   79 5.3.1 Theory of EBSSO ����������������������������������������������������������������   79 5.3.2 Measuring Physical and Social Disorder������������������������������   80 5.4 Research Approach ��������������������������������������������������������������������������   82 5.4.1 Development and Testing Codebooks for EBSSO����������������   82 5.4.2 Institutional Review Board and Confidentiality��������������������   84 5.5 Preparing for Fieldwork��������������������������������������������������������������������   84 5.5.1 Piloting����������������������������������������������������������������������������������   85 5.5.2 Choosing the Unit of Analysis����������������������������������������������   85 5.5.3 Coding Norms and Validation����������������������������������������������   86 5.5.4 Launching ����������������������������������������������������������������������������   86 5.5.5 Sampling ������������������������������������������������������������������������������   86 5.6 Hiring, Training, and Assessing Observers��������������������������������������   87 5.6.1 Hiring Observers������������������������������������������������������������������   87 5.6.2 Training��������������������������������������������������������������������������������   88 5.6.3 Advising the Authorities ������������������������������������������������������   88 5.7 Strategies for Observer Deployment and Technology����������������������   89 5.7.1 Unaccompanied Project Observers ��������������������������������������   89 5.7.2 Community Leader Involvement������������������������������������������   89 5.7.3 Law Enforcement Involvement��������������������������������������������   90 5.7.4 Driving����������������������������������������������������������������������������������   90 5.7.5 Collecting Data ��������������������������������������������������������������������   91 5.7.6 Taking Additional Notes ������������������������������������������������������   91 5.7.7 Taking Pictures and Videos��������������������������������������������������   92 5.7.8 Engagement in the Field ������������������������������������������������������   92

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5.8 Final Data Collection Efforts������������������������������������������������������������   93 5.8.1 Debriefing ����������������������������������������������������������������������������   93 5.8.2 Processing the Data��������������������������������������������������������������   93 5.8.3 Creating the Narratives ��������������������������������������������������������   93 5.8.4 Reporting Findings ��������������������������������������������������������������   94 5.9 Summary ������������������������������������������������������������������������������������������   94 References��������������������������������������������������������������������������������������������������   95 6

 The Future of Systematic Social Observation and Policing ����������������   97 6.1 New Technology and SSO����������������������������������������������������������������   97 6.1.1 Field Observations and Emerging Technology ��������������������   97 6.1.2 Integrating Machine Learning and VBSSO��������������������������   97 6.1.3 Environment-Based SSO and Machine Learning ����������������   98 6.2 Comparative Research via SSO��������������������������������������������������������   99 6.2.1 Organizational Comparisons������������������������������������������������   99 6.2.2 International Comparative Research������������������������������������   99 6.3 Theoretical Advances and New Insights ������������������������������������������  100 6.3.1 Assessing the Effectiveness of Police Supervision��������������  100 6.3.2 Training and Behavioral Changes����������������������������������������  101 6.3.3 The Context of Police Service Delivery�������������������������������  102 6.4 Concluding Thoughts on SSO����������������������������������������������������������  102 6.4.1 Cooperation��������������������������������������������������������������������������  102 6.4.2 Replication����������������������������������������������������������������������������  103 References��������������������������������������������������������������������������������������������������  103

Index������������������������������������������������������������������������������������������������������������������  105

Abbreviations

AI BOSS-D CV EBSSO FLETC IPSSO IRB LAPD LAPD-PJ ML RMS RPD SSO VDA VBSSO

Artificial Intelligence Belgian Observation and Systematic Study of Decisions Computer Vision Environment-based SSO Federal Law Enforcement Training Center In-person SSO Institutional Review Board Los Angeles Police Department Los Angeles Police Department Procedural Justice Study Machine Learning Records Management System Rochester Police Department (New York) Systematic Social Observation Video Data Analysis Video-based Systematic Social Observation

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Chapter 1

Introduction

Contemporary policing is in crisis in many countries, few more so than the United States, given civil disturbances experienced in many of its cities during the spring and summer of 2020. This comes on the heels of a large-scale effort to equip police with body-worn cameras (BWCs) with the aim of increasing accountability and transparency of what police do (White & Malm, 2020). That effort came about largely as response to the killing of Michael Brown in Ferguson, MO in 2014. Ironically, the BWC as well as civilian cell phones have uncovered officer misbehavior numerous times since widespread adoption and deployment, the most recent at this writing being the killing of Tyre Nichols in Memphis, TN.

1.1 The Current State of Policing and Police Research 1.1.1 What We Don’t Know About Policing Sadly, we now too often see police killings of civilians in the United States, where this happens at least 1000 times per year, as a video presentation by a department releasing curated footage on YouTube, or in the case of Tyre Nichols’ homicide, on the VIMEO platform. The Los Angeles Police Department (LAPD) has released footage on more than 100 officer-involved shootings and critical incidents on its YouTube channel since they were mandated to do so in 2018. What has changed? The public, politicians, and police managers have widespread access to police applications of lethal violence, with very few depictions of police work available that might document other aspects of work and behavior. With more than 53 million annual contacts estimated to occur between the police and members of the public aged 16 and older, we know very little about what happens in those cases (Tapp & Davis, 2022).

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. McCluskey et al., Systematic Social Observation of the Police in the 21st Century, SpringerBriefs in Criminology, https://doi.org/10.1007/978-3-031-31482-7_1

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It is against this backdrop, which in some ways adds a very violent overlay on top of our general ignorance of what police do and how they do it, that we write this book. This state of affairs is concerning as the public conversation around de-­ escalation, for example, has been one that is based on a sliver of information about what the police do (cf. Todak & James, 2018; Engel et al., 2022). Will a twenty-first century research agenda allow us to learn more about what police do and how they do it? Can we develop a systematic knowledge-base to aid in improving policing? Will new insights be drawn from the deployment of expensive camera technology? Our answer to these questions is yes. We can deploy a research agenda that allows for a more widely distributed knowledge-base that can offer the public, police, and policymakers some insights, and at least partially that agenda will be driven by data captured by BWC in the United States. Paradoxically, we will have to reach back to a police pioneer who eschewed ethnography and official police records for systematic observation (SSO) of the police and combined his insights with those of the BWC revolution. Further, though thus far we have focused on the United States, the research program suggested here is one that is ripe for comparative and international deployment. Observation of the police, early ethnography included, progressing to in-person SSO (IPSSO) and more recently to video-based SSO (VBSSO) has done much to enrich our understanding of policing, and this text is an attempt to move that research forward (Brunson & Miller, 2023).

1.1.2 Back to the Future In 1971, The Police and the Public made its debut. This seminal work by Albert J. Reiss, Jr. was the first book to describe how police officers interacted with citizens based on independent observations by trained researchers using SSO. The method of SSO as designed and implemented by Reiss uncovered a whole new world for police research, one that used a qualitative approach but quantified the behavior of police. Wilson (1968), Skolnick (1966), Muir (1977), and others described the nuances of policing (e.g., discretion, varieties of behavior, and citizen interactions). But they based their work on interviews, ethnographic techniques, and official police data that provided a partial picture of what the police did, but with substantial gaps. This is very much like the contemporary state of police research. Reiss, through SSO, was able to capture a fuller portrait of police work, de-bunk myths, and create new language about police and their work. Based on work in Chicago, Washington, D.C., and Boston in the late 1960s, he demonstrated, for example, that police officers rarely made arrests (one per shift) and that police demeanor was affected by the citizen’s attitude. He coined the word “proactive” to describe actions by police that were self-initiated – a term that is now commonly used not only by the police but is used in everyday language to describe behavior by individuals and organizations. This technique of observing behavior in the natural setting is still being used by police researchers to understand how and whether the procedural justice of police

1.2  An Overview of the Text

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encounters changes with the introduction of police BWC (McCluskey et al., 2019). But technology is opening new fronts for the examination of police behavior, as departments like the LAPD now have vast libraries, estimated to be up to 400,000 h of footage from 2019 alone, of video recordings of police–citizen contacts (Uchida & Anderson, 2021). These new data sources raise questions that we address here: For what research questions and locations is IPSSO still a feasible approach to learning about what the police do and how they make decisions? What can be done with these BWC data? Can the fields of criminal justice, criminology, and sociology develop a new science around BWC as an emerging data source?

1.2 An Overview of the Text 1.2.1 The SSO Method in Context The tradition of SSO has been carried on since the 1960s and has a longer history in social science outside of policing research (Brunson & Miller, 2023). Reiss’ (1971) method of creating predefined protocols for observation; training observers; sampling observable units, often in the form of police shifts; and coding characteristics of the police–citizen encounter are now familiar to many students of criminology, criminal justice, and policing. For those of us who had the good fortune to work with him (McCluskey and Uchida), we learned firsthand that taking notes during a ride-along and then writing a narrative afterward were critical parts of SSO. His proclivity for capturing the essence of mundane ride-alongs in simple prose brought life to his work and made for fascinating storytelling. Major follow-on studies by Ostrom et al. (1977) and Mastrofski et al. (2007), as well as dozens of smaller scale studies of policing (e.g., Worden & McLean, 2014), have contributed substantially to theoretical grist for academic theories and insights for police managers. In the first quarter of the twenty-first century, there was a re-emergence of SSO, now often through the medium of recorded video, reducing the need for in-person observation to explore many questions beyond policing, such as how robbers approach convenience store robbery (Nassauer, 2018) and the sequencing of open-­ air drug selling (Sytsma & Piza, 2018). This approach to the study of policing is especially feasible in the United States, where BWC are widely adopted, as of 2023, across a majority of police agencies. Further, state and federal officials are actively engaging in funding, training, and technical assistance to increase the number of organizations adopting the technology (Uchida & Anderson, 2021). In the EU, however, access to such footage is less forthcoming due to privacy rules and limited usage, and perhaps the continued value of in-person SSO (IPSSO) of the police cannot be ignored under such restrictions on use and access. Beyond the observation of the police and their activities, there is a nagging question regarding variations correlated with where police–citizen contact occurs (Smith, 1986; Reisig & Parks, 2000; Mastrofski et  al., 2002). Linking characteristics of

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places to encounters between the police and citizens, in the form of ecometrics (Raudenbush & Sampson, 1997), is amenable to in-person and visual-archive data that can provide a background for coding. Exploring and documenting variation across areal units, in our judgment, is an important area where SSO techniques can be harnessed to help inform the public and police managers of what the police do and where they do it.

1.2.2 The Logic and Flow of the Monograph Because of the emerging use cases of SSO with respect to policing, we have written a short how-to manual as a starting point for interested researchers or police managers. In no way can we specify a complete project, but we aim to offer those curious and interested a comprehensive first source that will link to important questions and decisions one might make in launching an SSO project. This will include outlining steps in planning, execution, consideration of technological choices that researchers may make, and reference to key research exemplars and protocols to offer a starting point. We forgo specific suggestions regarding analytical approaches one may take, once data are assembled in machine-readable form, since that will be heavily dependent on theoretical frameworks, units of analysis, and measurement levels of variables and beyond the scope of this monograph. Where possible we refer back to our own or colleagues’ experiences as they have endured the difficulties of field work, mistakes, false starts, and inevitable reworking of project materials. Recommendations regarding planning and access to police organizations draw on insights derived from several research teams. Their work in the field spans decades, as do the authors’ own experiences regarding the navigation of relationships with police organizations. Tradeoffs on the modality of police observation will be considered in two chapters focusing on in-person SSO and the conduct of video-­ based SSO. Further, we might not restrict such an SSO to an academic approach to policing, but instead we would argue that, especially in larger police agencies, officers could be trained to code colleagues’ video and provide a basis for the understanding of local or regional patterns in the delivery of service to the public. This would be especially beneficial if common instrumentation were to be developed. In at least one instance, a research team at Washington State University is beginning to deploy such an approach to capture a generalizable measure of “police professionalism.” The reader is welcome to jump into any particular chapter of interest, but a review of the entire text should not be overly onerous and maps as follows. In Chap. 2, we consider SSO in its larger historical sweep. How did it originate? What new evidence was developed in policing that is unique to the method? Next, in Chap. 3, the practical application of in-person SSO is considered. What choices should a researcher prepare to confront in navigating access, developing codebooks, sampling units for observation, and conducting the fieldwork? In Chap. 4, we discuss video-based SSO (VBSSO) and its rapid emergence in the United States. Here,

References

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approaches to sampling video, the difficulties of working with video, and the contrast with IPSSO in terms of expense and assessable reliability are among the facets considered. This draws upon insights, suggestions, and cautions from structured conversations with research teams from the Finn Institute, led by Robert Worden, and Arizona State University, led by William Terrill, as well as previous conversations with David Makin and Dale Willits from the Washington State University Complex Social Interactions lab. Chapter 5 is an overview of environment-based SSO (EBSSO) as a methodology for enhancing policing in the twenty-first century. Data collection via EBSSO offers utility as a possible outcome measure, such as change in neighborhood disorder subsequent to an intervention, as well as a contextual measure which could possibly condition police behavior. We present a brief history of the technique, then chart the logic of workflow and how researchers might answer questions about: the selection of sites, development of samples, creation of codes and codebooks, and hiring, training, and deploying observers. Exemplars from the authors’ extensive field experience with EBSSOs are presented to offer insight into how decisions are made and the costs, benefits, and overall tradeoffs that accompany choices in EBSSO field work. Finally, the role technology may play in the future of EBSSOs is considered. We conclude with Chap. 6, outlining the future of SSO. Part of the uncertain future is how technology may shape the work and we offer some insights based on several projects. For those readers who consider one or more SSO technique to be feasible for addressing their research question, we offer opportunities for deeper dives into the literature. Consultation of prior users’ work is, in our view, a wise step in helping one navigate the field. Sharing instruments and experiences as a community of social scientists has been the norm of our experience. We have reached out to colleagues for help in developing this text numerous times and have been met uniformly with helpful assistance and insights. To the extent possible, we have developed archives of instruments and links to research which should aid those willing to engage in any of the SSO research methods outlined.

References Brunson, R.  K., & Miller, A. (2023). Police observational research in the twenty-first century. Annual Review of Criminology, 6(1), 205–218. https://doi.org/10.1146/ annurev-­criminol-­030421-­034101 Engel, R.  S., Corsaro, N., Isaza, G.  T., & McManus, H.  D. (2022). Assessing the impact of de-escalation training on police behavior: Reducing police use of force in the Louisville, KY Metro Police Department. Criminology & Public Policy, 21(2), 199–233. https://doi. org/10.1111/1745-­9133.12574 Mastrofski, S. D., Reisig, M. D., & McCluskey, J. D. (2002). Police disrespect toward the public: An encounter-based analysis. Criminology, 40(3), 519–551. https://doi.org/10.1111/j.1745­9125.2002.tb00965.x Mastrofski, S. D., Parks, R. B., Worden, R. E., & Reiss, A. J. J. (2007). Project on policing neighborhoods in Indianapolis, Indiana, and St. Petersburg, Florida, 1996–1997. ­Inter-­university

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Consortium for Political and Social Research [distributor]. https://doi.org/10.3886/ ICPSR03160.v2 McCluskey, J. D., Uchida, C. D., Solomon, S. E., Wooditch, A., Connor, C., & Revier, L. (2019). Assessing the effects of body-worn cameras on procedural justice in the Los Angeles Police Department. Criminology, 57(2), 208–236. https://doi.org/10.1111/1745-­9125.12201 Muir, W. K. (1977). Police: Streetcorner politicians. University of Chicago Press. Nassauer, A. (2018). How robberies succeed or fail: Analyzing crime caught on CCTV. Journal of Research in Crime and Delinquency, 55(1), 125–154. https://doi. org/10.1177/0022427817715754 Ostrom, E., Parks, R. B., & Whitaker, G. (2006). Police Services Study, Phase II, 1977: Rochester, St. Louis, and St. Petersburg. Inter-university Consortium for Political and Social Research [distributor]. https://doi.org/10.3886/ICPSR08605.v3 Raudenbush, S.  W., & Sampson, R.  J. (1997). Ecometrics: Toward a science of assessing ecological settings, with application to the systematic social observation of neighborhoods. Social Methodology, 29(1), 1–41. https://doi.org/10.1111/0081-­1750.00059 Reisig, M. D., & Parks, R. B. (2000). Experience, quality of life, and neighborhood context: A hierarchical analysis of satisfaction with police. Justice Quarterly, 17(3), 607–630. https://doi. org/10.1080/07418820000094681 Reiss, A.  J. (1971). Systematic observation of natural social phenomena. Sociological Methodology, 3, 3–33. https://doi.org/10.2307/270816 Skolnick, J. (1966). Justice without trial. Wiley. Smith, D. A. (1986). The neighborhood context of police behavior. Crime and Justice, 8, 313–341. Sytsma, V. A., & Piza, E. L. (2018). Script analysis of open-air drug selling: A systematic social observation of CCTV footage. Journal of Research in Crime and Delinquency, 55(1), 78–102. https://doi.org/10.1177/0022427817709502 Tapp, S. N., & Davis, E. J. (2022). Contacts between police and the public, 2020 (Special Report, Issue). https://bjs.ojp.gov/sites/g/files/xyckuh236/files/media/document/cbpp20.pdf Todak, N., & James, L. (2018). A systematic social observation study of police de-escalation tactics. Police Quarterly, 21(4), 509–543. https://doi.org/10.1177/1098611118784007 Uchida, C. D., & Anderson, K. (2021). Chapter 2. Managing digital evidence in a large agency: The LAPD experience. In C. D. Uchida et al. (Eds.), Managing digital evidence from body-­ worn cameras: Case studies in seven sites. Bureau of Justice Assistance. https://bwctta. com/sites/default/files/2022-­0 3/1%20DEM%20Final%20Report%2003%2001%2022_ CONTENT_0.pdf White, M. D., & Malm, A. (2020). Cops, cameras, and crisis: The potential and the perils of police body-worn cameras. NYU Press. Wilson, J. Q. (1968). Varieties of police behavior: The management of law and order in eight communities. Harvard University Press. Worden, R.  E., & McLean, S.  J. (2014). Systematic social observation of the police. In M.  D. Reisig & R.  J. Kane (Eds.), Oxford handbook of police and policing (pp.  471–496). Oxford University Press.

Chapter 2

The SSO Method in Police Research and Criminology

2.1  Introduction In the summer of 1966, 36 observers rode along with patrol officers in Boston, Chicago, and Washington, D.C. to watch, listen, and learn how police officers interacted with people and how citizens behaved toward the police. After weeks of training and preparation with Dr. Albert J. Reiss, Jr. at the Center of Research on Social Organization, these research assistants and law students rode with officers for seven days a week for seven weeks. During those 49 days, they recorded 3826 encounters in high-crime areas of the three cities. So began the first study of police that involved systematic social observations (SSO). In the years that followed, SSO has evolved to include multiple studies of police officers in numerous departments; branched out to include studies of hot spots, collective efficacy, and community violence initiatives; and embraced technology through the review of body-worn camera (BWC) footage. This chapter takes a sweeping view of SSO by placing the method into different contexts of police and criminological research. How did it originate? What new evidence was developed in policing that is unique to the method? By taking this approach, the chapter shows the importance of SSO, explains its advantages and disadvantages, and discusses the challenges faced by researchers under various circumstances.

2.2 Origins and Context for SSO Research on the police was in its infancy in the 1960s and 1970s. Many of the studies done during that period do not go into detail with their methodologies. As Manning and Van Maanen indicate in their review of published works, dissertations, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. McCluskey et al., Systematic Social Observation of the Police in the 21st Century, SpringerBriefs in Criminology, https://doi.org/10.1007/978-3-031-31482-7_2

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and works in progress, “Information on many of these studies is incomplete and sometimes quite imprecise. To wit, sites are often anonymous, the number of interviews conducted by the researcher is rarely available, and even the period of study is occasionally vague” (Manning & Van Maanen, 1978: 350, footnote 1). Three types of methods dominated police research – case studies, ethnographies, and systematic observations. The case study approach generally included interviews, surveys, and anecdotal observations. Ethnographies involved researchers who followed, talked with, and observed police officers over a specific time period. Among the case study approaches, Skolnick (1966), Chevigny (1969), and Wiley and Hudik (1974) are prominent. The classic case study, however, is that of James Q. Wilson in Varieties of Police Behavior. Like Skolnick, Wilson focused on “how the police patrolman behaves with respect to the more frequently applied laws,” that is, how does the patrolman enforce the law and maintain order? (Wilson, 1968: 4). Wilson’s methods to answer this question involved selecting eight cities,1 sending research teams of two people who “visited at least twice and usually three or four times for periods of no less than three weeks and in some cases for two months.” He makes no specific mention of what was done at each site, though he refers to interviews and quotes from officers, supervisors, and police administrators. Statistics were also gathered from the Uniform Crime Reports and on-site from the police agencies themselves. Importantly, Wilson’s work resulted in an explanation of police discretion, a description of three styles of policing (watchman, legalistic, and service), and a discussion of the interplay between policing and politics. While Wilson’s vision was to look closely at the police patrolman, his book lays out a typology for police organizations – one that serves as a basis for many future works (Maguire & Uchida, 2000). Ethnographic studies like those of Van Maanen (1978), Rubinstein (1973), and Muir (1977) examined officers working within the environments of specific police departments. Van Maanen focused on “Union City,” where he observed and wrote about officers and their knowledge of “persons, places, and settings within [their] assigned territory” (Manning & Van Maanen, 1978: 217). His article, “The Asshole,” speaks to how officers used a label to represent a “distinct but familiar type of person” that they encounter (Van Maanen, 1978). For Rubinstein, his year on the streets of Philadelphia gave him insight into the working officer and how his territory, encounters, knowledge of people, and his relationships with fellow officers and his supervisor shaped his beliefs and ways of handling situations (Rubinstein, 1973). Muir’s ethnography (1977) goes further than Van Maanen and Rubinstein in that he not only describes how 28 young police officers worked within the “Laconia” Police Department, but he explains how a “good” police officer is formed and developed. Over a 5-year research period, Muir developed a typology to determine the traits of a good officer. He found that the good cop developed two virtues: intellectually, he could grasp the nature of human suffering; and morally, he could resolve the

 Six of the eight cities were in New York State – Albany, Amsterdam, Brighton, Nassau, Newburgh, and Syracuse. The other two were Highland Park, IL and Oakland, CA. 1

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contradiction of achieving just ends with coercive means. When these virtues were applied to different situations and people, the good officer was born  – he could handle people without using physical force and get them to do things they would not ordinarily do. Importantly, Muir showed that officers were not alike, held different values, and behaved according to their individual ethics and beliefs (Snipes & Mastrofski, 1990). These case studies and ethnographies provided early explanations for policing and for the work of officers. But the methods themselves did not allow for replication of the studies or to generalize about police work and interactions with the public. Researchers did not include interview protocols or survey instruments, they did not discuss their note-taking during the ride-alongs, nor did they provide details about why departments and officers were selected.

2.3 Definition of SSO It is within this context that the work of Reiss is most appreciated. He saw things differently and defined systematic social observation in the following way: By systematic observation, I mean only that observation and recording are done according to explicit procedures which permit replication and that rules are followed which permit the use of the logic of scientific inference. The means of observation and recording, whether a person or some form of technology, must be independent of that which is observed and the effects of observing and measuring must be measurable. By natural social phenomena, I mean that events and their consequences, including properties of organization, can be observed more or less as they occur (Reiss, 1971).

As part of his extensive study in Boston, Detroit, and Washington, D.C., Reiss created predefined protocols for observation, trained observers extensively, sampled observable units (often in the form of police shifts), and coded characteristics of the police–citizen encounter. His method could be and was replicated by a number of scholars over the next 50 years.

2.4 Major Studies Using SSO Two major studies, the Police Services Study (PSS) and the Project on Policing Neighborhoods (POPN), followed the Reiss SSO method. PSS examined policing in three Standard Metropolitan Statistical Areas, Rochester, NY; St. Louis, MO; and Tampa-St. Petersburg, FL, in 1977 (Ostrom et al., 2006). Data collection involved 5688 encounters and was supplemented by 9021 interviews with random samples of residents in 59 neighborhoods (Smith & Uchida, 1988). POPN covered two cities, Indianapolis, IN and St. Petersburg, FL, involving 3125 encounters and 6125 surveys in 62 neighborhoods (Mastrofski et al., 1996; see also Reisig & Parks, 2003). As a result of these large SSO projects, a number of spin-off journal articles arose

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that looked at different ways in which the police behave. For example, POPN data were used to examine the relationship between police culture and coercion (Terrill, 2003) and to determine the situational predictors of police coercion or their decision to use force (Terrill & Mastrofski, 2002). Dozens of smaller-scale SSO have been conducted throughout the country covering important topics that are pertinent within the context of social justice. For example, Mastrofski et al. (1996) analyzed data from SSO in Richmond, VA to examine citizen compliance with police requests for them to exercise self-control, such as to “leave someone alone.” They measured predictors of citizen compliance, such as demonstrations of respectful police behavior, defined as fulfilling citizen requests, comforting or reassuring, and providing assistance, which were noted in 9% of these encounters. In contrast, disrespectful police behaviors, defined as derogatory remarks, ignoring citizens, or refusing citizen requests without explanation, were noted in 41% of the encounters analyzed. More recently, in Los Angeles, researchers examined procedural justice during police–citizen encounters before and after the implementation of body-worn cameras and found that procedural justice increased after the cameras were used for more than 1 year (McCluskey et al., 2019). Other studies used SSO to examine the exercise of police authority, police interactions with subsets of citizens (e.g., suspects), and police responses to particular kinds of incidents (e.g., disputes, domestic conflicts, and traffic violations) (See Worden & McLean, 2014). In-person SSO has limits, and the literature suggests that the method may not be suitable to study phenomena that rarely occur, including police use of deadly force, mass panic situations, and natural disasters (Mastrofski et  al., 2010; McCluskey et  al., 2014; Nassauer & Legewie, 2021; Worden & McLean, 2014).

2.5 Trends in Police-Based SSO Research: Using Technology Recently, technology in policing has made it possible to use SSO in reviewing videos from in-car, dash-mounted cameras and body-worn cameras (BWCs). In-car dash cameras have been used by police agencies since the mid-2000s but very few researchers have employed them for SSOs (Brunson & Miller, 2023). Two studies by Dixon et al. (2008) and Worden and McLean (2014) reviewed video from the Cincinnati and Schenectady, NY police departments, respectively. Dixon et al. randomly selected 313 videos for their examination of traffic stops. They found that Black drivers were more likely to experience extensive policing during the stop; that police communication with White drivers was, on average, more positive than that of the Black drivers; and that officers’ communication behavior was more positive when the officer and driver were of the same race (Dixon et al., 2008). Since the adoption of body-worn cameras (BWCs) by policing agencies in 2014, researchers have included SSO in their assessments of the technology. McCluskey et al. (2019) were among the early researchers to use SSO for their evaluation of the Los Angeles Police Department’s implementation of BWCs.

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Further, at least a dozen studies have employed video-based systematic social observations (VBSSO) to answer a variety of research questions about police behavior (McCluskey & Uchida, 2023). Procedural justice (Mell, 2016; Nawaz & Tankebe, 2018; and Dai, 2021), use of force (Willits & Makin, 2018; Sytsma et al., 2021; Terrill & Zimmerman, 2021; Schafer et al., 2022), discourtesy (Holladay & Makin, 2021) and communication patterns (Voigt et al., 2017; Makin et al., 2019) are among the research topics that have been covered to date. Research using VBSSO holds much promise as it is less expensive than in-­person SSO. However, as discussed more fully in Chap. 4, it is not without its drawbacks. Consideration must be given to issues of sampling, access to video footage, human subject concerns, and assessments of reliability among coders.

2.6 SSO of Neighborhoods and Places In this section, we introduce Environmental-Based Systematic Social Observation (EBSSO) to describe the method used to measure physical conditions and social disorder that exist within places. This concept is based, in part, on how police, communities, and researchers conceive of neighborhood crime patterns, engage in hotspot policing, and explain theories of social disorganization and collective efficacy. The early police researchers of the 1960s and 1970s saw that police officers were influenced in part by the environment and the specific areas that they worked. Skolnick (1966), Rubinstein (1973), and Muir (1977) emphasized that officer knowledge of their territory was important to how they interacted with citizens. The subtleties of what constitutes a neighborhood (e.g., apartments, single-family homes, types of businesses, and wide or narrow streets) shaped the way in which police treat people and view crime. In the 1980s, SSO research began to branch out into neighborhoods and communities to assist in understanding why crime patterns were high in some neighborhoods and low in others. In particular, SSO instruments were used by Ralph Taylor and his colleagues to test the theory of social disorganization and to explain differences in neighborhoods and people’s perceptions of fear, trust, and cohesion. Knowing about traffic volume (high or low), nonresidential properties (businesses), the presence or absence of a park, or the rates of physical incivilities (graffiti, trash, or abandoned housing) had effects on whether and how people interacted (Taylor et  al., 1985). By understanding citizen interactions with each other or the lack thereof, researchers could now understand the depth of social disorganization. The traditional measures of social disorganization (surveys, census data, and demographics of a neighborhood) were now supported by the physical attributes and social activities of places. The Project on Human Development in Chicago Neighborhoods (PHDCN) followed Reiss’s notion that assessing the physical conditions and social interactions within neighborhood settings would give a deeper understanding of place. In

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addition to obtaining perceptions of community residents through surveys, researchers with PHDCN decided to “observe” neighborhood clusters throughout the city. Their approach was clearly different from observing police officers in patrol cars. Over a five-month period (June-October) in 1995, trained observers drove a sport utility vehicle (SUV) at a rate of 3–5 miles per hour down every street within the sample of 80 neighborhood clusters. The team consisted of a driver, two observers, and a videographer. Two video cameras were located on each site of the SUV and captured physical features and social activities. The observers recorded their observations in a written log and spoke into an audio recorder. Data collection took place between the hours of 7 a.m. and 7 p.m. and resulted in the observation and recording of 23,816  face-blocks.2 Machine-readable data were then coded from trained observer logs and an intensive EBSSO review of the videotapes. The logs were used to capture land use, traffic, and the physical conditions of buildings, and videos captured indicators of physical conditions and social interactions on each face block (Sampson, 2012: 90). Ultimately, Sampson’s work in Chicago led to the development of the theory of collective efficacy and the science of ecological assessment called “ecometrics” (see Sampson, 2012; Sampson et al., 1997; and Sampson & Raudenbush, 1999). Collective efficacy went beyond social disorganization theory because it demonstrated that neighborhoods varied in social cohesion and trust and their rates of violent crime. Sampson and his colleagues showed that where collective efficacy was high, violent crime was low, while controlling for concentrated disadvantage, immigration status, residential stability, and individual characteristics (age, race, and gender). It is through Sampson’s work on ecometrics and collective efficacy that we emphasize the use of Environment-Based Systematic Social Observation (EBSSO). A smaller-scale study of collective efficacy in Miami-Dade County followed Sampson’s footsteps by using EBSSO to measure the physical environment and social disorder in eight neighborhoods (Uchida et al., 2015). A three-page EBSSO instrument to measure the physical environment and a one-page instrument to measure social indicators were used by trained observers at different times of the day and night within the eight neighborhoods. Face-blocks or street segments were selected within the neighborhoods, and the physical conditions and social disorder were measured through EBSSO instruments. Combined with community surveys and crime data, the researchers were able to replicate Sampson’s finding that areas of high collective efficacy enjoyed lower crime rates. (These instruments are available online at https://doi.org/10.6084/m9.figshare.22266217) Solomon (2019) extended the analyses of Miami-Dade County to determine whether housing foreclosures had effects on collective efficacy and crime. In the United States, during the period 2005–2010, residents were unable to pay their home mortgages and defaulted on their loans and the houses foreclosed, with

 The ‘face-block’ is the block segment on one side of a street. One regular street block would have two face-blocks and were counted as two separate units of observation (Sampson, 2012). 2

2.7  Linking EBSSO to Theories of Crime and Police Behavior

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ownership reverting to the banks that made the initial loans. This led to the abandonment of thousands of homes in Florida, Arizona, California, and other states. The housing crisis in the United States led to economic woes as well as a belief that crime was increasing because residents were not around to both take care of their homes and to serve as guardians of neighborhoods (routine activity theory). Because vacant lots, foreclosed homes, and bordered-up houses were a part of the EBSSO in Miami-­Dade County, Solomon was able to show a link between high crime, low collective efficacy, and high foreclosures. Chapter 5 provides more details on how this was accomplished using EBSSO.

2.7 Linking EBSSO to Theories of Crime and Police Behavior “Problem neighborhoods” are identified and studied in several ways. In policing, “hot spots” of crime are based in part on officer knowledge and on crime data (incidents and calls for service). The information gleaned from these sources are analyzed using mapping software, and police can conduct various enforcement activities and/or engage the community within these targeted locations. The use of EBSSO assists in validating data and preconceived ideas of an area. It confirms where the police should be doing something. In addition, EBSSO is a measure of what the police do in these places. Trained observers can walk and drive through these hot spot areas at different times of the day and night. Using the EBSSO instruments, they can obtain accurate accounts of the physical conditions and social activity that takes place. Studies by researchers at Justice & Security Strategies, Inc. using EBSSO instruments have aided police and community organizations in understanding that places with indicators of physical disrepair (e.g., graffiti, trash, and abandoned vehicles) and signs of social disorder (e.g., visible drug dealing, illegal vendors, and gamblers “shooting craps”) are correlates of criminal activity and low collective efficacy (Solomon & Uchida, 2018). For example, in Los Angeles, MacArthur Park and its immediate surroundings were identified by researchers and community organizations as a major hot spot for several years. Violent crime, thefts from motor vehicles, and burglaries were occurring routinely. Trained observers measured the problems in and around the park over a two-month period using EBSSO. They cited trash, graffiti, and broken fencing and saw drug dealing, gambling, and homeless tents throughout the area. The layers of information from multiple data sources showed the police the magnitude of the problem so that the captain responsible for the area would act to enforce vice offenses. In addition, community groups recognized that “taking back the park” was important, and they cleaned up trash, painted over graffiti, and began to hold community events to displace the drug traffickers and gamblers. EBSSOs combined with community surveys and crime data assisted in measuring collective efficacy. The physical attributes and social disorder within places help

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to explain why people living in these areas may not talk or interact with their neighbors. It literally shows the barriers to social cohesion and trust among neighbors that are necessary for collective efficacy to take effect. Similarly, it demonstrates that police, policymakers, and community organizations have a role in building trust and social cohesion by working with residents to improve the environment (Youth Policy Institute, 2016).

2.8 Conclusion The method of SSO, whether with the police or in neighborhoods, is a useful way to understand police behavior and community (dis)order. Based on Reiss’s groundbreaking work in the 1960s, numerous studies in policing have led to a better understanding of how the police interact with people and how people relate to the police. Procedural justice, police and citizen demeanor, and citizen compliance with police requests are among the many types of behavior that are better understood. With the availability of body-worn camera footage, VBSSO is now possible, and it remains to be seen how much can be done by researchers to test that method. Lastly, the use of and results from EBSSO in neighborhoods have important policy implications for police, community organizations, and residents and policymakers affected by negative physical attributes and social disorder.

References Brunson, R.  K., & Miller, A. (2023). Police observational research in the twenty-first century. Annual Review of Criminology, 6(1), 205–218. https://doi.org/10.1146/ annurev-­criminol-­030421-­034101 Chevigny, P. (1969). Police power: Police abuses in New York City. Pantheon books. Dai, M. (2021). Training police for procedural justice: An evaluation of officer attitudes, citizen attitudes, and police-citizen interactions. The Police Journal, 94(4), 0032258X20960791. https://doi.org/10.1177/0032258x20960791 Dixon, T.  L., Schell, T.  L., Giles, H., & Drogos, K.  L. (2008). The influence of race in police-civilian interactions: A content analysis of videotaped interactions taken during cincinnati police traffic stops. Journal of Communication, 58(3), 530–549. https://doi. org/10.1111/j.1460-­2466.2008.00398.x Holladay, B.  P., & Makin, D.  A. (2021). Baselining incivility in one-on-one police encounters from BWC archival footage: Exploratory study of race, gender and contact type effects. Police Practice and Research, 22(6), 1618–1636. https://doi.org/10.1080/15614263.2021.1914040 Maguire, E. R., & Uchida, C. D. (2000). Measurement and explanation in the comparative study of American police organizations. Criminal Justice, 4, 491–557. Makin, D.  A., Willits, D.  W., Koslicki, W., Brooks, R., Dietrich, B.  J., & Bailey, R.  L. (2019). Contextual determinants of observed negative emotional states in police–community interactions. Criminal Justice and Behavior, 46(2), 301–318. https://doi.org/10.1177/ 0093854818796059 Manning, P. K., & Van Maanen, J. (1978). Policing: A view from the street. Goodyear Publishing Company.

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Mastrofski, S. D., Snipes, J. B., & Supina, A. E. (1996). Compliance on demand: The public’s response to specific police requests. Journal of Research in Crime and Delinquency, 33(3), 269–305. https://doi.org/10.1177/0022427896033003001 Mastrofski, S.  D., Parks, R.  B., & McCluskey, J.  D. (2010). Systematic social observation in criminology. In A. R. Piquero & D. Weisburd (Eds.), Handbook of quantitative criminology (pp. 225–247). Springer. McCluskey, J., & Uchida, C. D. (2023). Video data analysis and police body-worn camera footage. Sociological Methods and Research. https://doi.org/10.1177/00491241231156968 McCluskey, J.  D., Parks, R.  B., & Mastrofski, S.  D. (2014). Systematic social observation. In G.  Bruinsma & D.  Weisburd (Eds.), Encyclopedia of criminology and criminal justice. Springer. https://doi.org/10.1007/978-­1-­4614-­5690-­2_677 McCluskey, J. D., Uchida, C. D., Solomon, S. E., Wooditch, A., Connor, C., & Revier, L. (2019). Assessing the effects of body-worn cameras on procedural justice in the Los Angeles Police Department. Criminology, 57(2), 208–236. https://doi.org/10.1111/1745-­9125.12201 Mell, S.  M. (2016). The role of procedural justice within police-citizen contacts in explaining citizen behaviors and other outcomes. Virginia Commonwealth University. Muir, W. K. (1977). Police: Streetcorner politicians. University of Chicago Press. Nassauer, A., & Legewie, N.  M. (2021). Video data analysis: A methodological frame for a novel research trend. Sociological Methods & Research, 0049124118769093. https://doi. org/10.1177/0049124118769093 Nawaz, A., & Tankebe, J. (2018). Tracking procedural justice in stop and search encounters: Coding evidence from body-worn video cameras. Cambridge Journal of Evidence-Based Policing, 2(3), 139–163. https://doi.org/10.1007/s41887-­018-­0029-­z Ostrom, E., Parks, R. B., & Whitaker, G. (2006). Police services study, phase II, 1977: Rochester, St. Louis, and St. Petersburg. Inter-university Consortium for Political and Social Research [distributor], 2006-03-30. https://doi.org/10.3886/ICPSR08605.v3 Reisig, M. D., & Parks, R. B. (2003). Neighborhood context, police behavior and satisfaction with police. Justice Research and Policy, 5(1), 37–65. Reiss, A. J., Jr. (1971). The police and the public. Yale University Press. Rubenstein, J. (1973). City police. Farrer, Straus and Giroux. Sampson, R.  J. (2012). Great American city: Chicago and the enduring neighborhood effect. University of Chicago Press. Sampson, R. J., & Raudenbush, S. W. (1999). Systematic social observation of public spaces: A new look at disorder in urban neighborhoods. American Journal of Sociology, 105, 603–651. Sampson, R. J., Raudenbush, S. W., & Earls, F. (1997). Neighborhoods and violent crime: A multilevel study of collective efficacy. Science, 277, 918–924. Schafer, J., Hibdon, J., & Kyle, M. (2022). Studying rare events in policing: The allure and limitations of using body-worn camera video. Journal of Crime and Justice. https://doi.org/10.108 0/0735648X.2022.2062036 Skolnick, J. (1966). Justice without trial. Wiley. Smith, D. A., & Uchida, C. D. (1988). The social organization of self-help: A study of defensive weapon ownership. American Sociological Review, 94–102. Snipes, J. B., & Mastrofski, S. D. (1990). An empirical test of Muir’s typology of police officers. American Journal of Criminal Justice, 14, 268–296. Solomon, S.  E. (2019). Neighborhoods matter: Crime collective efficacy and foreclosures in Miami. Dissertation. Manuscript, Maastricht University. Solomon, S. E., & Uchida, C. D. (2018). Miami-Dade community-based crime reduction program: Final report, building collective efficacy: One block at a time. Justice & Security Strategies, Inc. Sytsma, V. A., Chillar, V. F., & Piza, E. L. (2021). Scripting police escalation of use of force through conjunctive analysis of body-worn camera footage: A systematic social observational pilot study. Journal of Criminal Justice, 74, 101776. https://doi.org/10.1016/j.jcrimjus.2020.101776 Taylor, R. B., Shumaker, S. A., & Gottfredson, S. D. (1985). Neighborhood-level links between physical features and local sentiments: Deterioration, fear of crime, and confidence. Journal of Architectural and Planning Research, 2(4), 261–275.

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Terrill, W. (2003). Police use of force and suspect resistance: The micro process of the police-­ suspect encounter. Police Quarterly, 6(1), 51–83. https://doi.org/10.1177/1098611102250584 Terrill, W., & Mastrofski, S. D. (2002). Situational and officer-based determinants of police coercion. Justice Quarterly, 19(2), 215. https://doi.org/10.1080/07418820200095221 Terrill, W., & Zimmerman, L. (2021). Police use of force escalation and de-escalation: The use of systematic social observation with video footage. Police Quarterly, 25(2), 155–177. https://doi. org/10.1177/10986111211049145 Uchida, C. D., Swatt, M. L., Solomon, S. E., & Varano, S. P. (2015). Community, crime control, and collective efficacy: Neighborhoods and crime in Miami. Lexington Books. Van Maanen, J. (1978). The asshole. In Policing: A view from the street (pp. 221–238). Goodyear. Voigt, R., Camp, N.  P., Prabhakaran, V., Hamilton, W.  L., Hetey, R.  C., Griffiths, C.  M., et  al. (2017). Language from police body camera footage shows racial disparities in officer respect. Proceedings of the National Academy of Sciences, 114(25), 6521–6526. https://doi. org/10.1073/pnas.1702413114 Wiley, M. G., & Hudik, T. L. (1974). Police-citizen encounters: A field test of exchange theory. Social Problems, 22(1), 119–127. https://doi.org/10.2307/799571 Willits, D. W., & Makin, D. A. (2018). Show me what happened: analyzing use of force through analysis of body-worn camera footage. Journal of Research in Crime and Delinquency, 55(1), 51–77. https://doi.org/10.1177/0022427817701257 Wilson, J. Q. (1968). Varieties of Police Behavior: The Management of Law and Order in Eight Communities. Harvard University Press. Worden, R. E., & McLean, S. J. (2014). Systematic social observation of the police. In M. D. Reisig & R.  J. Kane (Eds.), The Oxford handbook of police and policing (pp.  471–496). Oxford University Press. Youth Policy Institute. (2016). Collaboration for efficacy and cohesion: Youth Policy Institute’s Los Angeles Byrne Criminal Justice Innovation Program. Unpublished report. Youth Policy Institute.

Chapter 3

Developing and Conducting an SSO Study: A How-to-Guide for Social Science Research

In the 1960s, Albert J. Reiss’ study established systematic social observation (SSO) as an essential method to study police behavior (Worden & McLean, 2014). Since its introduction, however, the method has been used rather infrequently (Brunson & Miller, 2023). Although SSO is a very intensive research method, which may partly explain its infrequent use, this can also be the result of a lack of clear guidelines on how to perform SSO. Although Reiss and Mastrofski et al. (1998) outline this procedure, this guideline requires an update, combining the tips and tricks of different SSO studies. This chapter fills a gap by updating the aforementioned guidelines and clearly defining how to set up an in-person SSO (IPSSO) project. We aim to make researchers aware of what SSO entails and how they can prepare for, conduct, and report about this data collection method. To explain these different steps, we provide examples based on the research of the authors, who studied Belgian police officers’ decision-making processes, partly based on IPSSO (see, e.g., Feys, 2022a, b) and examined police behavior in the Los Angeles Police Department (LAPD). The sections that follow suggest a sequential approach when conducting SSO, with a particular focus on in-person SSOs.

3.1 Determining the Research Frame 3.1.1 Research Topic and Context Researchers wishing to conduct an SSO study should first determine their research topic, research question(s) and aim(s), and the context of their research (e.g., specific population, specific geographical areas). Only after clearly establishing the research frame can researchers consider whether their topic can be studied by means of SSO.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. McCluskey et al., Systematic Social Observation of the Police in the 21st Century, SpringerBriefs in Criminology, https://doi.org/10.1007/978-3-031-31482-7_3

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Worden and McLean (2014) found that studies using SSO regularly focus on police patrols, but they argue that SSO can also be used to study other police functions. Studies have examined the exercise of police authority, police interactions with subsets of citizens (e.g., suspects), and police responses to incidents (e.g., disputes, domestic conflicts, traffic violations). Worden and McLean (2014) gave an overview of some large-scale SSO studies that can be used as input for the development of new projects. For example, the relationship between police culture and coercion (Terrill et  al., 2003) and situational determinants of police coercion or police officers’ decision to use force (Terrill & Mastrofski, 2002), derived from the Project on Policing Neighborhoods, built on the preceding work of Reiss and Ostrom. When IPSSO seems suitable for one’s research project, researchers should consider who, where, when, and what they would like to observe (Mastrofski et  al., 1998; Van Damme, 2017). Particularly the latter question will be answered through the research design and is related to determining the unit of analysis (e.g., disputes, see Bayley, 1986). This can be an individual, neighborhood, police–citizen interaction, specific behavior, etc. (Mastrofski et al., 2010; Sampson & Raudenbush, 1999; Sytsma & Piza, 2018; Todak & James, 2018). Schulenberg (2014) argues that she chose police–citizen encounters as the unit of analysis as she does not want to know, for instance, how an officer uses every minute of their time. This means that she completes an observation form every time an officer interacts with a citizen. Observers should clearly define when the observation unit starts and ends, and as such what should (not) be included.1 The unit of analysis can also be a time period (observing what happens in a specified time), a behavior or act, or an event (e.g., encounter between police officer and citizen). Most typically in police research, police–citizen encounters are the unit of analysis (Reiss, 1971; Mastrofski et  al., 2002). Mastrofski et  al. (2010) suggest careful consideration of what the event under study is and to define (prior to data collection) what should be done if the original interaction is broken up for another one. Research Frames in Action In the most recent projects conducted by the authors, several important questions had to be answered. What Was to Be Studied? The Belgian Observation and Systematic Study of Decisions (BOSS-D) was a project focused on police officers’ decision-making and aimed to map and understand the factors that affect police decisions. The project also specifically focused on a comparison between  perceived decision-making processes (how they believe they make decisions) and actual decision-making processes (how they make decisions in practice) – the former was studied by means of a survey and semi-structured interviews; the latter was studied by means of IPSSO.

 For instance, Todak and James (2018) defined that only encounters between police officers and citizens that last longer than 2 min should be included. 1

3.1  Determining the Research Frame

In the case of the Los Angeles Police Department (LAPD), the research team was interested in whether body-worn cameras (BWC) influenced the level of procedural justice that officers displayed in their encounters with citizens. Hereafter, we refer to this study as the LAPD-PJ study. Where Should the Study Be Done? Five Belgian police forces were randomly selected to participate in the BOSS-D project. For the LAPD-PJ study, two Divisions of the LAPD, Mission and Newton, were chosen since they were the first places where BWCs were deployed, and a pre-­post design of observation was most feasible in the project timeline. Who Was to Be Studied? The BOSS-D study involved police officers working in intervention (i.e., responding to citizen calls, proactively patrolling) and criminal investigators. In the LAPD-PJ study, officers were randomly selected from the patrol divisions; however, this was complicated by the fact that almost all patrol units are comprised of two officers. When Did Observation Take Place? Observations were conducted during a pre-defined time period for BOSS-D – however, the COVID-19-period challenged the original planning, extending it to over a year. In LAPD-PJ, observation waves were fielded prior to and subsequent to the BWC deployment in different years. In terms of sampling, shifts were stratified with respect to call loads. Because the LAPD works a 12-h shift, it was determined that half-shift observation was most feasible for a passenger riding in a cramped backseat of a patrol car during a hot LA summer. What Was the Unit of Analysis? In the BOSS-D study, the units of analysis were focused on decisions, either in police interventions (intervention) – defined as an encounter of police officers based on an urgent call or proactive activity – or regarding criminal investigative acts (criminal investigation). In LAPD-PJ, the primary unit of analysis was citizens encountering the police, and a single encounter could contain multiple citizens (a complainant and a suspect for example) in different roles. How Are Key Units of Observation Defined? For the start of an observation, the BOSS-D project defined an encounter beginning when the police received a citizen call, the police officer proactively started an intervention or an investigative act (e.g., interrogation). The LAPD-PJ study defined an encounter beginning when the police spent 1 min or had three exchanges with a citizen. Any physical contact, such as grabbing or handcuffing, also constituted an encounter.

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The end of an observational unit for BOSS-D was defined as when the call was resolved, the proactive intervention ended or the investigative act completed. The LAPD-PJ project defined the end of an encounter when the police were no longer in contact with the citizen for a period of time. This required judgment, for example, when police might go back and forth between neighbors having a dispute. If tied with a unifying event and little time passed between contact, the observer would code this as a single encounter with two citizens. However, if time was spent searching for the second party then a second encounter commenced, but it was linked to the first via a common event identifier in coded data.

3.1.2 Methodology Researchers that select SSO for their method should consider several aspects that are necessary for setting up the project. First, they should decide whether to set up a solo observer-project or one with multiple observers. A solo observer typically designs the study and collects and analyzes the data alone. This has advantages of consistency and uniformity, but also disadvantages (e.g., no analyses possible on variation across observer data) (Reiss, 1971). Nawaz and Tankebe (2018) argue that the use of only one consistent observer throughout the study strengthens reliability, whereas Hoeben et al. (2018) imply that more observers strongly improve the reliability of the data. The decision to work with one or more observers depends on the available resources and potential observers. In either case, thorough protocols should be developed to ensure that replication is possible. An SSO project included in a policing or methodological course at the university is a cost-effective approach to multiple-observer IPSSO, provided that these students have the necessary abilities to conduct SSO. Furthermore, as detailed below, these students need to be trained, supervised and monitored, which is an intensive task as well (for more details, see Mastrofski et al., 1998, 2010; Schulenberg, 2014; Terrill & Zimmerman, 2022). There is also a less intrusive alternative, for example, by inviting an external observer to test the codebook in the beginning of the observation phase in a small number of observations (see, for instance, Van Damme, 2017). As such, interpretations of the codebook can be discussed after the observations and can be made consistent. Another methodology described in Chap. 5 involves the use of body-worn camera (BWC) footage and video-based SSO (VBSSO). Researchers should consider the relative advantage of IPSSO weighed against the use of existing video footage. VBSSO could be useful when rare events are recorded by bystanders and hosted on YouTube (Nassauer & Legewie, 2018) or when video accounts of incidents are released to the public (Uchida et al., 2022). Researchers should consider the advantages and disadvantages of each mode of observation and choose accordingly. The processes described in this how-to-guide focus on important choices researchers must make in SSO designs, regardless of mode of observation.

3.2 Practical Preparation

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Variation in Application of Methodology Sole observer in the BOSS-D project as compared to a field research team in the LAPD-PJ study. In the BOSS-D study, a sole observer performed IPSSOs. This improved the consistency of data registration and processing, but was also based on practical considerations. That is, Belgium has a rather extensive procedure to get permission for police observations, which involves the police force and the attorney-general. In some provinces, a form has to be filled out explaining what specifically will be observed and which parts of police work cannot be observed directly. Furthermore, a morality research, or background check, was conducted on the observer to make sure that she had no criminal background and there were no counterindications for observation allowance. This procedure is usually feasible for a PhD researcher, but clearance is harder to obtain for different undergraduate or graduate students. Therefore, including students was infeasible and with limited resources, other researchers could not be included. In the LAPD-PJ study, security clearance for each observer was required. This was a slow process and any research team operating in the field must plan, either IPSSO or VBSSO, to commit substantial time to securing clearance for ride-alongs or the review of footage. With regard to this study, IPSSO was necessary as the rollout of BWC was the intervention that was a variable of interest. Thus, the same pre- and post-methodology of IPSSO was used to measure police behavior.

3.2 Practical Preparation 3.2.1 Cooperation and Agreements Obtaining cooperation from the target organization is essential (Brunson & Miller, 2023; Schulenberg, 2014). Cooperation can entail gaining access to certain footage (e.g., body-worn camera videos) or access to a police department or force itself in case of IPSSO. Gaining cooperation entails drawing up agreements in writing between the observer and a representative of the target group. There are no standard guidelines on how to draw up such agreements, as this depends on the country in which the observations are conducted. We suggest that the agreement includes: safety precautions; privacy and confidentiality agreements; whether or not the participants can see the field notes related to their activities (if asked); how the results will be disseminated to the participants or larger police organization; and if and how researchers can publish on the findings (Mastrofski et al., 1998; Reiss, 1971; Schulenberg, 2014; Todak & James, 2018; Van Damme, 2017).

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Access to Organizations and Police Officers In the BOSS-D project, SPSS was used to draw a random sample of police agencies for selection. These police forces were then asked to participate in the project by email. This was followed by a face-to-face meeting in which the project was explained and agreement was obtained verbally. Afterwards, the procedure to get formal agreement was started. To formalize this cooperation, research agreements were drawn, detailing the expectations of both parties. The written agreement among others included safety precautions (e.g., the need to wear a bulletproof vest, what to do in aggressive or otherwise dangerous situations) and agreements on anonymity of the police forces and the respondents themselves. The LAPD-PJ project was fielded as part of the department’s adoption of BWC and funded through a federal grant. The LAPD asked Justice & Security Strategies (JSS) to evaluate the adoption of BWCs and was identified as the research partner within the grant proposal. The evaluation included the SSO design for data collection. Prior to commencing the project, JSS obtained permission from the chief of police to conduct ride-alongs with randomly chosen officers. LAPD policy dictates that no civilians could ride in two-officer vehicles, but the chief agreed to waive this policy and wrote a memo to captains of the divisions where the evaluation would occur. It should also be noted that the project director (Dr. Uchida) had established a working relationship within the LAPD for 5 years when this project began. He was familiar with the policies and procedures of the department and also knew the captains within the patrol divisions.

3.2.2 Ethical Clearance Ethical considerations, including privacy and confidentiality, are vital to receive full cooperation and gain trust from police officers participating in the project. Furthermore, and especially in SSO projects focusing on police officers, citizens who have not actively consented to being observed are usually included in the project. As such, we recommend obtaining ethical clearance from an institutional review board (IRB) for each project that involves SSO. Doing so demonstrates the transparency of the research team, assists in obtaining voluntary cooperation2 and provides a means to obtain informed consent.

 In the study of Lum et al. (2020), calltakers and dispatchers were explicitly told that they were not obliged to participate. Although this can result in bias, as it may be that people who do not want to cooperate exhibit other behaviors than those that do cooperate (Mastrofski et al., 2010; Schulenberg, 2014), it is ethically incorrect to enforce (involuntary) cooperation. 2

3.2 Practical Preparation

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One of the ethical concerns regarding SSO projects is to obtain informed consent from research participants. This can be verbal at the beginning of a ride-along (Todak & James, 2018), but it is preferred to be in writing. Schulenberg (2014) secured consent as soon as logistically possible. In the consent form, participants were informed that they could review notes recorded during the ride-along and that modifications were possible. This approach is believed to reduce negative reactions, increase trust and rapport, while also ensuring accuracy. The difficulty of obtaining consent in VBSSO, and how to balance access and respect for human subject in that mode, is discussed in Chap. 4. As briefly implied above, researchers should also consider the role of civilians. As in most SSO projects, civilians will not be fully aware of the research project, whom and what is observed and what the researcher’s role is. This should be laid out for the IRB in advance, and agreements should be made on how to proceed should a civilian have questions. Providing an information letter to civilians who experience doubts concerning the observer’s role or wish to receive more information, might be a partial solution for this issue – at least after the police have completed their job to avoid too big of an influence on the interaction. Another component of ethical research involves data management procedures. Data should be processed and stored securely, and researchers should consider how they will pseudonymize the data they are inputting (e.g., by using codes instead of names). This should also be taken into account when reporting about the findings as police officers might be able to identify their own colleagues based on specific descriptions, characteristics or quotes – researchers should thus carefully consider how they distribute their findings. Data management, however, not only relates to communicating about the results but also to sharing (pseudonymized) data and observation instruments. Here, national laws and regulations might apply (e.g., concerning the sharing of personal, sensitive, or confidential information).3 The limits and boundaries for collecting and sharing data and materials should be explored in advance of any SSO project. If data can be shared, this can be done by means of a repository or by simply making the data available upon request. An example of an SSO dataset that has been made available to other researchers and has been used in different research projects so far, is the Project on Policing Neighborhoods (POPN). POPN includes approximately 3500 police-suspect encounters in Indianapolis and St Petersburg, collected during 1996–1997 (Paoline & Terrill, 2005; Spano & Reisig, 2006; Terrill & Paoline, 2007). With regards to data management, national and local or institutional guidelines should be identified  – for example, Ghent University requires researchers to store their (raw) data for at least 5  years after completion of a research project  – and followed consistent with the respect for human subjects.

 Belgium, for instance, has a registration obligation when personal data (e.g., names, identifiable information) are being processed, which is frequently the case when SSOs are conducted. 3

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Conducting Ethical Research For the BOSS-D project, an ethical clearance was requested at the ethical committee of the Faculty of Law and Criminology of Ghent University, which evaluated the entire project. The observer was fully transparent about the aims of the project, how the observations would take place, and what would happen with the field notes. Justice & Security Strategies, which ran the LAPD-PJ project, convened an IRB, which reviewed and approved the data collection protocols and reviewed the processes for obtaining informed officer consent and data management. Both of the projects were based on completely voluntary participation, meaning that police officers unwilling to participate would not have a ride-along and the observer would be moved to a different unit. Informed consent was usually provided in writing at the beginning of the shift (or on a later moment if that were impossible). For the BOSS-D project this form assured that: (a) the participants received information before participating in the project; (b) the participants voluntarily participated in the project; (c) the participants were aware that they could look into the field notes that related to them; (d) the researcher had the participants’ consent to ask questions and use this information for the project; (e) the researcher had consent to store, process, and report on the results in an anonymous manner; (f) the participants could stop their participation at any time and choose not to answer certain questions; (g) the participants could receive a summary of the main findings; and (h) the participants were aware that criminal offenses committed by police officers during the observations would be reported to the chief of police (i.e., head of the police force). The latter was important to avoid moral dilemmas on whether or not the observer should report criminal offenses – this, however, never happened. Researchers should also be aware of potential harm to participants and be sensitive to their concerns. On a few occasions during the IPSSO, the observer seemed to negatively affect a citizen’s state of mind. One such occasion in the BOSS-D project related to a young woman who had a firm belief that the observer was part of the social services and was taking notes because she wanted to take away her child. In this situation, the observer stopped taking notes, explained her role as an observer, and then kept her distance to avoid further discomforting the woman. Concerning research data management regarding BOSS-D, a data management plan (DMP) was provided, detailing how the data would be stored and processed. It was agreed upon that the data should always be stored at the institutional network capacity of Ghent University, which is not only secured but also provides regular back-ups and thus prevents loss of data. Furthermore, these data will be kept for at least 5 years after termination of the project, in line with institutional guidelines. In both projects, the findings can be published, but in a pseudonymized manner. This means that only the researcher is able to link certain data to

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specific persons, but they remain anonymous to other people. Every police officer is given a unique code, which makes them unidentifiable to others. Police officers’ names are not used in any form of communication, and data and results and matching lists are sufficiently encoded to preclude the ability to match individuals to the SSO data.

3.3 Preparing Fieldwork: Instruments and Training Preparing for fieldwork involves knowing what to do on site, creating research instruments, and training. This entails gaining insights into the method of IPSSO by reading the literature to increase one’s awareness of procedures and potential obstacles (Schulenberg, 2014; Van Damme, 2017), getting fully acquainted with the concepts under study, and how to operationalize the method. Second, researchers should get acquainted with the organization they will be studying. Although researchers will learn (informal) procedures and rules when inside the organization, a basic knowledge about it is desirable (e.g., organizational structure, division of tasks) (Mastrofski et al., 2010). As a means for preparing the SSO project, Reiss (1971) conducted exploratory research prior to SSO, which gave insights into the organization of the observation process and how to train observers – two essential steps in the SSO procedure. In this section, we will therefore primarily focus on the development of research instruments and training. General Notes on the Preparation of Fieldwork As preparation for the BOSS-D project, the study by Van Damme (2017), which was also conducted in Belgium, proved extremely useful for preparing the fieldwork. Furthermore, the police forces provided documentation to get acquainted with their organizations. The observations usually started with a tour within the police force. The observer obtained a sense of the department’s organizational structure and was able to introduce herself to officers who were not part of the project (e.g., those working on traffic regulations or neighborhood policing). Introducing herself to the entire police force proved to be helpful in gaining confidence and trust. The LAPD-PJ study included familiarization with the important patterns of communication that would help observers make sense of police work. For example, LAPD’s code system for call types dictates routine vs. priority calls (lights and sirens allowed) and the number of key codes that might be heard in radio traffic. Additionally, some familiarity with the layout of the mobile digital terminals mounted in cars helped observers keep track of time, dispatch conditions, and the like.

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3.3.1 Codebook and Procedures Codebook A well-prepared data collection instrument is one of the advantages of SSO. Referred to as a codebook, it may include a sheet to count and document activities (e.g., police presence, forms of disorder) or a questionnaire to be filled in by an observer. The instruments provide focus for the observer (i.e., what should and should not be observed) as the observer cannot observe and record every aspect of a situation, and it structures the data collection process (Brunton-Smith, 2018; Mastrofski et  al., 2010; McCall, 1984; Reiss, 1971; Schulenberg, 2014). A codebook should include all elements or variables an observer wants to observe. This can include questions regarding the police officers, citizens, characteristics of the encounter or interaction, tactical variables, and the situation itself (Mastrofski et  al., 2010; Worden & McLean, 2014). A codebook usually consists of close-ended questions (see Mastrofski et al., 2010; Rengifo et al., 2018), but some researchers refer to multiple choice outcomes, openended questions, narratives and verbal descriptions (e.g., Reiss, 1971; Rengifo et al., 2018; Todak & James, 2018). Researchers should review prior research and, if possible, obtain instruments from other researchers. To provide some examples, we have posted observation instruments at https://doi.org/10.6084/m9.figshare.22266217. Once the codebook is developed, outside experts should review it. Methodologists, police researchers, and/or police practitioners, could provide input on the content, clarity, and feasibility of the observation instrument (Todak & James, 2018). The codebook should be tested during some exploratory observations to optimize it and revise it into a final version. When the codebook is finalized, it can be programmed as a survey in a software program for efficient data collection and processing (e.g., Qualtrics). Codebook Creation and Practical Considerations The BOSS-D codebook on police decision-making was developed based on previous literature4 and experiences derived in the preceding research phases. More specifically, interviews were conducted with police officers to explore how decisions were made and which factors affected them. These interviews provided insights about elements of decision-making by police officers and these factors, organized at four levels, were translated into codebook items. The codebook was centered around these factors, namely:

 Especially the research and codebook of Van Damme (2017) were useful in developing the codebook for the BOSS-D project. The BOSS-D codebook was later shared with other researchers, including Van Leeuwe (2022). The sharing of these codebooks proved very useful in designing SSO studies and drafting codebooks on related topics. 4

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–– Officer characteristics, such as gender, age, years of experience, ethnicity, and personality. This information was collected through a personality and background characteristics questionnaire that respondents filled out before, during or after the observations. –– Civilian characteristics, such as age, gender, apparent social class and ethnicity, and whether the citizen is known to the police and has a criminal record. –– Organizational characteristics, such as laws and other regulations, whether or not the police officers regularly work together, and whether or not the supervisor(s) played a role in the decision-making process. –– Situational characteristics, such as type of location (e.g., public vs private), work pressure (in terms of number of encounters, calls, or tasks), whether or not the police were recorded by citizens, the number of police officers, and the number of citizens. A fifth part of the codebook included general information about the date and duration of the shift, the time of the specific observation, the type of encounter, which decisions were made and by whom, and whether the encounter resulted in a written account. Throughout the different parts, some methodological questions were included (e.g., percentage of the encounter that could be observed, changes in the behavior of police officers or citizens when the observer was present to gauge reactivity). Another interesting question relates to whether the observer faced any moral dilemmas during the observation.5 As we briefly mentioned before, the COVID-19-crisis impacted the SSOs in the BOSS-D project. The codebook was drafted before COVID-19 struck. When the observations started, police work was organized differently and several regulations focusing on COVID-19 were introduced. Although this affected the observation period largely, the observer used this unique period to include variables concerning COVID-19 in her codebook (e.g., wearing face masks, adhering to social distancing), regarding police officers and citizens. The LAPD-PJ project was able to secure instruments with the assistance of Drs. Mastrofski and Jonathan-Zamir that covered improved measures of procedural justice (Mastrofski et al., 2016). The codebooks were programmed into Qualtrics and by using unique event and ride identifiers some field coding was possible using mobile hotspots during the down time on shifts. An example of the Qualtrics survey used for LAPD-PJ can be accessed here: https://doi. org/10.6084/m9.figshare.22266217

 This was, for example, the case when the observer was asked to frisk a female person in terms of safety because there were no female police officers at work. The observer had to balance between her objectivity because of her role as an observer and her helpfulness toward the police officers. Moreover, national legislation clearly states that police officers can ask citizens to conduct such a frisk, which made it difficult to turn down this request. The observer conducted the frisk (after she had been given instructions on how to do so) and included this situation in her notes. 5

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Procedures Researchers should specify their data collection procedures and produce a manual which allows replication (Schulenberg, 2014). Such a protocol would ensure reliability among observers; that is, they interpret things in the same way (Rengifo et al., 2018). Clear coding instructions and operationalizations need to be provided that help observers consistently register their observations, which can enhance the reliability and validity of the SSO project (Schulenberg, 2014). Such a manual or protocol is useful for projects with multiple observers and sole observer-projects (Van Damme, 2017). The way in which observers interact with police officers is important. There are some situations where being entirely passive during the observation or refusing requests for assistance can impede the development of rapport, and thus the data collection itself (Schulenberg, 2014). Officers may request the observer to hold a flashlight, diagnose computer problems, or to look for suspicious vehicles. Doing these simple tasks shows reciprocity, and the validity of data is believed to be enhanced as participants will be more comfortable in the presence of observers. This means that helping participants with minor aspects of their work can put them more at ease. Observers should find a good balance between adapting a more active and a more passive role, depending on the situation. For instance, in the study of Todak and James (2018), the observer could interact with the subject during the ride but not interfere in interactions with citizens. In POPN, observers were allowed to assist police officers if there was a clear, present danger to someone involved (Spano & Reisig, 2006). These aspects should be agreed upon in advance, and when they occur, interactions should be noted and cases debriefed. Several studies report that research participants may “test” an observer during the observations (Mastrofski et  al., 2010; Reiss, 1971; Schulenberg, 2014; Van Damme, 2017).6 Testing can take different forms: participants may try to learn what other observers have reported about them or their colleagues; they may check on whether the observer gives certain information and to see how this information is evaluated7 (Reiss, 1971); or they may test someone’s knowledge of the organization or opinions on controversial topics (Schulenberg, 2014). Reiss (1971) found that the testing of observers declines over time, as the observers are accepted by the participants.

 Schulenberg (2014) explains that such questions can emanate from a culture of suspiciousness and hostility toward outsiders. The longer an observer is present in the organization, the less suspicion and testing may occur. 7  Observers should not give the idea that they evaluate participants’ behavior – they should make clear that they are there as a learner (Mastrofski et al., 2010). 6

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Development of Procedures The field manual for the BOSS-D project was built around the stages of an observation, specifying the different steps necessary to prepare and conduct an observation shift: –– What to do before the shift (e.g., looking up the most recent COVID-19 regulations and assuring that electronic devices were charged). –– What to bring (e.g., badge to enter the police force, face masks, notebook, informed consent files, information letters for civilians, a small flashlight8). –– What to do at the start of the shift (e.g., informing police officers, providing informed consent files to sign). –– What to do during an observation (e.g., taking notes during an encounter, specific guidelines on what to do when the police officers split up,9 specific guidelines on providing information to citizens).10 –– What to do after an observation (e.g., holding a debriefing with police officers, taking notes on the observation). –– What to do at the end of the shift (e.g., holding a general debriefing if this was infeasible in between encounters, thanking police officers for their time, registering the end time of the shift). –– What to do after a shift (e.g., filling out the codebook in Qualtrics or directly in SPSS, processing the written notes). Throughout the manual, specific coding instructions and guidelines were included to enhance consistency. For instance, the manual defined that the first police officer was always the person that drives the police vehicle – if no one drove a vehicle, the officer taking the initiative in a situation was considered to be the first police officer. The manual further outlined the safety procedures to be followed (see earlier) and the role of the observer. For example, the observer could not do police work (unless absolutely necessary), and she could not include information that could identify a police officer or citizen. Finally, the manual included a list of abbreviations used in the codebook and

 This was extremely useful to shine a light during nightly walks or searches, as well as to write notes during night shifts or in the dark. 9  The manual explained that when the police officers split up, the observer should follow the interaction that is most relevant for the study. Generally, interactions with citizens were considered to be more important than looking for evidence or searching a database. However, if the observer had to choose between two types of interactions (e.g., one police officer takes a victim statement, while the other talks to neighbors who might have seen something), this division was less clear. 10  The manual specified that information should preferably be provided at the end of an encounter (to minimize the observer’s influence on the police–citizen encounter) and that it should be made clear that the observer is not a police officer. Information on the research (and potentially an information flyer) should be provided when citizens ask questions about the presence or role of the observer, but the observer could proactively give this information when the citizen seemed to be in doubt and the situation so required. 8

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defined terms of significant importance for the research. Examples are the terms “decision” and “observation.” In the LAPD-PJ project, experienced SSO researchers delivered an interactive lecture on “Doing the Rides,” which covered the major elements of expectations in the field: –– –– –– –– –– –– –– ––

Obtaining consent. Explaining the nature of your observation work to officers you observe. Do not take notes in the presence of citizens. Build rapport with officers and tips for conversational steering. Forbidden behaviors (solving crimes for police, post-shift contact). Confidentiality – in an age of cell phones, no photos or selfies whatsoever. Responses to citizen inquiries. Special circumstances such as emergencies or experiencing harassment.

Role playing responses to difficult questions in a low-stakes setting was helpful for building the skill of deflecting or redirecting questions, which is vital for fieldwork. Slides that correspond to this lecture can be found here: https://doi.org/10.6084/m9.figshare.22266217

3.3.2 Training Training on operationalizing IPSSO should focus on getting observers acquainted with the codebook, protocols, and methodology. In the SSO literature, several researchers refer to training sessions organized in the course of their project. These trainings are organized in different ways, but focus on SSO methodology, active discussions on coding protocols, practicing using vignettes, and training rides (see Mastrofski et  al., 1998; McCluskey et  al., 2019; Todak & James, 2018; Piza & Sytsma, 2016). The duration of training differs substantially. Dixon et al. (2008) provided 30 h of instruction in small seminar classes, in which observers were taught how to work with the codebook and how to record observations. Hoeben et al. (2018) refer to a training of 1.5 days, in which observers were introduced to the theoretical background of the data collection, safety precautions, the data collection software, and protocols. Sykes (1978) refers to a training of more than 3 months, using a training package consisting of written material, videotapes, and a training manual of 300 pages. POPN training included a semester of coursework, IPSSO training rides in departments separate from those studied with coded data and detailed narratives, and training rides and on-site coding. Observers were hired from among the top performers in the courses.

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Training Observers Training in the BOSS-D project was threefold. First, the available literature was consulted to understand the different steps of an SSO project. Second, conversations were held with a previous SSO researcher to learn about her experiences, difficulties, and good practices. Third, the observer co-organized and followed an observational training during a doctoral training program, in which an expert in the field (Dr. McCluskey) provided a 3-day training on how to apply observational methods to police research, including practical exercises in the field. The third type of preparation was hands-on and proved extremely useful to prepare for the SSOs. Although training for SSOs was rather intensive and took up a decent amount of time, having to train only one observer made it more feasible to do this in a short period of time. Training in the LAPD-PJ project involved assembling materials for review by observers and conducting a several day, classroom-based, review of the prior research using SSO, what its strengths were, and what the process for coding and narrative writing would entail. The training also involved rides with senior lead officers to familiarize observers with LAPD processes and the geography of the two divisions and to provide an introduction of the observers to the patrol officers in each location.

3.4 Piloting As implied above, pilot testing the observation instrument before starting the fieldwork is essential for successful data collection (see Lum et al., 2020; Mastrofski & Parks, 1990; Todak & James, 2018). Van Damme (2017), for instance, conducted exploratory observations to finalize her codebooks and the data collection process, to get to know the participants, and to explore how to inform the heads of the police forces and the participants themselves. Piloting, Testing, and Feedback Piloting of the codebook and observation procedure for the BOSS-D project was done during exploratory shifts. Initially, the observer intended to conduct one exploratory shift (i.e., pilot shift) in each police force to test the different observation instruments. However, due to the COVID-19 crisis, all exploratory shifts were cancelled. Eventually, after 4  months, one police force decided to start up the observations and allowed two exploratory shifts and to start the actual observations immediately after. One exploratory shift was conducted with both intervention and criminal investigation; a second exploratory shift was organized with intervention alone.

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Based on the exploratory shifts and feedback from both experts on police observations and police research, the codebook was revised, and additional coding instructions were provided. Testing the instruments was very important to make sure that all coding instructions were clear and data could be gathered as consistently as possible. The LAPD-PJ project made changes to the codebook that were consistent with the reality of two officer units that were being observed. For example, the lead decision-maker might switch off between driver and passenger officer, and to maximize observed contact with citizens and the police who make decisions about what to do in the encounters, the instruments were adapted to this reality. Either officer could be identified as the lead during the shift. In other observations, such as those done in POPN, with single officer units, this was a static decision, but in LAPD, officers had a contact (lead) and cover (backup) tactical approach, agreed upon when they exited the vehicle; thus, observers knew to follow the lead officer and could explain that process to the patrol team upon commencing observation.

3.5 Collecting Data 3.5.1 Planning and Sampling The planning process includes determining when observations should take place and how many are needed. The amount of time in the field depends on resources, number of observers, and the number of observations needed to achieve the research goals. Myrstol (2012), for instance, conducted observations for 28 consecutive days in January 2004. Reiss (1971) had 36 observers in three cities and deployed them over seven consecutive weeks during the summer of 1966. For Sykes (1978), however, data collection took over a year. A crucial aspect in the planning and sampling of observations concerns the number of observations that should be performed. This will depend on the specifics of the project, and researchers should define what they hope to achieve at the outset. Multiple types of objectives can be defined, such as achieving a minimum number of hours of observation or registering a minimum number of observation units (e.g., number of police citizen-encounters). Throughout the SSO literature, the numbers and types of observations vary. For example, researchers report 129 h of observation for calltakers (Lum et al., 2020), and 650 h (Myrstol, 2012) and 3000 h for patrol (Sykes, 1978). Researchers also report diverse numbers of encounters or observation units that have been observed or analyzed, ranging from 94 disturbances in Denver (Bayley, 1986) to 3500 police-suspect encounters (Terrill & Mastrofski, 2002). Researchers have also defined their aims in terms of the number of police officers observed, especially when police officer characteristics are built into the research design (e.g., >10,000 subjects in the project of Sykes, 1978).

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As part of the planning process, researchers should decide how to sample observations. Worden and McLean (2014) report that most large-scale observational projects have sampled spatially (geographic space) and temporally (i.e., during distinct time periods such as patrol shifts11) but oversampled the busier beats and shifts. Although oversampling busier shifts results in more efficient data collection, such oversampling could result in bias and should therefore be applied cautiously (Myrstol, 2012). Worden and McLean (2017) sampled incidents on which they had surveyed citizens, but oversampled arrests and field interviews to ensure that separate analyses could be performed on the subsamples. Other sampling methods are event sampling (when events have a clear start and end), focal sampling (e.g., selecting specific participants), and scan sampling (scanning for a behavior or event and noting its occurrence). Van Damme (2017) and McCluskey et al. (2019) refer to the random selection of police officers for their IPSSO. Random sampling was done to avoid superior officers from assigning those police officers that they have most confidence in and believe are exemplary in dealing with citizens. Random sampling was also applied by Sykes (1978), Dixon et  al. (2008), and Myrstol (2012). The latter used a randomized sampling procedure to select the days, times, and geographic areas to be observed. An important consideration regarding planning and sampling of IPSSO is to leave some time between observations to process data on the one hand – Schulenberg (2014) stresses that most SSO studies have at minimum 2 days between observations (though admitting that that was impossible in their own research project) – and to limit the risk of over identification on the other hand (Van Damme, 2017). Intense observation schedules and high levels of workload per observation session could increase work fatigue and exacerbate the physically and mentally taxing nature of field research (Spano, 2005). Exhaustion should be avoided as it can undermine the accuracy of data collection and processing. As such, it is desirable to ensure short observation sessions and to restrict the number of observations per observer (Hoeben et al., 2018). Lum et al. (2020), moreover, report that observations were scheduled every day of the week in 2-h time slots to minimize disruptions to shift changes of calltakers and dispatchers. Planning, Sampling, and Numbers of Observations For the BOSS-D project, sampling occurred in different ways. The observer first sampled geographically by randomly selecting five police forces. For intervention, she then sampled temporally by selecting shifts. Busier moments were not oversampled; rather she tried to accomplish a varied set of observations, including morning, evening and night shifts.12 These shifts were agreed

 Researchers should also consider whether or not overtime will be included in the observations (e.g., Van Damme, 2017). 12  Practical considerations should also be considered when defining the sampling strategy, such as the availability of resources and a car. The observer in the BOSS-D project was only able to conduct late night shifts because she possessed a driver’s license and a car, and because resources were available to finance the expensive transportation costs. 11

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upon with each police force, usually contacting the person responsible for the planning of these shifts for officers, either in person, by phone, or through e-mail. For criminal investigation, she joined two shifts to understand how a criminal investigation shift is organized, but further observations were organized by means of event sampling. For instance, criminal investigators called the observer when they were about to conduct an interrogation or polygraph test and the observer joined for those events specifically. Finally, at the beginning of the observation period, a focus sampling strategy was applied as the observer was initially coupled with police officers who had also participated in the interviews – which would enable her to make a one-on-one comparison between what was said during the interviews and what was observed during the SSOs. In a later stage of the observations, however, the observer was randomly assigned to shifts, regardless of who participated in the interviews. This eventually resulted in 213 police officers participating in the SSOs. The SSOs took place from October 2020 to March 2022. Because the observations lasted for more than a year, seasonality effects were countered. The original plan was to conduct 600 h of observation, but the observer ended up observing for more than 2000 h as a result of the COVID-19 pandemic. Because of the pandemic, the shifts in the first few months of the SSOs were rather calm and did not provide sufficient units of analysis. As the timing for the project was limited, the observer shifted from conducting two to three observation shifts per week to up to six shifts per week. This was very intensive and negatively affected the time available for the processing of the observation notes. In the LAPD-PJ project, shifts were analyzed for the typical call load so that busier times could be sampled. Captains at each division provided research staff with full lists of officers working specific shifts and days during a particular time period (usually 8  days). This list contained all patrol officers and supervisors regardless of assignment and included all shifts, termed “watches.” We determined that supervisors and those officers who were assigned to desk work would not be observed as their interaction with citizens would be limited. Ultimately, uniformed officers on patrol (including special units) were randomly selected for observation based on their shift assignment. Up to five officers within each stratum were identified as potential participants each shift since sometimes sick days or court might make observation impossible.

3.5.2 Taking Notes Taking notes sounds straightforward, but researchers need to specify what is needed and what should be written to ensure the systematic collection of information (Mastrofski et al., 2010). Researchers should explain in detail what, how, and when to take notes in their protocol or manual. What should be written down depends on

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the codebook and the topic of the research project. When considering how to take notes, an abbreviation system or shorthand might be worthwhile to facilitate the taking of notes. Van Damme (2017) suggests that a fast writing style with abbreviations is necessary to observe and take notes at the same time. Other researchers argue that it is better not to take notes during the encounter itself (Schulenberg, 2014). Mastrofski and his team (2010) suggest taking little notes (e.g., using keywords) and writing them out in a narrative shortly after the observation period – ideally within 24  h of the observation shift (Schulenberg, 2014). During the POPN study (Mastrofski et al., 1998), observers took brief notes on a small notepad that could be carried in their pockets or purses. Observers explained to their participants that taking notes is part of their job, similar to police officers’ duty to report. This helped police officers understand the reasons behind this and enhanced rapport between both. Researchers may also consider using electronic devices to record observations. McCall (1984) argues that these may increase the reactivity of measurements, but Mastrofski et al. (2016) imply that recording a situation and coding it later has some advantages because multiple observers can test inter-reliability and there are no recall problems.

How and When to Take Notes The observer of the BOSS-D project tested different ways of taking notes during the exploratory shifts. She concluded that bringing a tablet, directly registering the information in Qualtrics, was infeasible for observations in which different interactions took place and she needed to shift between different “pages” of the survey. Paper codebooks, printed as little booklets, worked well during the first couple of shifts, when there were only a few observations during each shift and the observer could easily finalize the notes between police–citizen encounters. When the number of observations per shift increased, taking notes in a notebook was more feasible. This way of working made it easier to note the interactions between police and citizens and how the decisions were made chronologically – especially considering the abbreviation system used. Toward the end of the observation period, and particularly during the most intensive shifts, it was not always feasible to take thorough notes during all observations. If that was the case, the observer wrote down some keywords to describe the encounter and used these keywords to reconstruct the encounter after the shift. This was usually done on the ride home; the observer then recorded herself talking about everything she had seen. When she arrived at home, she used the keywords to determine whether she had audio-recorded all necessary information. The observer usually took notes during an encounter and right after, for instance when the police officers returned to the police station. There were, however, a few situations in which it was not comfortable to take notes. A

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clear example is a situation regarding a domestic violence victim, that had left her house to escape the violence. When seeing the observer take notes, she thought that the researcher was part of the social services and was present to assess whether she was allowed to keep her child. It became clear that the woman’s first child had already been taken away from her by the social services and that she was terrified that that would happen again. In this situation, the observer stopped taking notes, taking into account the woman’s well-being. In the LAPD-PJ project, given the location in the backseat of the vehicle, the observer had ample opportunity and space to use electronic tablets to take notes on every encounter. Further, a “lite” version of the coding instrument which captured the encounter sequence and key characteristics of the persons encountered in the role of “citizens” were used to capture data immediately following encounters. This was coded into a Qualtrics survey form and, by using key identifiers, could be merged with data coded outside of the field when narratives were also completed. The decision to use the tablet and establish connectivity via mobile hotspots was one of efficiency, so that duplicate work, of taking notes by hand and noting participants’ characteristics, could be recalled and completed before leaving the field.

3.5.3 Debriefing SSO is extremely feasible for those events or behaviors that can be objectively observed. SSO is less conducive to understanding the internal thought processes of participants. However, multiple projects focusing on police discretion and decision-­ making involve these thought processes as main aspects of the research design. In these cases, debriefing after an observation could help to map police officers’ thoughts. Previous SSO projects engaged in debriefs. Lum and her colleagues (2020) asked calltakers a couple of questions when they were not engaged in calls. Others informally asked police officers to describe what they were thinking and feeling during an observed encounter (Gould & Mastrofski, 2004; Mastrofski & Parks, 1990; Mastrofski et al., 1998) or why they took certain decisions and what influenced their reactions (Schulenberg, 2014; Van Damme, 2017). For example, Terrill and Paoline (2007) used the debriefing data in POPN to explore the reasons behind officers’ decisions to not arrest suspects that they otherwise had probable cause for taking into custody. This information can be used to learn more about how decision-makers attend to and process information and make choices. The debriefs serve as a supplement to conventional analysis from which we draw inferences about decision-making (see Worden & McLean, 2014).

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Debriefings to Understand Police Work To further understand police decision-making, in the BOSS-D project, openended questions were asked concerning the reasons why certain decisions were made or why a situation was resolved in a particular manner. Questions were sometimes asked during an encounter, provided that the observer never disturbed encounters with citizens. For instance, this was possible when waiting for a coroner after a body had been found. However, questions were usually asked immediately after an encounter or when driving back to the police station in a regular police car.13 If neither of these options were possible, the manual stated that a general debriefing could also be held at the end of the shift, discussing multiple encounters at once. But because of time constraints, end-of-shift debriefings were rare. Overall, the practice of conducting debriefs immediately after a police action is recommended.

3.5.4 Leaving the Field Virtually none of the SSO researchers discusses the phase of “leaving the field” in current academic literature. An exception is Van Damme (2017), who explains that she provided little chocolates as a thank you for all police officers participating in her project. Leaving the field, however, entails more than merely thanking respondents, as is explained in the box below. Considerations When Leaving the Field In the BOSS-D project, the observer thoroughly prepared how to “leave the field” at the end of the observations. First, she individually thanked each police officer at the last shift she accompanied with that person. She also took time to explain to officers why the observations ended, what would happen to the data collected, and how they would be briefed about the findings of the research. Participants were also able to contact the observer after the SSOs should they have any questions. Second, exit conversations were held with the chief of each police force and the person who was assigned as the observer’s point of contact. These meetings were organized on the observer’s initiative to discuss how the observations went, the cooperation received and difficulties experienced, what would happen next with the observation data, and how the project would proceed. The observer also explored how police forces wished to have the results communicated in the police force. Most importantly, however, the observer

 When the ride back took place in a police van, it was sometimes impossible for the observer to hear the police officers and vice versa. 13

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explicitly asked for feedback on her presence in the police force and if there had been any remarks regarding her observation tasks. This information could prove useful for future research projects. The main conclusion here was that an open, respectful, and transparent attitude had helped the observer to gain trust and confidence from police officers. Police officers felt that the observer attached great importance to confidentiality and anonymity, which was one of the reasons why respondents did not feel the need to withhold information. A final element discussed during the meetings, and one that relates to a final step in leaving the field, concerned to what extent the observer could revisit the police forces. As all police forces agreed that the observer could come back to the police force at any time, this invitation was used whenever possible to give an informal update on the research project. This was well-received by respondents as it was an easy way to keep in touch with the research project. As such, “leaving the field” was done rather gradually by intermittently keeping in touch with the police forces. In the LAPD-PJ project, a long-standing cooperative research collaboration had been formed between Justice & Security Strategies and the department. The SSO project built on that foundation, and the research team worked to provide useful resources including reports, presentations to command staff, and publications that highlighted the advantages and challenges that BWC presented for the department. Such long-term collaborations and partnerships help to inform the context of research, establish limits of inferences and generalizability of the data, and can open new questions for researchers which are consistent with the “action-research” approach that has been highlighted elsewhere.

3.6 Processing Data After collection of the necessary data for the project, these data need to be processed for future analyses. Processing SSO data is done in three stages, of which the two first steps can be performed simultaneously or in different order. First, the field notes are transcribed into detailed accounts or narratives, outlining the encounter and what has been observed. Second, the coding instrument is used to enter data directly into a software program (e.g., Qualtrics), although this can also be done before the creation of narratives. Third, the narratives could be coded according to a protocol (Mastrofski et al., 2002). Mastrofski and his colleagues relied primarily on field notes and narratives rather than a direct data entry form, though they did streamline this process later. The creation of narratives is ideally done within 8–12 h after the shift (Schulenberg, 2014) to diminish recall errors. The processing of field notes is time-consuming (Brunson & Miller, 2023). Van Damme (2017) reports that it usually took more than 8 h to process the data of one

3.6 Processing Data

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ride (i.e., shift of approximately 8 h). Schulenberg (2014) argues that the rewriting of observation sheets and the writing of narratives took approximately 12 h for each 10-h shift.

3.6.1 Creating Narratives Narratives, detailed accounts of the event, are written based on field notes.14 The purpose of such narratives is to contextualize the quantitative data. A narrative should include some essential aspects: a detailed description of the situation and the interactions between the parties involved, whether the participants seemed to alter their behavior during the observation, and the role of the observer. The latter includes whether they performed certain tasks in the situation, if they had an impact on the situation, and even how they felt during or after the observation. Concerning the participants’ behavior, Reiss (1971) made observers answer a question at the end of the shift, related to their belief, if participants were behaving in an “unnatural” way because of the observer’s presence. Assessing whether this is the case may be rather challenging. The SSO guidelines included in the manual can specify how and when to create narratives. Concerning the latter, guidelines can be provided on whether field notes can be processed during police officers’ downtime. Van Damme (2017), for instance, started to process her field notes when police officers were doing paperwork, but she was usually interrupted by an urgent call. During most of the observation moments, there was little or no opportunity to process the notes.

Creating Qualitative Narratives In the BOSS-D study, the observer started writing out the narratives during downtime of police officers (usually at the police station) and/or in between police–citizen encounters. If this was infeasible, the notes were further processed after the shift. To create narrative accounts, the researcher created a template that outlined what precisely needed to be written down and how to structure the data. This template significantly facilitated the data processing and enhanced the consistency of the narrative accounts. At the top of this template general information was provided: the anonymous code of the police force in which the observation took place, the target group (i.e. intervention or criminal investigation), the shift number, the date of the shift, the duration of the shift, and the police officers’ unique codes. Additionally, a visual overview

14

 When observers use recordings instead of IPSSO, the footage should first be transcribed.

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is given of the different observations per shift and each observation’s unique code and timing. For each observation, a narrative was then added that described the situation and the interactions between the police and the citizens and the reasons given for the decisions made. The narrative accounts provide a qualitative explanation of the variables included in the codebook and are an equally important part of the analyses. The template was also used to process the voice memos, which were converted to text. To facilitate this processing, the observer used the AI tool sonix. ai15 to (literally) transcribe the recordings. Using this tool saved the observer a lot of time as she could easily listen to the audio recording to verify the accuracy of the transcription and could rearrange that text to create a clear narrative. Transcribing audio-­recordings in this way was eventually more efficient than processing written notes. The audio recordings were deleted after transcription. The LAPD-PJ project instructed observers on the format and shorthand for writing narratives within the observer manual and training. Field note structure was specified to help facilitate this, and example narratives from other projects were de-identified and used as resources for teaching observers the skill of writing up these accounts. Further, team leaders reviewed narratives and offered feedback to specific observers who needed some coaching in how to write up events efficiently and with maximum needed information included, especially with judgements about the causality of events that might be needed as a reference to the coded data. For example, patterns of police and citizen disrespect were of keen interest, and if disrespect were coded, it was expected that this detail would be captured in the narrative. Quality control of written and coded accounts is important for team-based SSO.

3.6.2 Coding Coding, sometimes based on the narratives, is an essential part of SSO. This is what makes SSO more structured than traditional types of observation. This is done by means of a sheet, instrument, or survey and sound operationalizations to improve consistency. More specifically, observers fill out the instrument for each observation, preferably directly in a software program that allows for efficient data analysis. For instance, the codebook can be inputted in Qualtrics, an online survey software,  The voice memos did not include personal information of police officers, nor did they include any information that could identify the police forces and police officers involved. The recordings solely included the observer’s spoken notes on police–citizen encounters in an anonymous way. As such, there were no issues regarding anonymity of respondents. If that is the case, researchers should clearly investigate the way in which these tools process and potentially save the data uploaded therein. 15

3.7 Analyzing Data

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after which an observer fills out this questionnaire for each observation (McCluskey et al., 2019). This allows for a quick transformation to an SPSS-database. Another example is BORIS, an open-source software for video-based behavioral coding (Friis et al., 2019). The narrative descriptions and information as a result of debriefings can be inputted in Atlas.ti (Terrill & Zimmerman, 2022) or Nvivo to qualitatively identify important topics or arguments (Bonner, 2014; Sytsma & Piza, 2018). Coding instructions are extremely important to assure consistent coding. Clarity, specificity, and precision of instructions improve coding accuracy across observations and observers. Nevertheless, consistent coding can still be challenging, and measures can be taken to ensure quality controls. In summary, researchers recommend at least two coders and rely on a third one in case of inconsistencies or doubts when coding from narratives. Gould and Mastrofski (2004), for instance, worked with a third coder if there was any discussion on the coding of items derived from field observers’ written accounts. McCluskey (2003) also coded supplemental data from narrative accounts, using observers’ field coding to identify relevant encounters. Reliability checks using a separate coder were also conducted in that research. The reality of IPSSO coding, however, typically relies on only one coder capturing data in the field consistent with the codebook and coding protocol. This problem can be partly dealt with by having a sample of the observations coded by a second coder (e.g., a colleague) and to discuss the coding process extensively after this first sample. This can also be a way to enhance reliability of coding. Quantitative Coding Software In both BOSS-D and LAPD-PJ, the codebook was programmed in Qualtrics to facilitate electronic recording. For each observation, the observer(s) filled out the codebook in Qualtrics as if it were a survey directed toward the observer. After all data had been inputted, the Qualtrics data could be downloaded as an SPSS database, merged using identifiers, and could be used for further analyses. Although the coding process was very time-consuming, Qualtrics was a good tool to support electronic coding. Nevertheless, at the end of the observations in the BOSS-D project, the data were eventually inputted in SPSS directly to eliminate this intermediate step.

3.7 Analyzing Data The possibilities to analyze SSO data are numerous and depend upon the variables included in the codebook, the type of data gathered and the aims of the research. We simply wish to highlight again that SSO allows for both quantitative (e.g., through SPSS or R) and qualitative analyses (e.g., by means of Nvivo). A third type of analysis can relate to methodological assessments of potential biases, observer effects, and reactivity. In this regard, Spano (2005, 2007) encourages observers to create semi-structured field diaries to document reactivity and observer bias. It can be used

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as a quality check, but also to improve observer training. One of its main limitations, however, is that such diaries imply that observers need to evaluate themselves (e.g., self-assessment of overidentification), which may be quite challenging.

3.8 Reporting Findings A final step in the SSO procedure is reporting about the project. We recommend researchers to report their findings on different levels: for the research community, participants, and the police organization. Reporting to fellow researchers can be accomplished through scientific articles and presentations at seminars or conferences. Academics and other researchers may have a sound interest in methodological aspects. Therefore, researchers should also thoroughly report their SSO methods: How was the project structured? Which research questions and aims were formulated? How was the codebook developed and which variables were included? How were the observations performed? Which difficulties were experienced? Which events had an impact on the data collection (e.g., the terrorist attacks in Belgium, as was the case in Van Damme, 2017)? What could have gone better? Which good practices were identified? What are the advantages and drawbacks of the data gathered? A detailed outline of these aspects can help other researchers to set up their SSO project. We also strongly recommend sharing observation materials and the observation data (either raw or processed) to allow for further analyses. Furthermore, these materials can be used to develop new codebooks and SSO procedures. For the police, researchers should consider making brief videos, visualizations, or factsheets instead of a full, technical written report. The target population is less interested in methodological aspects of the study and more interested in the findings that are relevant to their work. Reporting Findings at Different Levels The results of the BOSS-D and LAPD-PJ studies were communicated at different levels. For one, the researcher(s) wrote several research articles on these findings that were mainly directed at other academics and police researchers. The findings were also included in presentations at seminars (directed both at practitioners and police researchers) and conferences. With respect to the police, results were mainly discussed in the form of presentations that are more practitioner-oriented with LAPD-PJ being presented at a BWC research convening hosted at the LAPD headquarters. With regards to the BOSS-D project, as discussed during the exit conversations, verbal communication was preferred over written communication as it is more personal and allows for discussions between the observer and the participants (and other police officers). Nevertheless, information sheets are also drafted – these sheets summarize and visualize the main findings of the SSOs. A report is also drafted for the interested reader who wishes to learn more about the findings. Furthermore, published articles are also sent to the police forces to keep them up to date about the project.

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3.9 Conclusion The sequential presentation offered here prepares the potential SSO research team leader(s) with a starting point for a project and important touchpoints for consideration at the outset of such an endeavor. Technological, training, and codebook choices are likely to be constrained by resources, skills, and time. However, what is offered here is a framework from which one can make some conjecture about time, costs, and feasibility of an approach to answering a set of research questions. Allocating resources among different tasks, once the scope of work is identified, becomes more manageable. Methodological reporting is briefly done in the most SSO scientific articles, but has been the focal point of this chapter on SSO methodology. Advantages and pitfalls, resulting in lessons to be learned and best practices, were included in this chapter to provide tips and tricks on how to conduct SSOs, particularly focusing on IPSSO. As a resource, access to prior research and existing instruments and protocols is vital to the fielding of a research project. To that end we have archived instruments, slide decks from trainings, and notes on the writing of narratives from the BOSS-D and the LAPD-PJ IPSSO projects. Researchers interested in other approaches should look for that research in archives, such as the National Archive of Criminal Justice Data housed at the University of Michigan. Codebooks and links to reports can be found for the Ostrom et al. (1977) Police Services Study, Reiss’s three city study (1966), and Bayley’s (1982) Denver study, among others. The latter is possibly of interest as it features the subdivision of contact, processing, and exit tactics and citizen responses. In many ways, that small study anticipated the time-based studies (Piza & Sytsma, 2022) and sequential force studies that followed (Terrill & Mastrofski, 2002). In addition to these resources, we encourage, where possible, that researchers share their instruments with the larger research community to ensure that replication, comparative work, and refinement of measures that can run at a pace which is consistent with social science’s best efforts. Finally, we note that SSO will not be for everyone or every question. By now the reader should have a sense as to whether the cost will yield sufficient benefits when asking: Why use SSO? If other methods have obvious shortcomings, then SSO can help to fill in important gaps in measurement. If one is interested in studying decision-­making in situ, then SSO is likely a go-to strategy, with resource constraints in mind. The combination of SSO with other methods, including training of police involving a randomized control trial (RCT), would, for example, provide unique research insights that go beyond many other designs.

Why Use SSO? In the BOSS-D project, SSO was chosen because we explicitly aimed to observe police decision-making and compare it to how police officers described their decision-­making during interviews, and no official data were

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available to capture police decision-making in practice. We focused on decision-making more generally, thereby including all kinds of decisions observed in practice, but the SSO method did allow observation of some rather rare events (e.g., a polygraph test, which is not that commonly used in Belgium). A main motivation for in-person SSO was to have the opportunity to ask questions and hold debriefings. This was an essential part of this project as we wanted to know which factors impact police decision-making and how those factors affect the police decision. Because this involves internal thought processes and cannot be directly observed, engaging with the police officers was crucial to gain a real understanding of police decision-making. In the LAPD-PJ project, pre-post observation of police officer behavior changes related to the adoption of BWC was at the core of the research question. Many experimental designs, often relying on measures from police data, such as complaints, use of force, and the like, had been fielded or were underway at the point this choice was made. An SSO of officer behavior in situ had not. Thus, the methodological choice offered a different perspective, with a different error structure in measurement from the completed and ongoing RCTs fielded to study BWC impacts. The inability to field an RCT in LAPD is a different question and maintaining rigorous distinctions between experimental and control officers, given the organizational configuration and deployment patterns, was not feasible. Thus, improving on the measurement of what police do in the context of a quasi-experiment was a reasonable choice.

References Bayley, D.  H. (1982). Effectiveness of police response: Denver. Inter-university Consortium for Political and Social Research [distributor], 2006-01-18. https://doi.org/10.3886/ ICPSR08217.v1 Bayley, D. H. (1986). The tactical choices of police patrol officers. Journal of Criminal Justice, 14(4), 329–348. https://doi.org/10.1016/0047-­2352(86)90126-­1 Bonner, H. S. (2014). Police officer decision-making in dispute encounters: Digging deeper into the ‘black box’. American Journal of Criminal Justice, 40, 493–522. https://doi.org/10.1007/ s12103-­014-­9274-­2 Brunson, R. K., & Miller, A. (2023). Police observational research in the twenty-first century. Annual Review of Criminology, 6, 205–218. https://doi.org/10.1146/annurev-­criminol-­030421-­034101 Brunton-Smith, I. (2018). Systematic social observation. In G. J. N. Bruinsma & S. D. Johnson (Eds.), The Oxford handbook of environmental criminology (pp. 293–310). Oxford University Press. Dixon, T.  L., Schell, T.  L., Giles, G., & Drogos, K.  L. (2008). The influence of race in police-civilian interactions: A content analysis of videotaped interactions taken during Cincinnati police traffic stops. Journal of Communication, 58(3), 530–549. https://doi. org/10.1111/j.1460-­2466.2008.00398.x Feys, Y. (2022a). Discretionaire ruimte en de COVID-19-pandemie: Invloed van de crisis op politionele besluitvorming en politiestijlen. Cahiers Politiestudies, 4(65), 41–64.

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Feys, Y. (2022b). Politie en de COVID-19-pandemie in België: Impact op het politiewerk, de interne relaties en politie-burgerinteracties. Tijdschrift voor Criminologie, 64(1), 103–127. https://doi.org/10.5553/tvc/0165182x2022064001006 Friis, C. B., Liebst, L. S., Philpot, R., & Lindegaard, M. R. (2019). Ticket inspectors in action: Body-­ worn camera analysis of aggressive and non-aggressive passenger encounters. Psychology of Violence, 10(5), 483–492. https://doi.org/10.1037/vio0000276 Gould, J. B., & Mastrofski, S. D. (2004). Suspect searches: Assessing police behavior under the U.S. constitution. Criminology & Public Policy, 3(3), 315–362. https://doi.org/10.1111/j.1745­9133.2004.tb00046.x Hoeben, E.  M., Steenbeek, W., & Pauwels, L.  J. R. (2018). Measuring disorder: Observer bias in systematic social observations at streets and neighborhoods. Journal of Quantitative Criminology, 34, 221–249. https://doi.org/10.1007/s10940-­016-­9333-­6 Lum, C., Koper, C.  S., Stoltz, M., Goodier, M., Johnson, W., Prince, H., & Wu, X. (2020). Constrained gatekeepers of the criminal justice footprint: A systematic social observation study of 9-1-1 calltakers and dispatchers. Justice Quarterly, 37(7), 1176–1198. https://doi.org/10.108 0/07418825.2020.1834604 Mastrofski, S. D., & Parks, R. B. (1990). Improving observational studies of police. Criminology, 28(3), 475–496. https://doi.org/10.1111/j.1745-­9125.1990.tb01335.x Mastrofski, S. D., Parks, R. B., Reiss, A. J., Worden, R. E., DeJong, C., Snipes, J. B., & Terrill, W. (1998). Systematic observation of public police: Applying field research methods to policy issues. National Institute of Justice. Mastrofski, S. D., Reisig, M. D., & McCluskey, J. D. (2002). Police disrespect toward the public: An encounter-based analysis. Criminology, 40(3), 519–551. https://doi.org/10.1111/j.1745­9125.2002.tb00965.x Mastrofski, S.  D., Parks, R.  B., & McCluskey, J.  D. (2010). Systematic social observation in criminology. In A. R. Piquero & D. Weisburd (Eds.), Handbook of quantitative criminology (pp. 225–247). Springer. Mastrofski, S. D., Jonathan-Zamir, T., Moyal, S., & Willis, J. J. (2016). Predicting procedural justice in police–citizen encounters. Criminal Justice and Behavior, 43(1), 119–139. https://doi. org/10.1177/0093854815613540 McCall, G.  J. (1984). Systematic field observation. Annual Review of Sociology, 10, 263–282. https://doi.org/10.1146/annurev.so.10.080184.001403 McCluskey, J. D. (2003). Police requests for compliance: Coercive and procedurally just tactics (No. 25927). LFB Scholarly Publishing. McCluskey, J. D., Uchida, C. D., Solomon, S. E., Wooditch, A., Connor, C., & Revier, L. (2019). Assessing the effects of body-worn cameras on procedural justice in the Los Angeles Police Department. Criminology, 57(2), 208–236. https://doi.org/10.1111/1745-­9125.12201 Myrstol, B.  A. (2012). The alcohol-related workload of patrol officers. Policing: An International Journal of Police Strategies & Management, 35(1), 55–75. https://doi. org/10.1108/13639511211215450 Nassauer, A., & Legewie, N.  M. (2018). Video data analysis: A methodological frame for a novel research trend. Sociological Methods & Research, 50(1), 135–174. https://doi. org/10.1177/0049124118769093 Nawaz, A., & Tankebe, J. (2018). Tracking procedural justice in stop and search encounters: Coding evidence from body-worn video cameras. Cambridge Journal of Evidence-Based Policing, 2, 139–163. https://doi.org/10.1007/s41887-­018-­0029-­z Ostrom, E., Parks, R. B., & Whitaker, G. (1977). Police services study, phase II, 1977: Rochester, St. Louis, and St. Petersburg. Inter-university Consortium for Political and Social Research [distributor], 2006-03-30. https://doi.org/10.3886/ICPSR08605.v3 Paoline, E.  A., & Terrill, W. (2005). The impact of police culture on traffic stop searches: An analysis of attitudes and behavior. Policing: An International Journal, 28(3), 465–472. https:// doi.org/10.1108/13639510510614555 Piza, E.  L., & Sytsma, V.  A. (2016). Exploring the defensive actions of drug sellers in open-­ air markets: A systematic social observation. Journal of Research in Crime and Delinquency, 53(1), 36–65. https://doi.org/10.1177/0022427815592451

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Piza, E. L., & Sytsma, V. A. (2022). The impact of suspect resistance, informational justice, and interpersonal justice on time until police use of physical force: A survival analysis. Crime & Delinquency. https://doi.org/10.1177/00111287221106947 Reiss, A. J. (1966). Patterns of behavior in police and citizen transactions: Boston, Chicago, and Washington, DC. Inter-university Consortium for Political and Social Research [distributor], 2005-11-04. https://doi.org/10.3886/ICPSR09086.v1 Reiss, A.  J. (1971). Systematic observation of natural social phenomena. Sociological Methodology, 3, 3–33. https://doi.org/10.2307/270816 Rengifo, A. F., Green, C., Slocum, L. A., & Ho, A. (2018). A Bronx tale: Lessons on community and police from 10 years of systematic social observations. In S. K. Rice & M. D. Maltz (Eds.), Doing ethnography in criminology: Discovery through fieldwork (pp. 265–276). Springer. Sampson, R. J., & Raudenbush, S. W. (1999). Systematic social observation of public spaces: A new look at disorder in urban neighborhoods. American Journal of Sociology, 105(3), 603–651. https://doi.org/10.1086/210356 Schulenberg, J. L. (2014). Systematic social observation of police decision-making: The process, logistics, and challenges in a Canadian context. Quality & Quantity, 48, 297–315. https://doi. org/10.1007/s11135-­012-­9769-­1 Spano, R. (2005). Potential sources of observer bias in police observational data. Social Science Research, 34(3), 591–617. https://doi.org/10.1016/j.ssresearch.2004.05.003 Spano, R. (2007). How does reactivity affect police behavior? Describing and quantifying the impact of reactivity as behavioral change in a large-scale observational study of police. Journal of Criminal Justice, 35(4), 453–465. https://doi.org/10.1016/j.jcrimjus.2007.05.008 Spano, R., & Reisig, M.  D. (2006). “Drop the clipboard and help me!”: The determinants of observer behavior in police encounters with suspects. Journal of Criminal Justice, 34(6), 619–629. https://doi.org/10.1016/j.jcrimjus.2006.09.015 Sykes, R. E. (1978). Toward a theory of observer effect in systematic field observation. Human Organization, 37(2), 148–156. Sytsma, V. A., & Piza, E. L. (2018). Script analysis of open-air drug selling: A systematic social observation of CCTV footage. Journal of Research in Crime and Delinquency, 55(1), 78–102. https://doi.org/10.1177/0022427817709502 Terrill, W., & Mastrofski, S. D. (2002). Situational officer-based determinations of police coercion. Justice Quarterly, 19(2), 215–248. https://doi.org/10.1080/07418820200095221 Terrill, W., & Paoline, E. A. (2007). Nonarrest decision making in police-citizen encounters. Police Quarterly, 10(3), 308–331. https://doi.org/10.1177/1098611107299998 Terrill, W., & Zimmerman, L. (2022). Police use of force escalation and de-escalation: The use of systematic social observation with video footage. Police Quarterly, 25(2), 155–177. https://doi. org/10.1177/10986111211049145 Terrill, W., Paoline, E. A., & Manning, P. K. (2003). Police culture and coercion. Criminology, 41(4), 1003–1034. https://doi.org/10.1111/j.1745-­9125.2003.tb01012.x Todak, N., & James, L. (2018). A systematic social observation study of police de-escalation tactics. Police Quarterly, 21(4), 509–543. https://doi.org/10.1177/1098611118784007 Uchida, C., McCluskey, J., Kringen, J., Kringen, A., Kato, S., Melendez, H., & Schmitz, J. (2022). Police accounts of critical incidents: A descriptive and empirical assessment. Journal of Crime and Justice. https://doi.org/10.1080/0735648X.2022.2080100 Van Damme, A. (2017). The role of procedural justice in the relationship between the police and citizens (PhD dissertation). Ghent University. Van Leeuwe, A. (2022). Politionele selectie: In discretie of in diskrediet? Cahiers Politiestudies, 4(65), 19–40. Worden, R.  E., & McLean, S.  J. (2014). Systematic social observation of the police. In M.  D. Reisig & R.  J. Kane (Eds.), Oxford handbook of police and policing (pp.  471–496). Oxford University Press. Worden, R. E., & McLean, S. J. (2017). Mirage of police reform: Procedural justice and police legitimacy. University of California Press.

Chapter 4

Video-Based SSO and Body-Camera Data

An emerging and cost-effective approach to systematic social observation (SSO) is available to researchers who can access body-worn camera (BWC) footage. Researchers here are broadly construed to include typical academic teams, but also teams embedded with law enforcement agencies who may be tasked with generating insights on how to improve local practice and training from existing footage. In this chapter, we focus on video-based SSO (VBSSO). The consideration of VBSSO in the study of policing starts with an assessment of how video is sourced (e.g., in-­ car dash cameras, cell phones, or closed-circuit TV). First, is the video derived from BWC or some other source? Second, does the video data come from publicly available sources (e.g., YouTube, Vimeo), or is it accessed from the archival data held by police departments to which researchers are granted access? The strengths and weaknesses of these two approaches are first compared. This chapter features field experience generously shared by two research teams that explained their respective research projects and shared insights regarding VBSSO with the authors in a structured conversation. Insights gleaned are used to illuminate key choices, obstacles, and advantages of VBSSO for other users.  All three teams have members with extensive inperson systematic social observation (IPSSO) experience, an where possible, we draw important contrasts and caveats between the two modalities for observation of the police.

The first team was responsible for coding data featured in Terrill and Zimmerman (2022). That project’s lead VBSSO coder, Logan Somers and principle investigator, William Terrill shared their experiences with us in early

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. McCluskey et al., Systematic Social Observation of the Police in the 21st Century, SpringerBriefs in Criminology, https://doi.org/10.1007/978-3-031-31482-7_4

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2023 and serve as references in the field experiences highlighted below. Their project was sponsored by the US Department of Homeland Security and was a joint study by the Federal Law Enforcement Training Centers (FLETC) and Arizona State University. Hence, we reference their project as FLETCFORCE. The FLETC-FORCE project coded data focused on the sequential application of force in two departments with a focus on escalation and deescalation patterns in police–citizen encounters.

Robert Worden, Sarah McLean, Hannah Cochran, and Beau Holladay of the Finn Institute generously agreed to participate in a similar conversation in early 2023 about a VBSSO project they conducted. Their focus was on collecting VBSSO data to illuminate the effects of supervisory coaching on officer behavior in police–citizen encounters, especially, but not only, procedural justice. Their experiences in the field are summarized under the FINN-PJ project (see Worden & McLean, 2016; Worden et al., 2019).

Finally, Uchida, McCluskey, and Solomon collected data that appears in this chapter and in McCluskey and Uchida (2023). That research was an extension of the Los Angeles Police Department (LAPD) procedural justice research (LAPD-PJ) and is denoted as such in the field experiences in the boxes that accompany sections.

4.1 Data Sources for VBSSO 4.1.1 Camera Perspectives and Public Data A threshold issue considered for this section is “What video should be considered?” The proliferation of cell phones makes the availability of police wrong-doing, use of force, discourtesy, or arrest of famous individuals commonplace and accessible on YouTube and other platforms. Police BWC footage, on the other hand, is rarely released to the public without curation, but it is the source that is of primary interest in this chapter for at least two reasons. First, it is widely collected and stored, at least temporarily, by police agencies in the United States and abroad. Second, it has a set of problems that can be discussed more coherently than if one has to entertain a variety of caveats that accompany addressing several types of video sources. For example, BWC footage is often a first-person perspective, which eliminates much of the video record of the wearer’s physical action. This is not true of third-person

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video, and fixed dashboard cameras, for example (Terrill & Zimmerman, 2022; Worden & McLean, 2017). Similarly, the BWC wearer will sometimes obstruct the lens with arms, clothing, car doors, and the like. Microphonic placement is also at issue as the audio record for the wearer is likely more reliable than that for the citizens encountered (McCluskey & Uchida, 2023). Publicly released video is one resource for researchers interested in certain questions. For example, Uchida et  al. (2022) recently examined 140 YouTube video releases of US police departments’ critical incident (CI) public information briefings, which largely include officer-involved shootings (OIS). These CI videos featured, in 84% of cases, curated extracts from officers’ BWC. Though by no means the majority of the department’s video release they represented 7.4%, or about 1 min of the overall incident video runtime in each video. The authors’ review of the BWC video and audio quality indicates these could be a source for researchers, depending on the scope of the research questions asked. The important caveat is that the curated video, decision to release, and redaction/enhancement of video likely introduce bias in any such analysis. In addition, third-party video of police, with a completely different perspective of police–citizen interactions in many cases (e.g., George Floyd video captured via cellphone), is another publicly available data source that researchers can consider. Use of such video footage does not easily allow for statistical inference because the reference population is unclear. Loss from nonactivated cameras, curation processes, spoilage or lost video or audio, and nonrelease all contribute to unknown parameters to sampling error in release to the public domain.

4.1.2 Police BWC Video as Data Police agency archives represent the second source for accessing BWC video, which is the primary focus of this chapter. Within departments, given access to agency records management systems (RMS), knowledge of their data archiving process, and retention requirements, researchers can make some approximations of representativeness of sampled videos. Using a department’s video footage to address research questions is most akin to the IPSSO noted in Chap. 2 but under circumstances where the video is sampled and can be referenced back to some population of police–citizen encounters or activities. That is, permission to observe is obtained, and the observers are able to access the video footage, with some limits. This will allow for the data to be sampled with known properties, especially in relation to the larger population of video footage within the department. More robust inferential statistical modeling will be the end result. Of course, this is dependent upon regularized deployment and usage of cameras, which in the case of one of our projects in Belgium made VBSSO impossible as the Belgian police forces included in the project did not yet use BWCs when the observations started.

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Below we take the reader through a series of steps that will aid in developing a VBSSO project and also share observations of project teams that have developed different approaches and solutions to the issues we raise. First, establishing access to a police department’s video footage entails answering a variety of questions regarding the nature and extent of the videos available and the reasons some footage may be inaccessible. Second, we will consider, in general, how to sample videos from that database. Third, ethical issues involving the access, coding, and disclosure of events in videos are reviewed. Fourth, we consider the varieties of approaches for developing codes, training coders, and assessing reliability. Each area is examined with reference to contemporary and ongoing research efforts in the field. In sum, we ask and answer: In what ways do BWC archives present challenges for research? How will researchers select or sample videos to review from archives? What are the protections for the subjects (police and citizens) who appear in the videos? What data will be extracted from the video and how will their reliability be assessed? In what ways can VBSSO be compared and contrasted with IPSSO? Finally, we offer the reader a simulation to walk through sampling and to illustrate how the small but growing body of VBSSO research could be used to develop specific approaches to executing codebook creation, training, reliability studies, and the integration of theoretical frameworks with scientific measurement and data collection.

4.2 Establishing File Processing Behind Departmental BWC Archives 4.2.1 Aspects of BWC Archival Management That May Lead to Missing or Incomplete Data Police BWC archives have varying levels of completeness and accessibility, depending on record management system (RMS) integration (i.e., 911 calls, arrests, and other reports linkable to video), policies, and officer behaviors. Specifically, activation, upload, tagging of video, retention policy, internal restrictions, and linking with records are at least six considerations in developing a sample from a departmental archive. Activation rates may vary over time, across space, and by officer (Katz & Huff, 2022). This generates systematic error, restricting what researchers can observe in the BWC record. In some departments, RMS activation rates are assessable by researchers, and often internal documentation of activation tagging are possible references that can be made by researchers. To be sure, an activation rate of 50% on a shift will produce significantly different results from one where 95% activation is the case. Patterson and White (2021) found in their IPSSO of 14 Tempe, AZ officers identified as “expert de-escalators,” that activation occurred 95% of the time. This was substantially greater when compared with overall activation rates by other

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officers, which were documented to range from 71% to 76% activation. Katz et al. (2014) noted that activation was present in less than 50% of case types where it was expected for Phoenix police officers at the very earliest point of BWC adoption, though later research suggests a much higher rate. Reporting and carefully understanding how these data gaps will propagate into a sample is important for comparison, replication, and generalization of findings involving police research from BWC archives. Uploading of local video is the point where the camera data are transferred into the department archive on the cloud or server. This process is not without spoilage, but to our knowledge, that is relatively rare. Different camera systems, however, may have different loss rates where audio, video, or both are corrupted between activation and upload or by the camera quality. Ascertaining this is particularly difficult for researchers and would require questions from the IT managers within a department. A loss rate of more than 1% on this step is, to the best of our knowledge, unlikely without intentional corruption or camera destruction. Tagging video, to our knowledge and familiarity with the process, is heavily dependent on officer data entry on their own videos and has implications for retention when “uneventful” or “mundane” video is automatically purged. While retention rates vary in the United States, agencies are purging data to make sure there is room for video in scarce and expensive storage space. Tagging involves using codes from the department to assign a retention period and event type to a video (arrests, e.g., may be retained for years, uses of force indefinitely, complaints indefinitely, and routine traffic stops with no ticket for the 6-month retention period). Proportion of proper tagging at ingestion (upload) of the video is important to consider as miss-­ tagged or untagged video may be difficult and time-consuming to access or otherwise be irretrievable. Retention of video noted above is related to departments’ resources and policies. The Los Angeles Police Department retains, at this writing, 100% of the uploaded videos since the inception of the BWC program, on the online cloud Axon Inc. provides through a portal known as Evidence.com (Uchida & Anderson, 2021). Storage space on Evidence.com, on the cloud or in an on-premise computer system, is expensive; thus, departments typically have automatic or manual erasure of videos that are not tagged in a manner that requires retention (arrests, evidentiary videos, and so on). Departments that manage their own internal archives, with finite storage and backup, are similarly constrained by video retention and storage cost limitations. The systematic loss of video will be precisely those cases that end without clear problems, but which might represent particularly useful insights into the application of the police craft. In Belgium, body-worn cameras have been implemented rather recently (Goyvaerts et al., 2022) and the use of bodycams is regulated in a national police law. The law stipulates that bodycams need to be worn visibly and that the citizen in question needs to know that he/she can be recorded. A verbal warning needs to proceed with this recording. Unless tagged as useful for an ongoing investigation, recordings are automatically deleted after 30 days. In the former case, recordings can be kept for a maximum of 365 days. Citizens cannot get access to these videos, unless it is used as evidence in criminal proceedings.

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A recent research project regarding the use of bodycams in Belgium has, however, demonstrated that police forces implement these regulations differently (Goyvaerts et  al., 2022). Because of this diverse implementation of the law, it is unclear to researchers how and where to gain access to bodycam footage for research purposes. As the videos are transferred to the Belgian judicial authorities when they have no further use for police activities (and in most cases no later than 30 days), researchers usually cannot directly ask police forces to distribute these videos. There is, however, no procedure at the level of the judicial authorities that researchers can follow to gain access either. This limited access in Belgium illustrates that understanding of the local and national patterns of BWC use and retention is vital for helping researchers navigate VBSSO research. To be sure, recorded video as data is not completely ruled out, as Friis and colleagues (2020) equipped ticket inspectors in and around Copenhagen, Denmark with BWC to collect data on aggressive and nonaggressive encounters with passengers in violation of ticketing rules. Restriction of videos is a status of lockdown on video for purposes of sensitivity and organizational desire to ensure it is not leak-able and for evidentiary use. Policies can, for example, make videos locked for administrative or investigative review for everyone but the chief and perhaps internal affairs/investigator reviews. These videos would be unlikely to be available to researchers. For example, in a study of use of force cases in Newark, NJ, internal affairs was using the video in an active investigation, and thus, it was unavailable for review and inclusion in the research (Sytsma et al., 2021).

4.2.2 Identification Approaches to Ascertain BWC Available Within an Archive In especially complex scenes, such as assemblage of use of force video with many officers, BWC present in the archive is curated in a post hoc activity done by professional standards, use of force, or internal affairs units depending on how organizations manage that process. Being aware and able to account for and access the variety of videos from such events can offer a much more in-depth perspective than the single officer video when accurate tagging conventions make such access feasible. We would caution, however, that focus solely on such curated critical incident videos, while of interest to researchers, may skew the overall understanding of policing that may aid police managers. Put simply, such samples are censored and omit cases that may have been de-escalated or otherwise prevented from being critical incidents, which provide equally interesting findings and contrasts. Linking video to the department’s RMS is an important part in identifying videos within a department’s archive. Thus, the use of force reports kept by an agency is a “look up” table, making it easier to find videos of interest in most organizations. Identification of other videos, however, can be problematic if RMS systems are not

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well integrated with the archive and can create an obstacle to efficient access and review. In our experience, some departments have exemplary integration (Katz & Huff, 2022), as illustrated by work on activation and video linkages. Other departments’ BWC archives, though apparently complete, are not directly linked to calls for service, reporting, and arrest databases from which a research team would desire to sample encounters between the police and the public. However, an important lynchpin of SSO, as a form of police observation that allows for statistical inference, is that it links back to an underlying population of police–citizen interactions in a way that analyses of all videos of a department’s complaints, uses of force, or even arrests may not. Put differently, the uses of force should be understood as having some probabilistic relationship to other videos, and this requires much work within a department’s RMS. None of these aspects of organization policy, officer action, video accessibility, or selection should be considered an insurmountable hurdle for data coding and analysis. A scientific approach to BWC, however, requires familiarity with an organization’s generating process and documentation. Establishing, to the best of one’s knowledge, how a video comes to be part of a department’s archive and how that procedure may affect sampling is an essential part of the research process that adheres to Reiss’s (1971) principles. Many departments publish occasional reports documenting one or more of the aspects outlined here soon after they adopt BWC, and referencing such material, in our judgment, is better than ignoring it.

4.3 Sampling Strategies 4.3.1 Current Research Approaches The sampling of video is a key initial question that researchers must confront in conjunction with the research questions being posed. The VBSSO approach is recognized as opening up new questions about rare events, such as the use of force. For example, recent research has sampled all available use of force in Newark, NJ (Systsma et al., 2021); all use of force and a sample of potential force videos in Newport News, VA (Schafer et al., 2022); and sampled video from a selected time period in Port Aransas, TX (Pollock et al., 2021). These approaches yield different statistical and population references. Selection limited to uses of force will leave the researcher with a sample where inference about avoiding use of force is difficult. Potentially Violent Mobilizations (as introduced by Fyfe, 1988; Bayley & Garafolo, 1989), for example, often end with no use of force. Describing and charting use of force, in contrast, is accessible, and being able to observe use of force cases and other rare events is an advantage of BWC. Schafer et al. (2022) obtained all 59 use of force cases for coding from Newport News, Virginia police, which would have required 2 years of continuous IPSSO to observe. Similarly, Terrill and Zimmerman’s (2022) work samples videos drawn from two agencies, one, a large Midwestern/

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southern municipal police force with BWC and the second, a semi-rural sheriff department with dashboard cameras, to capture and code use of force sequences to explore the phenomenon of de-escalation. An illustration of the capture of rare events outside of the use of force context is in White et al. (2022), who studied the application of naloxone to opioid overdose victims in Tempe, AZ. That team was able to describe officer actions, speed, and the outcomes of cases in a manner that heretofore had been obscured from researchers in criminal justice and public health. Other rare events, such as situations resulting in law enforcement officer injuries, are also areas where BWC archives may offer researchers substantial insights.

4.3.2 Possible Sampling Strategies We cannot offer a concrete sampling strategy for all research, but we suggest that researchers should be familiarized with departmental workflow, records management, and digital evidence management when accessing a department’s archives. This familiarity will aid in developing a sampling plan that best aligns with the research question. Those with access to organizations that allow for the integration of BWC data and the agency’s RMS can develop sampling plans, which draw on information in new ways to answer novel questions. For example, one might be interested in the neighborhood variations in police behaviors to assess issues of equity and fairness. Coding might examine procedural justice, discourteous language, and/or uses of force across geographic locations stratified by concentrated disadvantage. Geolocated videos/RMS data would allow sample selection of situations from such areal units and offer enormous cost savings over IPSSO projects, such as the Project on Policing Neighborhoods (POPN). Officers who demonstrate superior skills in de-escalation could be compared with peers on a sample of calls that involve disturbances to distill the approaches that highly skilled officers might take when compared with novice or less skilled officers. Similarly, those who undergo training in de-escalation could be compared to themselves and as yet untrained peers in a true experimental design. The VBSSO affords researchers a platform for conducting criminological/criminal justice academic research, but, in our judgment, working together with police agencies some truly groundbreaking results should become available in the coming years. Further, the archival nature of the videos, coding, and instruments should, to the extent possible, be shared among the community of researchers to advance this practice, surface problems, unreliable approaches, and false starts and ensure that the measurement is reliable and valid (see also Makin et al., 2019).

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4.3.3 Machine Learning and Prospective Augmentation of Sampling Approaches A third possibility for drawing on data would rely on the use of artificial intelligence (AI) or machine learning (ML) routines to scan BWC archives for candidate videos that could then be reviewed for research purposes. A sample could be derived from the population of videos that had been pre-processed along dimensions of interest. Natural language processing (NLP), which could convert audio channels to text and examine key words, might be such an approach to identify cases for inclusion in a study. The efficiency gains of such tools, if feasible to implement, is illustrated in the work of Holladay and Makin (2021), who studied discourtesy in a sample of one-­ on-­one police–citizen interactions. Cases of one-on-one encounters had to be identified via individual review and search of video from a department’s BWC archives. They performed this labor-intensive search to isolate a sample without the influence of bystanders so dimensions of incivility could be assessed in the police–citizen interactions. Machine-aided search that could identify bystanders, or number participants, would greatly reduce such an effort. At this writing, such machine-based applications are in their nascent stages of development as BWC presents challenges, especially for image recognition, since it is mounted on a moving participant in the encounter. It is likely that departments will seek to implement these search tools as they become available and to the extent they are, results that can be shared with researchers may further enhance the capacity for establishing representativeness of a sample of cases with reference to the larger whole of BWC encounters captured.

Sampling Approaches in Action In LAPD-PJ, a VBSSO project (McCluskey & Uchida, 2023) was used as a follow-­up to the IPSSO data collection. Rather than sample videos from the RMS, the research team identified shifts and police activities and encounters from a sample of rides conducted by the in-person observers. The research team then used the date and time stamps and unit identifiers to access a series of videos that corresponded to the IPSSO observations. This relied on the sampling plan for shifts and officers used by the IPSSO to obtain 102 videos and a total of 46 police–citizen encounters. It is important to note that in the case of the LAPD, officers were deployed in two-­person units, so multiple cameras were typically available for review in each encounter. In contrast, researchers working on the FINN-PJ project used the RMS of a mid-­sized metropolitan police department to draw their sample. That team began sampling officers who represented randomly assigned treatment and control groups for a supervisory coaching intervention, which was anticipated

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to affect their performance in contact with citizens. Once officers were identified, they sampled calls for service (CFS), stops, and arrests. The CFS were oversampled for types that would likely be more challenging and offer opportunities to examine the application of skills and judgment by officers. This approach to sampling allowed for statistical inference back to the population of police–citizen encounters of certain types. The FLETC-FORCE project obtained data from one municipal department’s BWC archive and a rural sheriff’s dashboard camera archive for their research project and characterized it as a convenience sample of interesting events and encounters drawn from two agencies. In this instance, no access to the local RMS was available, and the agencies drew video samples that would be of interest to help explore officers’ use of escalation and de-escalation in police–citizen encounters. This would then be considered a convenience sample of video data.

4.4 Access Locations and Human Subjects Protection 4.4.1 Data Access In our conversations with researchers and review of materials from ongoing projects, there are a variety of ways that access has been established. For example, David Makin and Dale Willits at Washington State University operate The Complex Social Interactions (CSI) lab, which has an Evidence.com linkage with Criminal Justice Information Services (CJIS) approval and is governed by a set of regulations and requirements for background checks and nondisclosure agreements for coders. In contrast, use of force data collected in Newark was coded by a single VBSSO observer who had access to video review terminals on-site at the police department (Sytsma et al., 2021). Review of LAPD data comparing IPSSO to VBSSO similarly allowed coders to only review data on terminals linked to Evidence.com on-site at LAPD headquarters and for them to be subject to confidentiality requirements that had been in place for the IPSSO field observations. Varying configurations of access will dictate tools that research teams can bring to bear on the video as a data source. For example, data viewed through a terminal accessing the departmental archive is unlikely to allow extracted video files. So coders will have to align coding technology and instrument access with that reality. However, when departments are willing to export video files to researchers, maintaining continual security and confidentiality are of paramount concern. Departments that engage in-house research teams would have the advantage of security and the ability to deploy tools for review that can take advantage of the existing environment. One tradeoff here is that files migrated from the archive system can be used within commercial applications for video analysis, such as Atlas.ti.

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4.4.2 Human Subject Protections and Institutional Review Human subject protection and the ethical handling of data are explicit in the arrangement that the CSI lab has established. Those researchers are generally prohibited from coding video data from BWC within a private dwelling, which is part of their initial review process (D.  Willits, personal communication, March 9, 2021; D. Makin, personal communication, March 9, 2021). The research team can, when the benefits outweigh the costs, establish access to within-dwelling videos, if, for example, the research benefits (e.g. domestic violence research that may aid in helping victims) outweigh the possible costs to those who are on video in terms of exposure of private space for research. This is an important balance, and researchers must be aware that the risk to subjects is one that they have not explicitly agreed to; therefore, the pursuit of answers to mundane  questions should be reviewed with some skepticism when one balances the rights of subjects with the likely utility of research (Nassauer & Legewie, 2022). Similarly, the consequences of research for officers captured on BWC is not a zero risk to the subject, and therefore, researchers must articulate, a priori, why and how videos will advance science, safety, and practice, as well as protections afforded officers. In one IPSSO in Belgium, officers were, for example, explicitly told that illegal behavior observed during research would be reported to superiors. Chillar et al. (2021), in contrast, note that their review of BWC footage in the United States would not be used to identify officer wrongdoing, but only be for the purpose of research. Procedures for maintaining confidentiality, nondisclosure agreements for coders and personnel, and reporting that protects subjects (e.g., avoiding anecdotal presentations of cases from the archive), including officers are required steps in conducting VBSSO research. Further protections and security are necessary for any access that might be permitted off the premises of the police agency. Consideration of the four pillars of human subject research, as a general touchstone, is to be carefully weighed as one judges whether access to footage is justified by the underlying research question (Nassauer & Legewie, 2021,  2022). The principles of beneficence, respect for persons, justice, and respect for law and public interest dictate that researchers carefully balance the interest of subjects (both officers and civilians) and the potential utility of the research endeavor if successfully executed. With respect to those interested in international comparative research, we would note that there could be substantial variation in human subject restrictions that must be overcome. For example, in the European Union, the General Data Protection Regulation (GDPR)1 outlines the privacy legislation and defines how personal data of subjects (including research participants) can be registered, processed, and saved. An important aspect of this regulation is the legal grounds for processing personal  Verordening (EU) 2016/679 van het Europees parlement en de raad van 27 april 2016 betreffende de bescherming van natuurlijke personen in verband met de verwerking van persoonsgegevens en betreffende het vrije verkeer van die gegevens en tot intrekking van richtlijn 95/46/EG. 1

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data. The law stipulates six legal grounds for such processing (Art. 6), one of which is consent of the research participants. Such consent is different from the ethical informed consent, which participants give to indicate that they voluntarily participate in a project and have been sufficiently informed. The GDPR also requires persons whose personal data are processed to be informed of this processing beforehand (e.g., which information is collected, for which purpose, who has access to it, how long these data will be saved). Furthermore, researchers need to register the processing of personal data, usually in a register of the institution they are associated with. Such consent is, however, infeasible with regard to citizens that indirectly participate in SSO-projects, thus raising ethical questions on whether and how such consent needs to be obtained. In IPSSO projects, as noted in Chap. 2, researchers can justify citizens as secondary or indirect participants. The extension of that argument to VBSSO is unclear as other regulations of video and privacy may supersede research interests. For example, citizens who record the police in any way cannot share these videos online, at least not if the police officers are recognizable. In Belgium, citizens can be brought to court for sharing videos of police officers without legal grounds. The Controleorgaan op de politionele informatie, a Belgian police oversight body that focuses on police handling of information and makes recommendations on these aspects, argued that even citizens who film police officers need a legal base for doing so, which is usually that it is in the public interest to make a recording. Merely recording police without any legal grounds is thus prohibited. These legal regulations restrict the use of recordings made by citizens in the course of research projects.

4.5 Code Development, Training, Unit of Analysis, and Issues of Reliability 4.5.1 Code Development and Training The development of a codebook, outlined in Chap. 2, is also an essential procedure in VBSSO. However, it is also true that video can be revisited, reviewed, and recoded in subsequent passes so that a more interactive coding and recoding is possible. Experience in the POPN IPSSO project in the 1990s indicated that field coding revisions, upon encountering novel situations, were not uncommon, but difficult to reconcile with observations that had already been completed. Thus, the willingness to change coding in an IPSSO is constrained, whereas in VBSSO coding, changes can cost time to revisit footage, but will not result in data loss or noncomparability. Put differently, in the context of VBSSO, the creation and elaboration of codes and definitions, training coders on protocols, and being open to generating revisions are all part of the process to collect data. Several ongoing or recently completed projects collecting data using VBSSO have published articles that offer good illustrations of how a variety of coding

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choices can be addressed, the assessment of which may be heavily dependent upon the size of one’s team. Willits and Makin (2018) have established a lab-based coding system with an elaborate three-tiered system of annotation and on-site access to police BWV, which they have outlined as systematic social event modeling (Makin et  al., 2020). Training of coders, drawn from university students, and obtaining human subject approval, as well as certified criminal justice information access, are a foundation point for fielding this research team. The coding approach, regardless of research questions, begins with a process for tagging a variety of event times, and next a review of the tagged events for the duration (and accuracy), and finally coding the information at the end of these video events to develop a sequence of police– citizen actions as data. Embedded in this process are inter-rater reliability tests, validation, and coding verification. The rationale behind this approach to systematic social event modeling and specific applications are illustrated in a variety of articles including an exploration of the effects of gender on police decisions (Nowacki et al., 2022) and civility in police–citizen encounters (Holladay & Makin, 2021). By virtue of what we believe, at this point, to be the largest coding team deployed, the researchers have analyzed thousands of hours of BWV from a variety of departments in their extensive work on VBSSO research projects. Schafer et al. (2022) document a research team with three graduate students that were trained on a codebook, including definitions and examples that captured aspects of police use of force and suspect resistance. In total 220 videos, derived from the Newport News, VA police department’s archive, sampling all uses of force and a selection of 161 arrest incidents in a 24-month period, comprising 180 h of footage, were reviewed for the project. A third team, Sytsma et al. (2021) conducted a research project with the Newark, NJ police department featuring analysis of uses of force captured on BWV.  The project featured one coder on-site at the department and reported approximately 300 h to code 91 use of force events. Data from police department records were used as supplements for measures of gender, ethnicity, and age of officer and suspect. This process of triangulation is likely a useful supplement for any SSO modality that has some access to the local department RMS. Data from the RMS, especially regarding items such as intoxication, can provide some background to facts that are inaccessible to or unreliably captured with VBSSO. Those authors recently revisited these data with much finer coding of 5-s increments to examine patterns of static, gender, for example, and dynamic variables, such as suspect antagonism, and the influence on use of force timing and duration within these events (Piza et al., 2023).

4.5.2 Units of Analysis and Coding Patterns The unit of analysis for VBSSO has, at this writing, been varied. It includes a project coding police–citizen contacts at the encounter level (Dai, 2023) down to a project coding a much smaller number of use of force videos subdivided into slices of videos at 5-s intervals (Piza et al., 2023).

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In practical terms, one’s theory and research question should guide the structure of coding elements, to the extent the data allow for reliable coding. Specifically, researchers interested in procedural justice as delivered by the police to citizens would be justified in coding that as a summary of the encounter between them in its entirety. Procedural justice, in that sense, would be summarized as a computation of what was displayed and coded from the entire transaction between officer-citizen (e.g., Jonathan-Zamir et al., 2015; Mell, 2016). Terrill and Zimmerman (2022) use Terrill’s prior work on sequencing of force patterns as police responses to citizen behaviors. This framework serves to structure their observed unit as the citizen, but to embed the sequences in that police–citizen transaction. In a last, but not only, example, Voigt et al. (2017) coded utterances in a fashion that comported with communication theory and allowed the contours of police and citizen verbal interaction to be traced over the course of a traffic stop.

Unit of Analyses and Coding Choices The FINN-PJ researchers adapted the POPN instruments and their prior work (Worden & McLean, 2017) to develop the VBSSO coding, thus specifying coding down to the citizen level. For example, an encounter between an officer and three citizens would yield coding at the level of each citizen (as well as the overall encounter-level in which they are nested). Their coding of BWV sampled from a metropolitan department yielded coded data on more than 4000 citizens in 2071 encounters with an aim of understanding the level of procedural justice that was delivered to citizens. Specific items for the observation that capture procedural justice were adapted from their own prior work as well as other research teams using IPSSO instruments, including Jonathan-Zamir et al. (2015). Their codebook ultimately included 187 items for each citizen. Further effort was devoted to the development of coding items to capture officer-supervisor contacts at the encounter level, which could be derived from the video reviews. The FLETC-FORCE researchers shared their experience in reviewing videos and started with a similar POPN approach focused on use of force. The research team reviewed videos with the feasibility of capturing the forcesequence levels as a coding unit and determined it was possible to do so. Terrill’s earlier work, using IPSSO, (Terrill & Mastrofski, 2002 for example) drew upon this sequencing of an officer’s coercion level and citizen response. So, in a sense, the project is at the citizen level, but it uses the timecode of BWV (and dash camera footage, which was acquired from a sheriff’s department) to further subdivide the encounter into this sequenced pattern of backand-forth police actions and citizen responses. Both teams noted the advantages to more confidently establishing causal order given the timestamp on the video and the chance to stop, rewind, and recode data.

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4.5.3 Training, Reliability of Codes, and Reliability of Coders Sytsma et al. (2021) report a 5-day retreat on-site with the research team and one coder to establish the coding process, codes, and definitions. After all cases were coded, a test of intra-coder reliability on random selection of 10% of cases yielded reliability tests indicating measurement consistency. The use of SSO and VDA by this team was elaborated upon in an article and chapter outlining methodological issues that arose, how researchers can handle such events and how VBSSO can help improve police accountability (Chillar et al., 2021; Piza & Sytsma, 2022a, b). Schafer et al. (2022) used a sub-sample of video that was group coded for comparison and to increase reliability. The process included blinded paired coding of videos to establish item-by-item reliability. Comparisons resulted in the elimination of several measures and revisions of others, including whether a suspect was intoxicated, which was coded more conservatively subsequent to review. Kroner and Schafer (2022) conducted a study of coder and coding reliabilities on a sample of 99 behavioral health calls from an anonymized agency that implemented BWC. Four graduate students were trained as coders over a 30 h period. The results offer evaluation of BWC footage coding that is mixed. The reliability coding suggests interrater reliability for some of the measures, which included physical and verbal behaviors of officers and citizens, as well as situational characteristics and citizen states, such as emotionality and presence of a weapon, among others, as being adequate to strong. Others had demonstrably poor consistency, including evaluation of audio quality, whether officers decreased distance with the citizen or showed empathy, and whether the citizen was emotionally excited. Terrill and Zimmerman (2022) collected data on the sequential application of force by police using three trained coders plus a research leader. Group-based coding was used to identify problematic items such as DUI encounters with sobriety tests involving multiple commands. A 100% consistency check on all cases with a third coder as “tie-breaker” was conducted to ensure reliability of coding. A total of 530 videos, with 438 used in the final sample of 540 police-suspect encounters, were coded after being obtained from a municipal police department and a sheriff’s office. The project mixed body camera and dash camera footage in the research design. It is clear from the review of this sample of published VBSSO projects that the ability to review and recode data and the ability to observe rare events are primary strengths of BWC.  Further, the timecode associated with video also allows for micro-process examinations along the line of sequences (Terrill & Zimmerman, 2022), short 5-s slices of time (Piza et al., 2023), utterances (Voigt et al., 2017), and the establishment of initiation and duration of use of force (Willits & Makin, 2018; Schafer et al., 2022). Interestingly, the research on micro-processing based on 5-s increments found that 1-s increments of coding would be too small to be reliable; thus, there are likely limits to the affordance that time-code offers researchers conducting VBSSO.

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Training and Reliability in the Field The FINN-PJ researchers conducted a 1-day training on instruments and procedures, with practice coding of video, followed by project data coding. The latter was checked in group debriefings of paired-up videos. The process for coders was to first watch the incident and take notes. Next, they would code the incident, watching the video three or four times. This could take several days for a long encounter. Structured overlap on observations by different coders allowed for coding debriefing to compare codes and resolve differences. Longer videos were particularly problematic, and observer variation and differences in subjectivity and objectivity were noticeable. Subjective assessment was, however, in some cases, unresolvable. Fundamental questions, such as whether a person on the BWV was supposed to be coded a citizen under the coding rules, sometimes arose. Discrepancies were sometimes resolved by a data manager and debriefings could be tense if coders’ interpretation and coding were at odds with one another. A total of 827 encounters were double-coded for this comparative process. One problem that presented itself in the comparison reviews was the ordering of citizens using codes (C1 = first citizen encountered, C2 = second, and so on) sometimes created cross-observer confusion as they were coding different citizens with different numbers in the comparison cases. This required an astute data manager to uncover and properly reconcile as encounters could have as many as a dozen citizens coded. The FLETC-FORCE study started with the impression that 1–2 weeks of training would suffice. Observers started coding and compared notes with each other. This process unearthed the need for more specific directions and the training wound up lasting 6 weeks. Even with the 6  weeks of coding practice the research team decided to double code all the videos and have inconsistencies in coding decided by Terrill to ensure high reliability. This amounted to about 2000 h of work to develop protocols, train, and code 540 police-suspect encounters.

4.5.4 Coder Over-Identification One area, to our knowledge, as yet unexplored, is coder over-identification, or close association with the research subjects. This would have several possible configurations. First, preexisting attitudes regarding the legitimacy of police (or lack thereof) may subtly shape the error pattern of observers. If a project has observers from a similar background (middle class, nonminority, college students), the homogeneity of attitudes may not be detectable in typical inter-coder testing. Second, familiarity with the research subject may condition coders to change definitional interpretations systematically as their time on a project increases. This

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suggests that, for large-scale coding projects, intermittent test and checking on common coding application would be useful to chart both within observer trajectories and between observer variations. Finally, it seems that, with many projects observing hundreds of videos, individuals engaging in VBSSO may come to have particular opinions about officers (e.g., “he’s an asshole” or “she’s a great officer”), and that may influence coding in the n + 1 case after that attitude forms. We posit these effects here for completeness, as they seem like plausible threats to reliable measurement, but we know of no specific data confirming or disconfirming this conjecture. Like the IPSSO projects, this threat is likely best handled by extensive training and a management and monitoring system that tracks the coders’ performance systematically. Given the ease with which common videos can be group coded and compared, this would be a useful approach to reinforce high coding standards and take advantage of the typical VBSSO configuration that involves multiple coders to minimize threats to data reliability.

4.6 A Comparison of VBSSO and IPSSO 4.6.1 Video and Audio Channel Adequacy as a Record of “What Happened?” A final study considered here involves work by McCluskey and Uchida (2023) to directly compare IPSSO and VBSSO involving police–citizen encounters in the Los Angeles Police Department (LAPD). That project assessed video quality and performed comparisons between coding generated by VBSSO and IPSSO of the same incidents and is detailed in this section. Here we summarize key findings regarding the reliability of the BWC record for coding purposes and present new results examining evidentiary elements observed during the same encounters by IPSSO and VBSSO. McCluskey and Uchida (2023) first examined 102 videos to assess the adequacy of the audio and video channels for participants (citizens, other service providers) and recording officers, indicating full or most speeches were captured for 63% of participants and 85% for recording officers. These results indicate that there is a differential reliability for audio capture of officer utterances as compared to citizens. As with other VBSSO researchers who comment on audio quality this project noted that common issues decreasing audibility were background noise and distance from the officer. Further, encounters that took place on the street (e.g., traffic stops) had lower levels of audibility, suggesting interactions of event types and location contributing systematic data loss to the audio record captured by BWC. A second comparison was made by those authors regarding the adequacy of the video channel. Obstructions (28%) were observed in more than a quarter of the videos, and in about 10% those obstructions persisted for more than 25% of the video runtime. Lighting, camera angle, and distance also contributed to what reviewers considered to be degradation of the usefulness of the video as a data

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source. Camera angle was a surprising contributor, obscuring the view in 44% of cases, almost none of which involved uses of force. In contrast, Piza and Sytsma (2022a, b) note that in the use of force cases they sampled, the officer’s camera fell off uniforms 34% of the time, which we would suspect offers even more video channel degradation for coders. As a result of the obstructions, angles, and lighting and other video quality problems, observers reported that they could make a confident description of the characteristics of citizens, such as race/ethnicity, age, and gender, involved in the encounter in only 30% of the videos. Assessing and Reporting Video and Audio Data Adequacy The FLETC-FORCE researchers noted several problems which were evident in the VBSSO. First, with regard to the audio, there were noted problems with wind and traffic sounds limiting voice capture. Additionally, one site featured a number of Spanish-speaking citizens, and no observer was sufficiently proficient in the language to code those data. Finally, with the BWC and the camera angle, when an officer was talking to multiple people it was difficult to determine which citizen was given a command, for example. Interestingly the team noted that the coding of race and ethnicity was related to suboptimal video capture. The coding approach had to settle on a white/non-white dichotomy because the video did not provide enough information to further subdivide the categories reliably. Unless an officer ran the license and reported characteristics, there was little to distinguish White and Hispanic in the BWC record. The FINN-PJ project coded several items explicitly to capture the adequacy of the BWV as source data. Coders, for example, indicated that about 12.5% of the time in a typical encounter audio was unintelligible, and their coders reported that they were unable to visually observe important parts of citizen involvement with the police in 30% of the cases, and in almost 5% of the cases, the citizen was not visible on the video. In our view, coding and reporting such data on cases, and an overall summary of confidence in the coding, is one way to measure and mitigate the missing data problem caused by audio and video channel deficiencies. For example, the routinized reporting of such measures would make sense, and testing models for sensitivity to cases with more or less missing data would assuage concerns about the overall analytical value of VBSSO.

4.6.2 Comparing IPSSO and VBSSO in Terms of Evidentiary Coding Items McCluskey and Uchida (2023) made a direct comparison of 46 police–citizen encounters drawing on data from VBSSO and IPSSO. This yielded results suggesting that police legal and coercive actions, such as making an arrest, brandishing a

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weapon, or handcuffing a citizen, generally had high concordance and reliability across the two observation modalities. Three of four measures of police procedural justice, such as display of neutrality, respect, and participation, showed much lower levels of concordance and reliability. Police disrespect, however, was found to have high reliability. A third domain of variables capturing citizen states and behaviors indicated moderate to strong concordance and reliability across the two SSO modalities. The collection of data from the LAPD-PJ research project using IPSSO and VBSSO is detailed elsewhere (McCluskey et  al., 2019; McCluskey & Uchida, 2023). As illustrated above, the design allows for a comparison of these two modalities for data collection. In this section, we focus on evidentiary coding done by IPSSO observers and that done by VBSSO observers. To be clear, the observers in both settings participated in both kinds of research and were trained on the instruments. Evidentiary calculations derived from IPSSO have been used to generate measures of probable cause in observational research (McCluskey & Reisig, 2017) and evidence strength in predicting arrest (Mastrofski et  al., 1995). Additionally, the promise of BWC as an evidentiary tool (Robertson et al., 2022) is one that motivates a comparison of IPSSO and VBSSO results here. Eight indicators of evidence available to the police on the scene at the encounter were coded and compared in Table 4.1. These include the prevalence of the evidentiary indicator in the VBSSO and IPSSO data collection modes and the concordance across encounters. Finally, the last two columns present Gwet’s Agreement Coefficient (AC), which approximates a measure of observer agreement correcting for chance concordance and the lower bound of Gwet’s AC point estimate within the 95% confidence interval (Gwet, 2014; Klein, 2018). The IPSSO and VBSSO comparison explores the legal and evidentiary conditions observed during the encounter, as presented in Table 4.1. Results indicate that in reference to Landis and Koch’s (1977) criteria for benchmarking agreement categories, there is evidence of reliability across observation modalities. For example, the results indicate almost perfect agreement across modalities for three measures as the lower bound of the confidence interval for Gwet’s AC is compared to the benchmark: whether a citizen in the encounter fit the description of a person who Table 4.1  Legal/evidentiary conditions in police–citizen encounters (N = 46) IPSSO VBSSO Concordance Evidence available to police Police obs. circumstantial ev 5 5 78.3% Observe illegal act 10 8 91.3% Other citizen second hand info 9 10 71.7% Other cit told P obs offense 7 5 78.3% Citizen fit description 4 3 93.5% Cit. partial or full confession 2 1 93.5% Observe physical evidence 1 3 91.3%

Gwet’s AC Lower bound CI 0.73 0.87 0.58 0.72 0.92 0.93 0.91

0.54 0.74 0.33 0.53 0.83 0.85 0.80

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was wanted (AC = 0.92; lower bound 0.83); whether the citizen offered a full or partial confession to the police (AC = 0.91; lower bound 0.85); whether the police observed physical evidence of wronging at the scene (AC  =  0.91; lower bound 0.80). Whether police observed an illegal act showed substantial agreement (AC = 0.87; lower bound 0.74). The other three measures of evidence show moderate levels of agreement in terms of correspondence between IPSSO and VBSSO. Reports from citizens to police either in providing second-hand information or telling police they directly observed an offense were more frequent but also offered discrepancies. This could be accounted for from audio problems which might obscure this in the VBSSO record, and, in contrast, the presence of camera footage from both officers, which could yield statements to the backup officer that would be missed in IPSSO by a single observer following one officer. Overall, the varied convergence and divergence in these indicators is a cause for concern and merits further investigation of strengths and weaknesses of the VBSSO record as compared to the IPSSO derived-data. To be clear, this is a global measure of the police–citizen encounter, which meets IPSSO at its strength, of generating an overall account of an event, and does not leverage the sequential and time-coded nature of VBSSO as part of the test.

4.7 Example of a General Data and Sampling Plan to Address a Research Question 4.7.1 The Context for a Multi-organization Study of De-escalation Using VBSSO For a moment, imagine that the chiefs of police from three major metropolitan police agencies in the United States jointly agree that they would like to learn how their officers behave, with regard to escalation and de-escalation, in encounters with the public. How might we go about sampling BWC to help them gain a within- and between-department understanding of how officers are engaging the public and escalating or de-escalating encounters? In this section, we propose using the data generated by police work in three fictitious agencies (each having calls, crime reports, arrests, use of force reports linkable to a BWC archive) as a source from which to enumerate kinds of police mobilizations for linking to video tags in their BWC archives for a stratified sample of police–citizen encounters across those agencies. The pyramid diagram in Fig. 4.1 ranges from least common at the peak (officer-involved shootings) to most common (routine mobilizations) at the base. These are identifiable strata available from agency record management systems (RMS) allowing for sampling kinds of encounters that police officers have with the public. In the best SSO work using field researchers (e.g., Bayley & Garofolo, 1989; Terrill, 2003; Klinger, 1995 and many others), the use of force captured has, admittedly, been on the lower end of forceful behavior that the police can apply (i.e., verbal). Thus, field research in-person, if replaced by VBSSO, specifically focused

4.7 Example of a General Data and Sampling Plan to Address a Research Question Fig. 4.1  A possible operationalization of police–citizen contact types

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OIS Use of Force Potentially Violent Mobilizations Likely Routine Mobilizations

on sampling the types of encounters in departments as done here, would generate the variety, range, and sampling link to encounter population characteristics that would establish a theoretically informed approach to policy and training for the chiefs. The research by Willits and Makin (2018) and Sytsma et  al. (2021), for example, focuses specifically on the ability to obtain video from the archives of a pseudonymous and Newark, NJ department, respectively, by linking use of force reports to the video archives which does generate useful insights. But establishing a variety of encounters that start with similar conditions, but do not escalate to use of force, would be the motivation for the design proposed here.

4.7.2 Enumerating Police–Citizen Contacts for Sampling Uses of Force Officer-involved shootings (OIS) represent the application of lethal force involving citizens. Each of the cities in this sample has had recent incidents of officer-involved shootings that raised serious questions about the tactical choices leading to this outcome. We will sample the population of OIS from APD, BPD, and CPD, featured at the apex of the police–citizen encounter in Fig. 4.1. Use of force reports, at the second tier, are events captured within special reporting forms in each of the organizations that can be traced back to body-worn video. Enumerating reports for 1 year and sampling from this pool will allow for the generation of the proportion of use of force that is deemed within or outside of policy and necessary to resolve a presenting situation. This will allow researchers to chart the development of those encounters involving the use of force that “escalate” from more innocuous beginnings. We would propose randomly sampling up to 100 uses of force in each site for the previous year. However, given the proliferation of power analysis software and the ability to examine the integrated RMS systems, one could tune the sample to specific parameters balancing cost and sensitivity.

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4.7.3 Enumerating Police–Citizen Contacts for Cases That Have a Likelihood of Force Usage Potentially violent mobilizations (PVMs) link back to the language of Fyfe’s (1988) Metro-Dade project and study of NYPD conducted by Bayley and Garafolo (1989). These represent the kinds of events that are problematic – domestic disputes, call for a person in distress, man with a gun, neighbor trouble, assaults and threats, for example. PVM could be enumerated via 911 call type, crime reports, and arrests indicating the calls above. RMS will then be used to trace events back to extant BWC video to identify cases in this pool that did not yield a use of force but may have examples of verbal escalation and de-escalation or unreported force. We would anticipate sampling a number of  potentially violent mobilizations from each site from which video could be coded. Comparative analysis with this stratum will offer an estimate of how, in terms of tactics and situations, PVMs are handled in a de-escalatory and calming or escalatory  and aggravating manner. Additionally, an estimation of what proportion of PVMs are resolved without force, minimal force, or arrests can be generated in conjunction with other strata above. Specifically, the data would allow a picture of the use of force in the three departments and the quality of police–citizen interactions that characterizes day to day police work.

4.7.4 Enumerating Police–Citizen Contacts for Cases with a Very Low Likelihood of Force Usage The final stratum from which we would develop our example sample is likely routine mobilizations (LRM). These are the most frequently occurring interactions between the police and citizens (the residual non-PVM calls) and represent an important reference category for the other strata. We will similarly enumerate LRM via each site’s 911 call type, crime and activity reports, and arrests indicating minor calls and activities above to identify extant BWC video to identify cases that did not yield a use of force report but may have examples of verbal escalation and de-­ escalation or unreported force. This will offer a sense of how LRMs are handled in a de-escalatory calming or escalatory manner or how they may (or may not) mostly start out amicably and end amicably and the winding pathway toward compliance requests, for example. This will allow for an estimation of what proportion of LRMs are resolved without force, minimal force, and in conjunction with other strata to describe the quality that characterizes a nearly complete range of interactions. We anticipate sampling LRMs from each department’s BWC archive, again tuning sample sizes with some reference to statistical power. This is but one possible approach to sampling. Drawing BWC samples of nominated highly skilled officers in departments A, B, and C could, for example, be another strategy. Coded data from their actions could be compared to their

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respective inexperienced or less-skilled colleagues across the three departments and between the groups. Further, given access to RMS systems and the data therein, it may be feasible to merge VBSSO data with officer surveys or surveys of citizens who were encountered, as has been done in some prior VBSSO research (Worden & McLean, 2017). As the reader can see, the fact that one can use other systems (e.g., 911 calls, arrests, or use of force reports) to access archived data facilitates many approaches to questions that have vexed researchers and police managers alike.

4.7.5 Project Technology The processes used by researchers outlined in this chapter should serve as source material for decisions regarding how to access BWV and develop the codebooks in accordance with theoretical rigor to offer substantial policy recommendations and observations, with sufficient attention to coding reliability to be replicable and have balanced error with cost. Terrill and Zimmerman’s (2022) work on sequential force applications, we would argue, presents one of several such templates to follow. Most recently, Dai (2023) archived a complete set of instruments, including a codebook and observation protocols at the encounter and primary citizen level, which are available publicly at the National Archive of Criminal Justice Data (NACJD). His study is an assessment of procedural justice and thus would offer a useful starting point for those interested in examining that in another department. We also provide a brief appendix with references to key projects, in one place, with brief descriptions of samples. It has been our experience that outreach to researchers results in an eager response and cooperation every time we ask for help in understanding more about VBSSO use by our colleagues. Besides the development of codebooks and coding protocols, however, another aspect of VBSSO lies in the technological approaches to coding and compiling data. Depending on the research questions, simple spreadsheets, dedicated qualitative software, and statistical programs with coding interfaces represent costs and choices that should be influenced by the questions asked. Nassauer and Legewie’s (2022) text on video data analysis (VDA) offers an overview of qualitative software that may be purposed for video review and resources that VDA researchers may draw upon to learn more before investing in these sometimes expensive solutions.

Project Technology The FLETC-FORCE researchers used the program ATLAS.ti, which is able to insert codes into videos. That feature was used to subdivide videos into sequences for coding, and then data for each sequence was entered into a spreadsheet. This was possible because the video files were in an environment that allowed them to be imported into the ATLAS.ti program. However, it was

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clear to the researcher team that the sheer size of video files used in the project presented an obstacle to fully conducting analysis of video in the ATLAS.ti environment, hence the need to code each sequence in a separate spreadsheet program. The FINN-PJ team entered data on the encounter level and on the citizen level while viewing an instance of Evidence.com side by side with a data entry program spreadsheet. There was no opportunity to export video data to a separate program; therefore, videos were coded into the spreadsheet on a separate monitor. The LAPD-PJ project coded items regarding video and audio quality as well as encounter-level variables using a Qualtrics interface, which is akin to the side-by-­side process noted above. Coders reviewed the video on LAPD terminals with access to the video archives and coded the data in a separate form on a laptop with connectivity to the Qualtrics platform.

4.8 Conclusion The growth of police BWC footage in the United States and other countries is undeniable. Its value as a data source is being recognized and used to answer questions, about use of force, for example, which thus far had been typically inaccessible to widespread systematic observation. In a review of the three major IPSSO projects by Reiss (2005/1966), Ostrom et  al. (2006/1977), and POPN (Mastrofski et al., 2007/1996/7), which in total observed police encounters with several thousand suspects, only about 200 uses of physical force were observed. Our academic and policy conjectures surrounding contemporary patterns of police use of force often originate via very large surveys such as the police-public contact survey, via analysis of use of force reports obtained from police departments, or from publicly released data or crowd-sourced data on police shootings. It is apparent, however, that the availability of VBSSO data may soon change that. In this chapter, we set out to offer researchers a foundation from which they could consider launching an inquiry using VBSSO of police BWC footage accessed from department archives. No work of this type can anticipate all of the questions and problems faced in research data collection and management. But this chapter offers three primary cautions regarding familiarity with the agency from which BWC footage is obtained, developing a theoretical framework for questions and maximizing the opportunity to develop reliable measurement. Researchers are best served if readily familiar with the originating agency, and the more familiarity with policies, processes, and data systems, the more likely a project will develop a sampling strategy that can generalize to a level that can assist policy makers and police managers. Specifically, it is important to know what is not captured by the BWV and it is important to know how any sample relates back to the large number of police–civilian encounters in a department.

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Second, the unit of analysis and coding scheme requires a similar tuning to the theory that provokes the research questions at hand. Encounter-level analysis of procedural justice (Dai, 2023), sequential subdivisions of use of force (Terrill & Zimmerman, 2022), and utterance (Voigt et al., 2017) all make sense from a theoretically specified origination point. Each starting point, however, obscures, aggregates, or ignores questions at different levels. White et al.’s (2022) work on Naloxone administration is a powerful description of what the police do in specific cases of overdose, and draws its theoretical focus from the medical and legal implications in those situations. The possible failure to accumulate research findings due to idiosyncratic or noncomparable applications of frameworks to research is a danger for VBSSO. Nonetheless, we can offer no universal theoretical framework other than consultation of the literature to assess the fit of one’s own design in the traditions that have come before and to extend those theories and hypotheses with new possibilities. Concern about measurement is often accompanied with vague appeals to adherence to methods of science and is replete with poorly attributed quotes (mostly to Mark Twain in the United States). We find one from Lord Kelvin instructive: I often say that when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely, in your thoughts, advanced to the stage of science, whatever the matter may be (Thomson, 1889: 73).

This chapter has not focused on any specific measure, but our concerns with validity, reliability, and training seek general improvement to measurement and comparability of this research. Establishing a framework for applying VBSSO practices that hew to collaborative sharing of instrumentation, improved reporting of results and limitations of source data, and recognition of the need for the development of tools to expedite the tagging and coding of video are the first steps in developing replicable and comparable approaches. To the extent that this work grows into an ongoing partnership a long-term research plan would likely yield important practical and theoretically relevant results (Worden & McLean, 2022). Overall, the aim to move the body of twenty-first century police research forward and to accumulate a body of knowledge and methodological procedures must begin with a unifying statement attempted here. We do not, however, doubt that others will follow and further improve on the preliminary recommendations offered here as new tools, theories, and insights are drawn from the growing body of research approaches and findings. Resources Dr. Mengyan Dai has archived a complete set of codebooks and protocols at the National Archive of Criminal Justice Data at the University of Michigan, which serves as a clearinghouse and archival repository for sponsored research projects that are funding by the Department of Justice. The following link allows for access and exploration of the same instrument package which he generously shared with project: https://doi.org/10.6084/m9.figshare.22266217.

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Terrill, W., & Zimmerman, L. (2022). Police use of force escalation and de-escalation: The use of systematic social observation with video footage. Police Quarterly, 25(2), 155–177. https://doi. org/10.1177/10986111211049145 Uchida, C. D., & Anderson, K. (2021). Managing digital evidence in a large agency: The LAPD experience. In C.  D. Uchida et  al. (Eds.), Managing digital evidence from body-worn cameras: Case studies in seven sites. Bureau of Justice Assistance. https://bwctta.com/sites/default/ files/2022-­03/1%20DEM%20Final%20Report%2003%2001%2022_CONTENT_0.pdf Uchida, C., McCluskey, J., Kringen, J., Kringen, A., Kato, S., Melendez, H., & Schmitz, J. (2022). Police accounts of critical incidents: A descriptive and empirical assessment. Journal of Crime and Justice, 1–17. https://doi.org/10.1080/0735648X.2022.2080100 Voigt, R., Camp, N. P., Prabhakaran, V., Hamilton, W. L., Hetey, R. C., Griffiths, C. M., Jurgens, D., Jurafsky, D., & Eberhardt, J. L. (2017). Language from police body camera footage shows racial disparities in officer respect. Proceedings of the National Academy of Sciences of the United States of America, 114(25), 6521–6526. https://doi.org/10.1073/pnas.1702413114 White, M.  D., Watts, S., Orosco, C., Perrone, D., & Malm, A. (2022). Leveraging body-worn camera footage to better understand opioid overdoses and the impact of police-administered naloxone. American Journal of Public Health, 112(9), 1326–1332. https://doi.org/10.2105/ ajph.2022.306918 Willits, D. W., & Makin, D. A. (2018). Show me what happened: Analyzing use of force through analysis of body-worn camera footage. Journal of Research in Crime and Delinquency, 55(1), 51–77. https://doi.org/10.1177/0022427817701257 Worden, R. E., & McLean, S. J. (2016). Supervisory coaching, body worn cameras, and police performance. Proposal submitted to the Laura and John Arnold Foundation. The John F. Finn Institute for Public Safety, Inc. Worden, R. E., & McLean, S. J. (2017). Mirage of police reform: Procedural justice and police legitimacy. University of California Press. Worden, R. E., & McLean, S. J. (2022). Collaborative practitioner-researcher partnerships in policing: Two researchers’ reflections. Policing: A Journal of Policy and Practice, 22, 329–343. Worden, R. E., Reynolds, D. L., & McLean, S. J. (2019). Disparities in procedural justice: Police behavior and citizen judgments. Presentation at the Annual Meeting of the American Society of Criminology.

Chapter 5

Environment-Based Systematic Social Observation and Police Research

5.1  Introduction Understanding crime and police responses to the public involves knowledge of the neighborhood in which it occurs. Neighborhoods, for example, maybe residential, industrial, urban, suburban or rural, wealthy, middle class, or under-resourced. Becoming mindful – aware of the details of the place – impacts what strategies and solutions are appropriate to address the crime problems and our understanding of what police may choose to do or not do (Klinger, 1997). Typically, environment-based systematic social observations (EBSSO) are conducted to identify visual signs of social and physical disorder in public spaces. Social disorder refers to behaviors such as verbal harassment on the street, public intoxication, and/or rowdy groups of teenagers in public spaces. Physical disorder refers to deterioration of landscape, including trash piles, graffiti, abandoned cars, broken fences, bars on windows, peeling paint, overgrown lots, and other signs of physical neglect. Taken together, these signs of disorder serve as signals to potential residents/businesses and daily reminders to current residents/businesses of the level of investment or care of the property by the owners, residents, and local government. This signal or stimulus has theoretical links to crime and possibly to police behavior. Research has established a correlation between high disorder and crime. Wilson and Kelling (1993), in their 1982 article “Broken Windows,” posited that minor disorder is causally linked to serious crime. They theorized that disorders signal to potential offenders that residents are indifferent to what goes on in their neighborhoods. The theory asserts that disorder serves as a signal that residents are unwilling to confront strangers, intervene in crime, or call the police. Armed with this theory, police crackdowns on low-level crimes became the norm as a strategy to thwart rising crime in the 1990s. New York City Police led this effort, undertaking aggressive police tactics to control public incivilities, often to the detriment of upholding civil rights (Sampson & Raudenbush, 1999). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. McCluskey et al., Systematic Social Observation of the Police in the 21st Century, SpringerBriefs in Criminology, https://doi.org/10.1007/978-3-031-31482-7_5

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Sampson and Raudenbush (1999) debunked the “broken windows” theory, demonstrating that observed disorder did not match the theoretical expectation set up by its main thesis. However, Sampson and Raudenbush did establish that disorder is associated with crime in a complex and cascading fashion. They found that disorder may lead to negative changes in a neighborhood in terms of residents moving and businesses reducing investments, leading to the weakening of neighborhood viability. Studies of police efforts to address disorder and crime (e.g., Braga et al., 2015) indicate that police deployments vary with social and physical disorder, especially to the extent that organizations practice “broken windows” policing. Thus, at that level, police behavior is affected by disorder. There is not, however, a direct link between police behavior in everyday police–citizen encounters and disorder, but findings from SSOs are suggestive. Higher levels of force used against suspects, for example, were found in disadvantaged neighborhoods in Terrill and Reisig’s (2003) work from the Project on Policing Neighborhoods (POPN). Mastrofski et al. (2002) found that neighborhood disadvantage also impacts whether police behave in a disrespectful manner toward suspects. This is congruent with Smith’s (1986) findings from the earlier Police Services Study, which assessed a variety of police behaviors in police–citizen encounters and found them to vary across neighborhoods. In sum, place matters, and the study of place features which are potential stimuli, such as localized disorder, would move this research to a micro-level and perhaps new hypotheses about how the police behave within disadvantaged neighborhoods will emerge. The authors are leaders in developing this methodology, having honed their work over several decades of EBSSO research. The discussion here draws on multiple research efforts undertaken to study issues such as collective efficacy, problem-­ solving policing, school-based problem-solving, place-based “hotspot” policing, and community-based violence reduction efforts. These studies have been supported with local, federal and private funding. Each successive project has led to iterative refinement and development of the methodology. The authors based their methodological approach on the landmark neighborhood work of Sampson and Raudenbush as part of the Project on Human Development in Chicago Neighborhoods (PHDCN). Though other studies have employed EBSSO methodology (see Hoeben et al., 2018) or sister methodologies, such as ethnographic or crime-based observations, few studies explain in detail the approach. Several others rely on Google Street View, rather than in-person field data collection (Odgers et al., 2012). As a result, this chapter relies primarily on the experience of the authors in a variety of projects and focuses on in-person observation techniques and procedures. EBSSOs are an effective strategy for understanding and measuring variation in neighborhood viability and probing smaller units of analysis than the police sector or neighborhood. These strategies open up new ways to think about the size of neighborhoods and how individuals, including the police, function at the micro-­ levels of communities. This chapter explores the purpose of EBSSO, explains the coding instruments, details the steps for preparing for and conducting neighborhood SSO, reviews the

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strategies for in-person and vehicle-based SSO, and explains how to capture, process, and explore EBSSO data. We dive into the details of the process to demonstrate why EBSSO is a methodology that needs to have a more widespread adoption in police research both as a mechanism for understanding the distribution of crime and also as a possible area for theoretical elaboration on why and how policing may vary in geographic space. Where feasible, we offer experiences from the field that the authors have accrued in several decades of EBSSO research.

5.2 Neighborhood Context, Definition, and Units of Analysis The idea of community is critical to assessing crime. Although police are the government agents responsible for crime control, the vast majority of it results from the everyday activities of citizens acting in their communities or neighborhoods (Uchida et al., 2013). An extensive body of research illustrates the importance of location in the understanding of crime (see for example, Brantingham & Brantingham, 1991; Skogan, 1989; Uchida & Swatt, 2013; Wooditch & Weisburd, 2016). People often seek neighborhoods where culture is shared, social interaction occurs, governmental resources are allocated, and a sense of community is oftentimes seeded. Neighborhoods and the social structures contained therein can have some capacity to regulate human behavior through shared expectations that not only set boundaries of acceptable behavior but also create cultural norms about what actions should be taken when standards are violated (Bursik Jr & Grasmick, 1993). The context of social interactions between neighborhood residents is influenced in part by the length of residence and similar culture and/or ethnicity and holds the potential to create a strong sense of social cohesion and common interest (Sampson, 2006; Sampson & Raudenbush, 1999).

5.2.1 Neighborhood Definitions Definitions of the “neighborhood” have been the focus of much discussion, but researchers typically revert to definitions established by government entities. Neighborhoods as defined by government agencies are often quite large and are typically demarcated by natural or manmade breaks such as rivers or highways. Often at this spatial level, the “neighborhood” is heterogeneous with much internal variation. With EBSSO, researchers seek a more refined and smaller unit of analysis than the neighborhood. These sub-units, or micro-places, can range from blocks or street segments to intersections or addresses. Within neighborhoods, resources such as the neighborhood grocery store, churches, parks, and community centers provide physical locations for residents to interact, share perspectives and build common values. Ultimately, these social ties are the glue that helps bind neighborhood residents together (Solomon, 2019; Uchida et al., 2015).

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Some businesses and types of locations are hypothesized to serve the opposite function and perhaps attract individuals with lower community stakes or who become impaired in the case of bars. Further, such locations may contribute reinforcing stimuli for negative situations, perhaps through a sense that the location is in a vacuum of community-level social control if it has obvious signs of physical and social disorder present (Eck et  al., 2000; Levine, 2004, 2010; Uchida & Swatt, 2013). When using EBSSO to study a social phenomenon, we should be guided by these underlying concepts about neighborhoods in order to develop the appropriate analysis. If we choose too large and/or dissimilar of an area, we run the risk of generating a distorted image of how the neighborhood is functioning. We lose the fine details of the place and thus may lose sight of the key ingredients that distinguish their outcomes (Solomon, 2019; Weisburd et al., 2009).

5.2.2 Units of Analysis and Identification of Areas to Study Defining the areas of study is important when using EBSSO to guide research in the study of crime and social issues of the neighborhood or place. Administrative boundaries that define a neighborhood or place serve as a starting point. These boundaries may be as large or small as the study requires and are dependent on the research questions being posed. If the study seeks to follow the triangulation approach of Sampson and Raudenbush where EBSSO data are integrated with survey data and records data, we recommend starting with census and crime data to aid in defining the target area(s). Census data can be used to identify neighborhood clusters via census tracts with similar racial and ethnic mix and similar socioeconomic characteristics. The primary requirement of the selection of the area is to create neighborhood clusters or similar areas and contrast them with areas that are experiencing a different outcome or social phenomena. In sum, the size of the area can vary based on the similarities and differences in the routine activities or attitudes of the people operating in the space. This variation is what emerges from the coding and analysis efforts. EBSSO allows us to provide a fine-grained image of how the social phenomena are functioning within the target area.

Selecting Units of Analysis To focus on crime problems, police data such as calls for service or crime incidents can be used to create hotspots. For example, in Los Angeles, we used crime incident data to map violent crime hotspots in and around MacArthur Park (Youth Policy Institute, 2019). In this instance, we used crime incidents over a 3-year period. Within these hotspots of crime, we used kernel density and kriging methods to identify two to three persistent

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micro-hotspots of crime as well as two to three similar areas within the overall hotspot area that were not experiencing crime at the same level of intensity. The area in and around MacArthur Park was approximately one and a half square miles. This size area provided an adequate number of street segments or face-blocks to create useful EBSSO data. These were the units of analysis around the park. In addition, we also conducted EBSSO within the park itself. We created a grid, dividing the park into six distinct areas, and compared and contrasted the areas based on physical attributes within the park and the social uses of it as well. For example, we considered the distinctions between the toddler play areas as opposed to the soccer field. The six areas were the units of analysis within the park.

5.3 Theory and Purpose of EBSSO When people commute to work, go to the store or school using the same routes on a daily basis, most are oblivious to any activities outside of that normal routine. These areas are known as activity spaces and people operate within them almost on autopilot. That state of being is only slightly heightened when we enter unknown territory, but for the most part, we remain unaware of the details, for example, seeing that a sidewalk exists but not mentally noting if it is in good condition or what level of trash is present. Instead, we merely become aware of a general sense of our environment as it relates to our home activity space. With EBSSO, this automatic thought process is disrupted. The observer is forced to become hyper-aware of their surroundings, literally counting the number of light poles, litter, or graffiti, for example. To conduct EBSSOs, we rely on predefined coding instruments to systematically capture these details in the form of counts of items per unit observed. These details can then be compiled, analyzed, and often integrated with other data.

5.3.1 Theory of EBSSO Capturing the sights, sounds, smells, and feel of the streets is essential to understanding the social phenomena of neighborhood functioning. The EBSSO approach in neighborhoods builds on the research work of the early Chicago school of urban sociology (e.g., Burgess, 1925/2011; Whyte, 1943). Albert J. Reiss, Jr. (1971) established systematic social observation as the measurement strategy as discussed in previous chapters.

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Sampson and Raudenbush (1999) expanded the Reiss SSO strategy in a way few can replicate, due to the required financial investment. They completed their seminal work on EBSSO as part of the Project on Human Development in Chicago Neighborhoods.1 They took on the methodological uncertainty, asserting a strategy for properly conducting such observations and how to properly assess the measurement properties at the neighborhood level (Sampson & Raudenbush, 1999, p. 606). They demonstrated how to integrate observational, survey, and record-based data at the neighborhood level. In their extensive study, Sampson and Raudenbush examined all 865 census tracts in Chicago, allotting them into 343 “neighborhood clusters” based on race/ ethnic mix and three levels of socioeconomic status (SES). Next, they selected 196 tracts through a stratified probability sample to maximize variation of the race/ethnic mix and SES. During a 5-month period, observers drove a sport utility vehicle (SUV) at a rate of five miles per hour down every street in 196 of the Chicago census tracts. In all, they observed and videotaped 23,816 face-blocks focusing mainly on land use, traffic, the physical condition of building, and evidence of physical disorder. Of those face-blocks, 15,141 were sampled for videotape coding and 126 variables were coded, including detailed information on physical conditions, housing characteristics, businesses, and social interactions (Sampson & Raudenbush, 1999, pp.  616–617). This seminal work provided a theoretical framework on the sources and consequences of public disorder that upended views on broken windows and crime. For our purposes, this work opened the door to opportunity to examine neighborhoods at the micro-level. Because Sampson and Raudenbush validated the EBSSO approach and instrument bases at the broad-based level, we are now able to adjust the approach and reliably use it to study, compare, assess, and evaluate social phenomena within much smaller neighborhood areas.

5.3.2 Measuring Physical and Social Disorder We conduct EBSSO because we have learned that surveys and official crime data are inadequate descriptions of the environment. Data by zip code, census block, or other administrative reporting units, do not provide us with the depth of information to understand the “living” context of the neighborhoods. Rather, data at these levels gloss over the similarities and differences located within the micro-level of places.

 This project, funded by the John D. and Catherine T. MacArthur Foundation, the National Institute of Justice, the National Institute of Mental Health, the US Department of Education, the Administration for Children, Youth and Families, the Harris Foundation, and the Turner Foundation, is a major interdisciplinary study aimed at deepening society’s understanding of the causes and pathways of juvenile delinquency, adult crime, substance abuse, and violence. Over $55 million dollars was invested during the development years. SSO was a major component of the research methodology (NACJD, 2023). 1

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From zip code data, we often cannot tell if a neighborhood is primarily residential or business oriented. While the more geographically specific census data can provide insights into the demographics and make up a neighborhood, it fails to tell us distinctions between how residents live. Do they live in single-family homes or multi-unit structures? Are the structures new or old? Is the neighborhood in a period of transition? The day-to-day state of a neighborhood is poorly captured in official measures. For example, one has little sense of how these measures map onto these questions: • • • • • • • • • •

Do the residents/businesses/government keep their property in good condition? Are the landscapes well-manicured? Do the homes or businesses show the paint peeling? Is there graffiti present? Are security features, such as bars on the windows, present? Is there trash in the street or on the sidewalk? What kinds of trash is it? Is it broken beer bottles, cups, or drug, or sex paraphernalia? Are there vacant overgrown lots? Are the public spaces well maintained? For example, are the parks clean? Is the play equipment in safe working order? Is street signage present and readable? Is the lighting at night appropriate to ensure safety without disturbing the resident and the environment?

These questions are focused on the physical environment that is observable. The questions above are generally assessable as static on any particular day but could change dynamically over time as neighborhoods are “cleaned up” or fall into decay (Skogan, 1990). A second set of observables for EBSSO is how people interact and use their environment. This is addressed through questions such as these: What are people doing in the neighborhood? Are children playing in the parks? Or are strangers loitering? Are people hanging around and drinking illegally in inappropriate places? Are teenagers hanging out in groups and bothering people? Do the bike riders appear to be exercising, commuting, or casing the neighborhoods? The answers to these questions roll up into a picture of the physical and social state of the neighborhood, which links directly to collective efficacy (Uchida et al., 2015). It provides the observer with a sense of how invested and attached the residents and businesses are to their community. Further, it reflects the level of public investment and care of space of the local governments. EBSSO allows us to build a dataset that can demonstrate the local variation in the neighborhoods at a level not captured in other records. Once gathered, we are able to connect specific measurements, for example, of social and physical disorder in a micro-place, to other key information, allowing researchers to contextualize social functioning.

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Theory and Measurement in Action In a study of neighborhoods in Miami-Dade County, JSS researchers (Uchida et al., 2015) were interested specifically in collective efficacy. This is most evident in the way the public uses spaces. EBSSO combined with community surveys and crime data assisted in measuring collective efficacy. The physical attributes and social disorder within places help to explain why people living in these areas may not talk with or interact with their neighbors. It literally shows the barriers to social cohesion and trust among neighbors that are necessary for collective efficacy to take effect. To measure this through EBSSO, researchers focused on items such as the number of houses with security bars on their windows, the lighting of the face-block at night (were street lamps functioning?), the number of empty lots or boarded up houses, the amount of graffiti on a face-block, the number of houses with unmowed lawns, the amount of trash on the sidewalks, and the number of non-functioning vehicles on property or on the street. These physical signs of disorder are consistent with collective efficacy, as they are indicators of how much the neighborhood is invested in its surroundings and how much care is taken with property. Signs of social (dis)order are also consistent with collective efficacy as they show whether people are chatting with each other, walking their dogs, or playing in the park or whether there are signs of drug trafficking or public consumption of alcohol.

5.4 Research Approach 5.4.1 Development and Testing Codebooks for EBSSO What makes EBSSO distinct from ethnographic studies is the use of systematic coding instruments. The coding instrument captures measurable indicators of physical and social order and disorder. These indicators are derived from prior research on social disorder and routine activities theory. The instruments’ elements sensitize the observer to the details of the area, forcing an intensive examination to capture the information. This must be balanced with the time required to code the information. Observers may also be instructed to add notes at the end of the instrument to further describe important aspects that were witnessed. For example, in MacArthur Park in Los Angeles, observers explained why they felt “unsafe” in an area that was unlit after 7 pm. The elements of the physical disorder instrument require using different senses – seeing, smelling, and hearing. It includes counting, but being aware of the environment

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as well. That is, during the evening hours in a high-crime neighborhood, walking may be ill-advised. Elements include: –– Assessment of the amount of litter and trash in the private and public areas –– Assessment of the housing stock, focusing in particular on vacant and abandoned houses –– Count of the streetlights and private house lights Count of how many streetlights are working at night Indicators of the quality of light, i.e., perceived lumens –– Assessment of the neighborhood parks in terms of size, quality of equipment, and usage –– Level of repair/disrepair and cleanliness of the public streets and sidewalks, overall housing stock, residential landscaping, commercial establishments, street signage, and public space –– Count of graffiti by type, if can be determined –– Count of abandoned vehicles and vehicles in disrepair –– Count of bus stops –– Counts of the overall “traffic” density, specifying by motor vehicles, bicycles, foot or pedestrian, and nonstreet legal vehicles –– Indicator of the presence of “commercial establishments,” including an indication of the type of establishment –– Assessment of the “age” and state of repair of motor vehicles parked on the street or on private property, i.e., driveways –– Signs of other noted indicators, including presence of unattended animals, front fences, residences or businesses with “bars” on windows, loud music, noxious/ unpleasant or offensive odors, construction noise or obstructions, dogs barking or motorcycles or other loud moving noise, loud music, and police presence or driving through the segment –– An indication of how “safe” the observer felt on the street segment and a brief explanation of why the observer felt that way Social indicators include a variety of elements that require counting people and their activities within the face-block. In areas that are not primarily residential but business-related, this becomes difficult on high-trafficked, pedestrian streets. In the area across from MacArthur Park, for example, there was a subway stop that was very busy during rush hour, but less so at 2 pm. Having two people using the social indicator instrument helps in determining counts of people. Elements of the social indicator instrument include: –– Counts of the number of individuals present on the street segments –– Breakdown of the individuals by age and race categories –– Assessment of how many distinct “groups” are noted. Within each group, the coder provides details on: Age Suspected alcohol use

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Loud or boisterous behaviors Location Activity, including dominoes, cards Playing sports –– Observations of the types of activities of all individuals, including: Landscaping, home repair, car repair Family time walking, playing, exercising Indicators of drug use (smell), consumption of alcohol, etc. Maintenance of public spaces Indication of conflicts/arguments or police activity The data are collected primarily as counts or binary yes/no indicators with the option for comments and notes. Each survey includes basic data on the survey taker, the date, time of day, day of week, and street segment identification. While these instruments include the basic elements of EBSSO, they can be adjusted and tweaked to obtain the information needed to answer the research questions under consideration. For example, with MacArthur Park, the instrument was adjusted to capture counts of trash can placements, notations about the state of park benches, and details about the types of sports being played. The primary consideration regarding the instrument is investment of time to align the instrument with the research questions and to ensure that a systematic tool is developed prior to the coding efforts to ensure consistency of data collection. We recommend that pilot tests be conducted to ensure that the instrument is collecting the data needed for the study and to allow for time for adjustments and training of the staff on the use of the instrument.

5.4.2 Institutional Review Board and Confidentiality Researchers should ensure that procedures for maintaining confidentiality, non-­ disclosure agreements for coders and personnel, and reporting that protects subjects are in place. These are usually required by Institutional Review Boards (IRB). While EBSSO is less intrusive than SSO with police, EBSSO observers should be made aware that their presence is obtrusive, that they are “strangers” in areas and that they should be respectful of persons and property. For example, if photos or videos are taken during the observation, they should not include faces or addresses to maintain the privacy of the individuals and the households.

5.5 Preparing for Fieldwork In this section, we discuss steps for preparing for the fieldwork of EBSSO.

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5.5.1 Piloting Conducting a pilot effort is important to the success of EBSSO. Because conducting EBSSO is labor-intensive, it is important to know the landscape before launching the full-scale effort. We recommend the project leaders go to the proposed research location and complete an initial drive-through to gather a general perception of the area. This endeavor helps with the process of defining the target area. Often, during these drive-throughs, we have found that critical natural or man-made breaks exist, such as train tracks, shopping centers, or apartment complexes. These breaks often delineate significant differences in land-use patterns. Being able to identify these breaks in the flow of the neighborhoods and adjust the boundaries of the target areas is important. If these included areas are too varied, summaries of the coding can obscure or misrepresent key components. For example, in one instance, the housing plot size varied greatly from one section to the other section. In one section, the houses were very close together with small or nonexistent yards, while within the same “administrative” neighborhood, the houses were situated on half-acre lots. A street with retail shops ran through the middle of the neighborhood and served to split the land tracts and neighborhoods. Without the pilot, the coding would have obscured the distinction and likely misrepresented the nature of the community. A second challenge with EBSSO is access to communities. The pilot process can identify locations where access may be limited due to gated communities, park hours, or other obstructing factors. Knowing these limitations prior to establishing the sampling frame avoids having to restart the process if a neighborhood cannot be accessed. Also, outreach efforts can be attempted to gain access if possible via local government connections or engagement of the community associations.

5.5.2 Choosing the Unit of Analysis A core challenge with EBSSO is choosing a unit of analysis and maintaining the consistent measurement of those underlying units. For example, following the strategy established by Sampson and Raudenbush, a focus of the coding instrument could be on the face-block. A face-block is the block segment on one side of a street. One challenging aspect with the EBSSO measurement is the variability in the length of the face-blocks. In some places, the blocks are fairly standard and consistent. In other neighborhoods, the blocks vary greatly in size and shape. For example, in one community, homes were present on each of the four sides of the blocks; however, while the north-south direction only had two to three homes, the east–west directions had 10–12 homes. An appreciation for this variability is important when selecting the sample and establishing how the coding process will work. Depending on the research questions, it may be prudent to only do EBSSO on the east–west streets as opposed to all street segments. The pilot drive-through will help bring these variations and solutions to the surface.

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5.5.3 Coding Norms and Validation During the piloting period, the instruments can be tested for applicability and any specific missing elements that may need to be captured. If two or more persons can participate in the pilot test, the pilot can serve as an opportunity to establish coding norms and validation requirements important for training. For example, the coding instrument asks about the level of trash on the streets as no litter, low level, moderate level, and high level. It is important that coding norms are established to clarify expectations about the distinction between these types of levels, especially if comparing results across varied neighborhoods.

5.5.4 Launching After the pilot efforts are completed, final sampling, the procedure planning, and training efforts can be launched. The procedure planning involves determining how, when and by whom the SSOs will be completed. The sampling involves selecting the specific street segments to be coded and the frequency of the coding. The training involves explaining the purpose, approach, procedures, validation, and assignments for the SSO efforts.

5.5.5 Sampling This section on sampling focuses on street segments as a unit. There are other units that might comprise sampling (properties, addresses, and so on), but here we offer the simplification of discussion and direct the reader to consider each sampling approach as applied to their own theoretical and research frame. Besides choosing an areal unit for sampling, researchers must also consider the timing, patterning, and repeated observations that also constitute a sampling choice. There are at least three strategies for selecting the street segments to conduct EBSSO: (1) a random sample can be selected from the list of all street segments in the area; (2) a random sample can be selected from the list of segments where community surveys have or will be conducted, allowing for a link between the survey responder and the observer perceptions, if triangulation of the data is planned; or (3) all street segments can be completed, depending on the size of the area, project budget, and research questions. The easiest way to complete this street segment selection task is to use a mapping program to select all street segments in the target areas. Once the street segments are extracted, a random sample can be selected, or all the streets can be included. The next step involves developing a plan for frequency and schedule of times to conduct the SSO. A more thorough consideration and discussion of this process can be found in Solomon’s (2019) work.

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Because the social activity and physical demeanor of the neighborhoods change over time, conducting repeat EBSSO of all or a sample of the street segments/face-­ blocks is recommended. Explicitly building a time/place sample plan is an important consideration. For example, early morning in neighborhoods may involve trash pickup, school bus pickups, and early work arrivals. Mid-day/afternoons often include children playing, higher levels of traffic, and the start of loitering activities. Afternoons continue to be characterized by higher traffic levels as well as family and community activities such as exercising and sporting events. During the transition to the evening hours, lighting becomes an important aspect as well as measures of the level of variation in social activities on the streets. In our experience, it is best to complete at least two SSOs per face-block to capture the environment during the daytime hours and late afternoon or evening hours. Randomization can be used to select which street segments/face-blocks are visited during which time periods. How the face-blocks are visited is the next key consideration. EBSSO can be conducted by an individual observer, in teams, or with neighborhood experts and/or with law enforcement. Further, EBSSO can be completed by walking or driving. In this next section, we discuss the pros and cons of these methods.

5.6 Hiring, Training, and Assessing Observers 5.6.1 Hiring Observers The process of hiring observers involves identifying individuals with a natural curiosity and a disposition toward attention to detail. Observers must also be somewhat courageous and street-smart. Judgment is of the utmost importance, as observers have to know how to engage, de-escalate, and respond to situations that may arise unexpectedly in the field. In many cases, hiring individuals with experience living in the designated communities or nearby communities is advantageous to the project. These individuals will have knowledge of the areas and how to “fit in” when conducting the observations. This is particularly beneficial if only one observer will be completing the data collection efforts in a particular area. Other quality candidates include experienced professionals such as former community leaders, former law enforcement professional and/or experienced social work professionals who are used to going into diverse neighborhoods. If the project uses young and/or inexperienced students, it is best to add an experienced professional and place them into a group of three. These teams will improve the data collection effort and overall safety.

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5.6.2 Training The EBSSO process requires extensive and detailed training to ensure validity, reliability, and replicability. Training involves a comprehensive review of the why, what, how, and when of the process. For observers to be effective, they should understand why they are conducting the EBSSOs and the anticipated end products and outcomes. The observers need to know the research questions and how the EBSSOs are being used to answer those questions. The coding instrument, though designed for ease of use, has several nuances that should be addressed in training. Details about definitions, ways to code, and ways to count are critical. For example, observers need to know how to identify which face-block they should observe. They should be trained on the expectations for what is low-level trash versus moderate or high levels of trash. Observers will learn the details of counting streetlights, vacant lots, and vacant and/or abandoned houses. Issues arise, such as distinguishing between lights in parking lot versus streetlights – how are those lights counted? How do we distinguish between vacant as opposed to abandoned houses? If loud music is coming from across the street, is it counted or not? Clarification on these nuances is essential to produce consistent results. Training should also cover the lists of the assigned street segments, review safety and notification protocols, data collection procedures and times, discuss note-taking and photography boundaries, and address how to respond to inquiries from the community or law enforcement. Role-playing may be appropriate to cover some of these topics. Field training should also occur with the supervisors available to address questions on the first one to three street segments. Supervisors should be available to address questions of nuance throughout the process, to provide additional training as needed for clarification purposes, and be prepared to review, revise, and clarify directions for coding.

5.6.3 Advising the Authorities Regardless of what decisions are made about conducting EBSSO, it is best to advise the authorities of your efforts prior to conducting them. In most neighborhoods, residents, neighborhood managers, or officials will notice the presence of observers and become concerned about coding and photographing of the neighborhood. Often these individuals will approach the observers and inquire about what is occurring. Occasionally, calls to the police are made. If prior notifications are made, you can provide the inquiring party and/or police with a telephone number of an official with the local government to validate what you are doing. Without that notification option, the coding process can be interrupted, as explanations are required to conduct the activity. In some neighborhoods, our project teams have made presentations to the city councils and notified the police to avoid potential concerns by residents.

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5.7 Strategies for Observer Deployment and Technology 5.7.1 Unaccompanied Project Observers The best way to obtain a sense of the sights, sounds, smells, and feel of a neighborhood is to take slow walks up and down the face-blocks. With objective observer(s) alone, bias associated with prior knowledge about the street is reduced, particularly if the observer is new to the area. With this process, we recommend that the first pass of the face-block focuses on gaining a general sense of the block and making mental notes of the physical and social dimensions of the street. On the walk back, the observer can use the coding instrument to capture the specific items. If two observers are completing the walk-through, one observer can complete the form while the other observer counts and notes the items. The second observer can also take pictures and/or videos to help document the process for use in later debriefings. In addition, the observer doing the coding can denote the photo numbers on the coding sheet for easier reconciliations later. If the area is known as a high crime area, we strongly suggest a minimum of two and not more than four observers. This allows for one of the observers to concentrate on the coding instrument while the others stay situationally aware. More than four observers, however, will raise neighborhood concerns and may alter the effectiveness of capturing the natural state of the area. If only one observer is involved in areas of concern, we recommend that the observer take mental or very brief notes and complete the instrument in the car or at a secure location to remain situationally aware. Further, we recommend that the observers dress casually and wear comfortable shoes.

5.7.2 Community Leader Involvement An alternative configuration for conducting EBSSO is to involve a recognized community leader, such as a pastor or neighborhood organizer. The benefits of this strategy are twofold. First, the leader can help point out key locations and provide historical context about the neighborhood that can be noted in the narratives. For example, in one area in Miami, the community leader provided contextual information about where homicides had occurred and that the side street was known as “execution alley.” She explained that the neighborhood had vocalized the need for concrete barriers and extra lighting that were present to limit the access points and reduce the opportunity for violence. The community leader can also help ensure the safety of the observers as well as secure social engagement, which will be discussed later. Because the community leader is known in the area, residents are likely to be more relaxed about the coding process.

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5.7.3 Law Enforcement Involvement A third alternative is for the observers to complete the process with a police officer. While this alternative provides the highest level of safety for the observers, it poses potential biases. On the positive side, the officer often can be much like the community leader, providing helpful background and context for the areas. In some cases, the officer also becomes more aware of the neighborhood as they complete the process with the observers. On the negative side, social interactions that are signs of disorder and already rare by nature are likely to be suppressed or extinguished by an officer’s presence. Finally, we have found that law enforcement often prevents coding in some areas due to their concerns about the exposure to potential violence. There is also the option of having police complete the EBSSO themselves. We have found this strategy to be effective when engaging in problem-solving projects. As noted early, we often go about our daily lives and work without noticing the details in our environment. When officers are asked to police an area, they typically feel quite familiar with the area, not recognizing that they are overlooking these details. For example, one project yielded the following realization from a school resource officer: I know my neighborhoods. This is a stupid exercise – walking around, counting street signs, lights, and trash. I mean, really, what a waste of time. 2 weeks later… We gotta get to work. I never knew what those babies were walking through to get to school. That vacant lot is littered with everything unimaginable. The trash, broken glass bottles, syringes… invisible to us unless we get out of our cars. (School Resource Officer upon completing SSO exercise)

In projects where officers are asked to complete the coding instrument, the officers frequently report surprise and a significantly enhanced understanding of their assigned neighborhoods. Many report that they are “seeing, really seeing, the neighborhood for the first time.” These efforts help them to seek and form key collaborations to address many quality of life and more serious crime problems. For example, in Los Angeles, in Lemon Grove Park, the officers became aware of a completely new drug dealing location that was preventing residents from using the park. Because the area was in a tunnel under a road across the park, they had previously been unaware of ongoing activities that affected the access and exit from the facility.

5.7.4 Driving EBSSO can also be completed by driving slowly through the street segments. Two people are needed, for safety reasons. One can drive and share insights, while the other codes the street segments. While driving is faster and more efficient, it does, in our experience, degrade the details in the coding process. In particular, the

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observers can count key items and provide an overall sense of the areas, but details about trash and litter, levels of disrepair and cleanliness, and graffiti are more difficult to capture while driving. Using a hybrid approach of walking during the day and driving in the late afternoon and evening is an effective strategy. It is effective because the evening observations can focus more on examining the lighting and social interactions.

5.7.5 Collecting Data Fieldwork should begin immediately after training and notifications of the community. Observers should complete the physical and social observation forms for each face-block. Care should be taken to ensure that the forms are clearly labeled, providing the name of the observer, the date, time of day, day of week, and specific street segment, either by address or assigned identification number. Care should also be taken to ensure that the notations are readable. We mentioned this because when coding in the field, using clipboards, while walking and trying to be discrete and safe, penmanship declines for most observers. It is important that observers take time between street segments to review their forms, clarify responses, and finalize missing data. Too often this quick review step is skipped, causing problems later with data entry.

5.7.6 Taking Additional Notes During the time in the field, unique moments, sights, and sounds occur and these moments should be denoted to help with the qualitative descriptions of the face-­ block as well as to help interpret the quantitative results. For instance, perhaps during the coding process, a storm blows in and the streets become instantly flooded, pushing trash through the streets. From a social indicator perspective, perhaps police activity arises such that a perimeter is established, limiting access to the street segment. Capturing these natural phenomena and social circumstances may be important for later descriptions about the level of trash found in the streets or the type of groups that congregate in the streets. It is important the observers capture the events by taking detailed notes in the field to explain the circumstances that may have led to anomalies in the data and/or that show the unique events that are impacting the community. While these events are not replicable per se, they shed light on important circumstances and the dynamics of place.

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5.7.7 Taking Pictures and Videos Pictures and videos are powerful products of the EBSSO process. They aid in recalling the details of the street segment, documenting the results for potential replication of the coding or study, and explaining the findings of the effort. Taking photographs and/or videos that can be effectively integrated into the workflow during the coding process requires planning and practice. During the EBSSO process, hundreds, if not thousands, of photographs and videos can be captured. Sorting through them after the fact can be daunting if a plan is not in place for how to catalog and track them. As noted earlier, we recommend two strategies for keeping track of the digital images. First, on the coding sheet, note the image numbers at the beginning and end of the street at a minimum and note if special photos are taken to further document specific issues, such as park equipment in need of repair. An additional strategy involves taking pictures of the street signs at the beginning of a street segment and the end of it. This strategy is particularly helpful when taking photographs of detailed issues, such as broken sidewalks. As a rule, we recommend taking broader-angle shots of an entire street segment. We also recommend avoiding taking photographs of individuals or groups observed during the fieldwork, unless permission is requested and granted. Typically, photographs are very useful in reporting to translate a feel for the type of housing, the types of trash or vacant lots, and the incidents of disorder and graffiti in public parks. They are particularly helpful in presentations about the SSO research efforts. Video poses a greater challenge because typically it must be reviewed and coded to be included in the systematic social observation process. As Sampson and Raudenbush (1999) found, this coding process is extremely time-consuming and labor intensive. We also note that in order for the video to be useful, the videographer should be skilled to provide high-quality and useful videos. Narrated videos can be extremely useful, however, when only one coder is present or the fieldwork must be completed quickly. After the fieldwork is complete these videos can be used to fill in the coding deficits.

5.7.8 Engagement in the Field Walking or driving about in a neighborhood as a stranger should and often raises the concerns of the residents or businesses. In many cases, someone will engage the observer in conversation, asking about what the observer(s) are doing. In most cases, the engagement may be one where the individuals are concerned but friendly. Occasionally, the engagement may start or end hostile. As noted above, it is important to train observers on how to respond. The first reaction in most cases is to simply explain the purpose of the SSO process. In these instances, it is useful to have an identification card and a flyer or letter that explains who the observers are, the purpose of the project, and who to contact for more information.

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On rare occasions, the reaction to the observers is hostile or threatening. In these situations, the observers should focus on safety, leaving the segment as soon as possible. In certain instances, it is best if the entire observation process is stopped for the immediate timeframe until supervisors can regroup and reconsider the options. It is important for observers to always be respectful of the privacy rights of citizens in a neighborhood. Once again, in these situations, once safety is reached, narrative notes should be added to the street segment coding instrument.

5.8 Final Data Collection Efforts 5.8.1 Debriefing At the close of period of field work, the observers should debrief, review the coding forms, and clarify what they saw, smelled, felt and experienced. If more than one observer participated, they should discuss how they each felt in the various street segments, working to explain why they felt as they did.

5.8.2 Processing the Data Within 24–48 h, data and notes collected on the observation forms should be entered into database system. Efforts should be taken to identify missing data and rectify errors as soon as possible. Photographs should be downloaded and updated into the data structures if possible or at least labeled correctly for later reporting. In rare cases, it may be possible to use data publicly available on Google maps to verify or collect missing data about physical structures.

5.8.3 Creating the Narratives Time should be set aside to write up narrative notes and to develop overall descriptions of the areas under consideration. The narrative descriptions by the observers should detail the boundaries of the areas observed, the number of observations made, the general impressions, and any specific detail of events or conversations that occurred. The notes should document the highlights of the observations made in the neighborhood. Finally, the notes should document who completed the observations and over what period the observations were completed.

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5.8.4 Reporting Findings As stated in other chapters, methods for analysis of neighborhood results, too, are not described as they are beyond the scope. However, as a rule, basic frequencies and summary results for the neighborhoods should be generated for each variable on the coding instrument, either at the end of the process or on a weekly basis as the data is collected. Care should be taken to note and investigate any major outliers present in the data. If necessary, supervisors may want to revisit the street segments of the outliers to attempt to replicate the results.

5.9 Summary This chapter sought to advance the field of knowledge concerning how to systematically study neighborhoods as related to crime, physical and social disorganization, and police–citizen interactions. It advanced the methodological understanding of how to conduct environment-based systematic social observations, EBSSO, with the intent of improving our understanding of how “place” impacts these issues. The chapter provided a step-by-step process with tips, tricks, and examples for conducting EBSSOs. Specifically, the chapter explained how to frame a neighborhood, the theoretical considerations to developing the research strategy, how to create a measurement tool and what variables should be considered, and how to prepare for field work in terms of pilot testing and determining the data collection methods. Once the study is launched, strategies for sampling, hiring, training, and deploying observers and notifying the community were discussed. In addition, we discussed the ways to collect the data in terms of walking or driving in the neighborhoods. The final sections briefly described how to process the collected data for further analysis. Overall, EBSSO is a strategy to conduct micro-level research, which offers distinctive insights into understanding the complexities of neighborhood functioning. Researchers and practitioners, including, police, community members and policy makers, can benefit from understanding the baseline information generated about micro-neighborhoods. EBSSO is a good way to examine the root causes of crime based on physical and social disorder. EBSSO defines an approach to examine the sum of individualized attitudes and actions that are key components driving how citizen interact with each other and with the police. When community members are involved in the process, often, they begin to develop greater connection to their neighborhood and a sense of increased social responsibility. When the police are directly involved, particularly in problem-­ solving efforts, they improve their hotspot policing strategies and are more focused on what specific elements of the neighborhood need to be fixed. They also often build the relationships and trust with residents. In turn, often police officers alter their beliefs and behaviors about the neighborhoods, and in turn, these refined perspectives shift how they, as police, are received by the residents. Together,

References

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community members and the police are more effective in their efforts to engage political entities to allocate resources needed to provide for long term solutions. In sum, hyper-awareness of the sights, sounds, smells and feeling in a neighborhood often leads positive neighborhood changes. Resources A pair of observation instruments, one capturing social disorder and another focused on physical disorder are available for review here: https://doi.org/10.6084/m9.figsh are.22266217.

References Braga, A. A., Welsh, B. C., & Schnell, C. (2015). Can policing disorder reduce crime? A systematic review and meta-analysis. Journal of Research in Crime and Delinquency, 52(4), 567–588. Brantingham, P. J., & Brantingham, P. L. (1991). Introduction to the 1991 reissue: Notes on environment criminology. In Environment criminology (pp. 1–6). Waveland Press. Burgess, E.  W. (2011). “The growth of the city: An introduction to a research project”: From Robert E. Park, Ernest W. Burgess, and Roderick D. McKenzie, The City (1925). In The city reader (pp. 207–215). Routledge. Bursik, R. J., & Grasmick, H. G. (1993). Neighborhoods and crime: The dimensions of effective community control. Lexington Books. Eck, J. E., Gersh, J. S., & Taylor, C. (2000). Finding crime hot spots through repeat address mapping. In Analyzing crime patterns: Frontiers of practice (pp. 49–64). Sage. Hoeben, E. M., Steenbeek, W., & Pauwels, L. J. (2018). Measuring disorder: Observer bias in systematic social observations at streets and neighborhoods. Journal of Quantitative Criminology, 34, 221–249. Institute for Social Research, University of Michigan. (2023). Resource Guide Project on Human Development in Chicago Neighborhoods. NACJD. https://www.icpsr.umich.edu/web/pages/ NACJD/guides/phdcn/index.html Klinger, D. A. (1997). Negotiating order in patrol work: An ecological theory of police response to deviance. Criminology, 35(2), 277–306. Levine, N. (2004). CrimeStat III: A spatial statistics program for the analysis of crime incident locations (version 3.0). Ned Levine & Associates/National Institute of Justice. Levine, N. (Ed.). (2010, July). CrimeStat: A spatial statistics program for the analysis of crime incident locations (Vol. 33). Ned Levine & Associates/The National Institute of Justice. Mastrofski, S. D., Reisig, M. D., & McCluskey, J. D. (2002). Police disrespect toward the public: An encounter-based analysis. Criminology, 40(3), 519–552. Odgers, C. L., Caspi, A., Bates, C. J., Sampson, R. J., & Moffitt, T. E. (2012). Systematic social observation of children’s neighborhoods using Google street view: A reliable and cost-­ effective method. Journal of Child Psychology and Psychiatry, 53(10), 1009–1017. https://doi. org/10.1111/j.1469-­7610.2012.02565.x Reiss, A. J. (1971). Systematic observation of natural social phenomena. Sociological Methodology, 3, 3–33. https://doi.org/10.2307/270816 Sampson, R.  J. (2006). Collective efficacy theory: Lessons learned and directions for future inquiry. Taking Stock: The Status of Criminological Theory, 15, 149–167. Sampson, R.  J., & Raudenbush, S.  W. (1999). Systematic social observation of public spaces: A new look at disorder in urban Neighborhoods 1. American Journal of Sociology, 105(3), 603–651. Skogan, W. G. (1989). Communities, crime, and neighborhood organization. Crime & Delinquency, 35(3), 437–457.

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Skogan, W. G. (1990). The police and the public in England and Wales: A British crime survey report. HM Stationery Office Londres. Smith, D. A. (1986). The neighborhood context of police behavior. Crime and Justice, 8, 313–341. Solomon, S.  E. (2019). Neighborhood matters: Crime, collective efficacy and foreclosures in Miami. Maastricht University. Terrill, W., & Reisig, M.  D. (2003). Neighborhood context and police use of force. Journal of Research in Crime and Delinquency, 40(3), 291–321. Uchida, C. D., & Swatt, M. L. (2013). Operation LASER and the effectiveness of hotspot patrol: A panel analysis. Police Quarterly, 16(3), 287–304. Uchida, C. D., Swatt, M. L., Solomon, S. E., & Varano, S. P. (2013). Data-driven crime prevention: New tools for community involvement and crime control. Retrieved from https://www.ojp.gov/ pdffiles1/nij/grants/245408.pdf Uchida, C. D., Swatt, M. L., Solomon, S. E., & Varano, S. P. (2015). Community, crime control, and collective efficacy: Neighborhoods and crime in Miami. Lexington Books. Weisburd, D., Bernasco, W., & Bruinsma, G. (2009). Putting crime in its place: Units of analysis in geographic criminology. Springer. Whyte, W. F. (1943). Street corner society. University of Chicago Press. Wilson, J. Q., & Kelling, G. (1993). Broken windows. In G. P. Alpert & R. G. Dunham (Eds.), Critical issues in policing (2nd ed., pp. 395–407). Waveland Press, Inc. Wooditch, A., & Weisburd, D. (2016). Using space–time analysis to evaluate criminal justice programs: An application to stop-question-frisk practices. Journal of Quantitative Criminology, 32(2), 191–213. Youth Policy Institute. (2019). ¡SOMOS MACARTHUR! CBCR Planning Phase Narrative Internal Report. Youth Policy Institute, Los Angeles, CA.

Chapter 6

The Future of Systematic Social Observation and Policing

6.1  New Technology and SSO 6.1.1 Field Observations and Emerging Technology The use of new technology in IPSSO is evident in the Los Angeles Police Department procedural justice (LAPD-PJ) and the Belgian Observation and Systematic Study of Decisions (BOSS-D) projects. Compiling online surveys for completion using platforms such as Qualtrics represents a new way of executing this work and allows for distributed or decentralized teams to contribute to unified data repositories. Thus, remote work across a team is one affordance of that technology. The second advance both research teams note is the use of tablets in the field. This allowed for notes, and with mobile hotspots, connectivity to surveys in the case of LAPD-PJ study. These are very different from the POPN study outlined by Mastrofski et al. (1998), which was based on a software solution that was lab-based, centralized for the research team, and completely based on paper and pencil note-taking. Similarly, EBSSO has made substantial advances in the technology available to those collecting data in the field on environmental conditions. Besides photo, video, and audio capture, the EBSSO approach can equip coders with logs for environmental capture or draw upon Google Street View (GSV) data for coding data from image repositories (Odgers et al., 2012).

6.1.2 Integrating Machine Learning and VBSSO A possibility for sampling video for VBSSO could rely on the use of artificial intelligence (AI) or machine learning (ML) techniques. These algorithms could scan BWC archives for candidate videos that could then be reviewed in the context of a © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. McCluskey et al., Systematic Social Observation of the Police in the 21st Century, SpringerBriefs in Criminology, https://doi.org/10.1007/978-3-031-31482-7_6

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research project. The population of videos could be preprocessed along dimensions of interest using these tools. While AI and ML are still being tested on video footage, natural language processing (NLP) has promise since it is easier to convert the audio channel  of footage to text. Examination of key words can then serve as a method to identify cases for inclusion in a study or otherwise classify video. One project, funded by the Bureau of Justice Assistance in the United States, features the Rochester, New  York Police Department’s (RPD) video archive as a machine learning (ML) or artificial intelligence (AI) application test case (McCluskey, 2023). The purpose is to identify, for example, escalation and de-­ escalation through an algorithmic exploration of the audio and video channels of the BWC archive. The objective of the automated scanning will be to generate samples of videos that have similar starting points (high tension, highly emotional, coercive) but give way to different ending points (use of force as compared to compliance, calming, or amicable conclusions). If successful, this automated video search process will allow for the development of case-control type studies of escalation and de-escalation. The identified videos will then be subjected to a VBSSO process that features human review and coding of cases. It is anticipated that coders will include student interns and RPD officers so that comparisons of codebook applications across different groups can be assessed. The development of codebooks will proceed, as suggested in the chapters on IPSSO and VBSSO, starting with the extant research and assessing the utility of time-based approaches to escalation and de-­ escalation patterns. One significant advantage of the RPD-ML project is that it will train officers in the VBSSO coding and use their knowledge-base to refine the codebook development and test the reliability of code application between officers and civilian coders. The promise of computer vision (CV) is, at this juncture, limited by the mounting of the camera on the key participant in the police–citizen encounter (McCluskey & Uchida, 2023). This contributes a bias in the framework of video data analysis (VDA), and additionally, it captures movement of one participant (Nassauer & Legewie, 2018). This jittering effect makes CV application more difficult as compared to the typical fixed camera approaches used in computational resolutions of CV work for VBSSO.

6.1.3 Environment-Based SSO and Machine Learning With regard to EBSSO there has been a noted interest in drawing on a variety of archival imagery, such as GSV, to code environmental data, including recent examinations of reliability and validity of EBSSO using the data (Clausén Gull et  al., 2023). Direct comparisons of in-person EBSSO and GSV-based EBSSO in Detroit, MI confirm the virtual assessment of neighborhood physical disorders were highly correlated with in-person measures (Mooney et al., 2017). A wide variety of data beyond the GSV archive exist in a variety of street view imagery (SVI) repositories in different countries, many of which can be accessed

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for automated processing (see, e.g., Biljecki & Ito, 2021 for a review). Given the still image capture of SVI platforms, the problem of jitter in the BWC VBSSO is not present, and the application of ML approaches for coding data is practical and well within the reach of current computational social science methods. For example, Hipp et al. (2022) derived aspects of the built environment in Santa Ana, CA using GSV and modeled crime in street segments using those measures. Naik et al. (2017) used CV methods to examine physical changes in neighborhoods across five US cities. The measure of physical disorder and a variety of dimensions of the physical environment with ML EBSSO approaches is rapidly developing. We anticipate, like VBSSO, such approaches will aid in developing new theoretical insights and frameworks when applied to policing.

6.2 Comparative Research via SSO 6.2.1 Organizational Comparisons Organizations and international comparisons of social control, especially with regard to VBSSO applications, in our judgment, represent a near-term possibility for research using BWC footage. With regard to the United States there are thousands of agencies now using BWCs and developing archives of footage. Creating coding teams, built off of common research questions, would allow for an agency comparison that was last possible in the Police Services Study (PSS) data. Further, with the capture of rare events in archival footage, speaking to comparative use of force patterns, for example, would be feasible in a way not accessible to IPSSO. Schafer et al.’s (2022) work captured all 59 uses of force in their sample from the Newport News, VA police department over a 2-year period using VBSSO. In contrast, Worden’s (2015) reanalysis of PSS data examined uses of necessary/ unnecessary force among the 1819 suspects encountered with a total of 35 reasonable force uses (1.9%) and 16 unreasonable uses were documented – a total of 51 observed across all police organizations in that study.

6.2.2 International Comparative Research A second area of comparative research that would be ripe for the usage of VBSSO samples involves cross-national comparisons of what police do. Common tasks such as traffic stops, resolving disputes, or taking crime reports could be sampled from BWC archives. Local experts on policing could serve to ensure parallel codebook development with their international counterparts. This is slightly more complicated than an organizational comparison within the United States for at least three reasons. First,

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identification of legal frameworks and interaction patterns between the police and citizens that align with codebooks will require substantial discussion and consideration. Second, the possibility of multiple languages for which codebooks must be developed and trained is another consideration. Third, it is possible that privacy regulations in one site will limit some of the BWC footage that can be used in the entire project, and navigating research approval would be more complex. These difficulties, however, are small in comparison to the utility that such comparisons may yield for police researchers, police managers, and policy-makers alike.

6.3 Theoretical Advances and New Insights The SSO of the police, as outlined historically, typically tests a research question based on sample, protocols, coding, and analysis strongly rooted in theory. Worden’s (2015) situational, organizational, and officer determinants are, for example, a framework that informs much of the research on police decision-making. Engel’s (2002) and Engel and Worden’s (2003) work on supervision, using SSO data, is an overlay on this. We would argue that the opening of BWC archives will allow for a much deeper appreciation of what constitutes supervision and how decisions are made. The organizational variation, supervisory variation, and situational landscapes can be varied across officers to help build models aimed at testing specific theories in a way that the prospective IPSSO data collection effort often was not well-equipped either due to rarity of outcomes of interest (use of physical force) or not enough had been seen and understood thoroughly enough to develop more than preliminary research questions.

6.3.1 Assessing the Effectiveness of Police Supervision By working through the archival BWC footage we can see supervisors in mundane, potential violent, and critical incidents, perhaps learning much more about what supervisors do to improve outcomes or aid officers in de-escalation on the scene. This might help to answer the question, oft posed, but never answered: What is good supervision? In what ways does/can supervision affect street-level performance of patrol? The importance of supervision is regularly emphasized in the literature, but the paucity of research is often lamented (Skogan & Frydl, 2004). Among the limited research on supervision conducted using SSO, Engel and Worden (2003) examined officers’ use of time for problem-solving and linked it to supervisors’ styles using IPSSO data collected in the Project on Policing Neighborhoods (POPN). The analysis showed more time spent on problem-solving by officers, when they believed their supervisors emphasized it. Observational research on officers in Baltimore,

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MD, however, found little evidence that unassigned time was directed by supervisors (Famega et al., 2005). Smith (1984) used the Police Services Study (PSS) data to generate models of officers’ discretionary choice, which indicated that presence of a sergeant on scene increased the likelihood of an arrest. The magnitude of this effect varied across departments. Recent reanalysis of those data by Johnson (2008) suggested that observed officers spent significantly less unassigned time on personal business when they had more face-to-face contact with supervisors. Terrill’s (2000) dissertation work, based on POPN SSOs, captured data on more than 3000 police-suspect encounters in St. Petersburg, FL and Indianapolis, IN. Linking officers’ surveyed beliefs about the likelihood of supervisory critique and intervention with those SSO observations allowed him to examine that belief and its relationship to highest levels of force used. A bivariate relationship between beliefs about supervisory intervention and highest level of force applied was uncovered, but that effect was not statistically distinguishable from zero in multivariate models controlling for situational and organizational variables. Hypotheses from the literature suggest that supervisors with smaller groups of officers may be more able to direct proactive work and manage officer conduct. Many outcomes of interest, however, would likely be mediated by a variety of attitudes and factors, such as supervisory styles (Reynolds, 2020). Taken together, the research and reform (improving supervision) and the suggestions gleaned from prior research, indicate that VBSSO study designs that focus on supervision would be especially valuable for police managers, but also help extend SSO work further in terms of theory and methodology.

6.3.2 Training and Behavioral Changes Similarly, training focused on critical incidents, implicit bias, and de-escalation provide a learning laboratory to examine differential outcomes as a consequence of the training. Specifically, training aims not for attitude change but behavior change, promoting safer outcomes for officers and citizens, for example. Paper and pencil surveys, agency data built on use of force or complaint forms, and the like, to us, seem a bridge too far in understanding how cameras or training can influence police. The everyday contact with the public, on the other hand, is where that training should manifest change, if it is effective. If no change is detectable in rigorously designed studies, then new or revised training may be necessary. Currently, especially in the United States, training and retraining is the response du jour. The effectiveness of procedural justice (pre-George Floyd, Minneapolis), critical incident training (pre-Tyre Nichols), and de-escalation (pre-Breonna Taylor Louisville) based on data derived from police record systems (complaints, uses of force, arrests, etc.) should no longer be the gold standard, even if in a randomized controlled trial. The measurement of what police  do to citizens, in

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everyday encounters, should supplant this suite of convenient and flawed measurement based on official department records. The application of such effort is dependent on the underlying research question, but given the importance of life, limb, and legitimacy for officers and the public, the three programs mentioned above should be reassessed when implemented in other departments. The design of research capitalizing on BWC footage should be an expectation of such evaluation research. Further, application of internal VBSSO could become part of supervision, given that many supervisors already often review camera footage randomly. A purposive, trained approach to cases would, in our opinion, be another avenue for developing a repository of knowledge to advance the practice of public policing beyond disciplinary concerns.

6.3.3 The Context of Police Service Delivery Neighborhood effects, broadly construed, have been implicated in theory (Klinger, 1997) and empirical examinations of police decisions (Smith, 1986). The EBSSO data collected could provide evidence of environmental change over time, for place-­ based policing researchers. That is, neighborhood improvement efforts should have a detectable change in the environmental measures discussed here, and the longevity of that change and the rate to which the change decays back to a preexisting state of, say, physical disorder, are important. But EBSSO also can capture the contexts in which police service is delivered and provide a theoretical motivation for measuring the backdrop against which decisions take place and where. Coding and combining data from sources might make it possible to answer questions such as: To what extent do graffiti, disorder, and broken windows, cast as cues or stimuli for individuals who might commit crime, also shape the decisions of those who are tasked with exercising formal social control in those same neighborhoods? Disrespect, arrest, and use of force, as examples, have all been found to vary across the neighborhood level; thus, could EBSSO refined to smaller segments, such as street sections, to capture micro-environmental influences police behavior? The measurement, capture, and testing of such hypotheses, we would argue, is now open to EBSSO and VBSSO researchers, who can merge data from these two types of data collection efforts.

6.4 Concluding Thoughts on SSO 6.4.1 Cooperation Cooperation between researchers and police agencies is paramount for the success of a research endeavor based on any SSO modality (Worden & McLean, 2022). Understanding the nature of the work and data collected requires a partnership and

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preexisting knowledge bases that cannot be underestimated. Besides the cooperation of the organizations under study, it is imperative that the researchers engage in inter-research team cooperation and conversation to learn more about intriguing designs, new ways of measuring, and technological applications that can reduce the labor costs of deploying SSO.

6.4.2 Replication Rigor of research based on reliable and valid measurement, replication, and a repository of findings that build an iterative knowledge base for police managers, the public, and researchers alike should be the goal the research program outlined here. Review and coding of footage from BWC archives, for example, allows for a more rigorous codebook development and assessment of reliability levels of coding and coders. The latter was absent from IPSSO studies, wherein training, group exercises in VBSSO, and logical consistency checks on data were the state of the art for determining reliability. Specifically, VBSSO and EBSSO, when based on image capture or footage, are both areas in which replication of research and cross-coding by observers or entire research teams would yield insights into item reliability, improvements in codebook development, and opportunities for development of substantial coded data archives built on comparable measures.

References Biljecki, F., & Ito, K. (2021). Street view imagery in urban analytics and GIS: A review. Landscape and Urban Planning, 215, 104217. https://doi.org/10.1016/j.landurbplan.2021.104217 Clausén Gull, I., Kapetanovic, S., Norman, Å., Ferrer-Wreder, L., Olsson, T.  M., & Eninger, L. (2023). Neighborhood conditions in a Swedish context-two studies of reliability and validity of virtual systematic social observation using Google Street View. Frontiers in Psychology, 14, 1020742. https://doi.org/10.3389/fpsyg.2023.1020742 Engel, R. S. (2002). Patrol officer supervision in the community policing era. Journal of Criminal Justice, 30(1), 51. https://doi.org/10.1016/S0047-­2352(01)00122-­2 Engel, R. S., & Worden, R. E. (2003). Police officers’ attitudes, behavior, and supervisory influences: An analysis of problem solving. Criminology, 41(1), 131–166. https://doi.org/10.1111/j.1745­9125.2003.tb00984.x Famega, C. N., Frank, J., & Mazerolle, L. (2005). Managing police patrol time: The role of supervisor directives. Justice Quarterly, 22(4), 540–559. https://doi.org/10.1080/07418820500364692 Hipp, J. R., Lee, S., Ki, D., & Kim, J. H. (2022). Measuring the built environment with Google Street View and machine learning: Consequences for crime on street segments. Journal of Quantitative Criminology, 38(3), 537–565. https://doi.org/10.1007/s10940-­021-­09506-­9 Johnson, R.  R. (2008). Field supervisor behaviour and officer on duty personal business. International Journal of Police Science and Management, 10(3), 339–348. https://doi. org/10.1350/ijps.2008.10.3.89

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Klinger, D. A. (1997). Negotiating order in patrol work: An ecological theory of police response to deviance. Criminology, 35, 277–306. https://doi.org/10.1111/j.1745-9125.1997.tb00877.x Mastrofski, S. D., Parks, R. B., Reiss, A. J., Worden, R. E., DeJong, C., Snipes, J. B., & Terrill, W. (1998). Systematic observation of public police: Applying field research methods to policy issues. National Institute of Justice. McCluskey, J. (2023). Video data analysis: The use case of police body camera footage and systematic social observation. Paper presented at the McKenzie Salon Series: Rochester Institute of Technology. McCluskey, J. D., & Uchida, C. D. (2023). Video data analysis and police body-worn camera footage. Sociological Methods and Research. https://doi.org/10.1177/00491241231156968 Mooney, S. J., Bader, M. D. M., Lovasi, G. S., Teitler, J. O., Koenen, K. C., Aiello, A. E., et al. (2017). Street audits to measure neighborhood disorder: Virtual or in-person? American Journal of Epidemiology, 186(3), 265–273. https://doi.org/10.1093/aje/kwx004 Naik, N., Kominers, S.  D., Raskar, R., Glaeser, E.  L., & Hidalgo, C.  A. (2017). Computer vision uncovers predictors of physical urban change. Proceedings of the National Academy of Sciences of the United States of America, 114(29), 7571–7576. https://doi.org/10.1073/ pnas.1619003114 Nassauer, A., & Legewie, N.  M. (2018). Video data analysis: A methodological frame for a novel research trend. Sociological Methods and Research, 50(1), 135–174. https://doi. org/10.1177/0049124118769093 Odgers, C. L., Caspi, A., Bates, C. J., Sampson, R. J., & Moffitt, T. E. (2012). Systematic social observation of children’s neighborhoods using Google Street View: A reliable and cost-­ effective method. Journal of Child Psychology and Psychiatry, 53(10), 1009–1017. https://doi. org/10.1111/j.1469-­7610.2012.02565.x Reynolds, D.  L. (2020). Unpacking the untapped potential of first-line supervisors: Sergeants’ role in managing police discretion (Publication Number 28150494). Ph.D., State University of New York at Albany. ProQuest Central Essentials; ProQuest Dissertations and Theses Global; Social Science Premium Collection. Schafer, J., Hibdon, J., & Kyle, M. (2022). Studying rare events in policing: The allure and limitations of using body-worn camera video. Journal of Crime and Justice. https://doi.org/10.108 0/0735648X.2022.2062036 Skogan, W., & Frydl, K. (2004). Fairness and effectiveness in policing: The evidence. Committee to Review Research on Police Policy and Practices. Committee on Law and Justice, Division of Behavioral and Social Sciences and Education. The National Academic Press. Smith, D.  A. (1984). The organizational context of legal control. Criminology, 22(1), 19–38. https://doi.org/10.1111/j.1745-­9125.1984.tb00286.x Smith, D. A. (1986). The neighborhood context of police behavior. Crime and Justice, 8, 313–341. Terrill, W. (2000). Police coercion: Application of the force continuum (Publication Number 9967093). Ph.D., Rutgers The State University of New Jersey. ProQuest Dissertations and Theses Global. Worden, R.  E. (2015). The “causes” of police brutality: Theory and evidence on police use of force. In Criminal justice theory (pp. 149–204). Routledge. Worden, R. E., & McLean, S. J. (2022). Collaborative practitioner–researcher partnerships in policing: Two researchers’ reflections. Policing: A Journal of Policy and Practice, 16(3), 329–343. https://doi.org/10.1093/police/paac036

Index

C Comparative policing research, 2, 57 E Ecometrics, 4, 12 Environmental SSO, viii, ix, 5, 11–14, 75–95, 97–99, 102 Environment-based SSO (EBSSO), ix, 5, 11–14, 75–95, 97–99, 102, 103 Ethnographic studies, 8, 82 H How-to-guide, ix, 17–43 M Machine learning (ML), 55–56, 97–99

Police decision-making, 26, 37, 43, 44, 100 Police discretion, 8, 36 Procedure, 9, 17, 21–23, 25–31, 33, 42, 52, 53, 57, 58, 62, 71, 76, 84, 86, 88 R Reliability and coding, 5, 11, 41, 61, 69, 103 S Social disorder, 11–14, 75, 78, 80–82, 94 Social science research, 3, 17–44 Systematic social observation (SSO), v–vii, ix, 2–5, 7–14, 17–44, 47, 53, 59, 61, 65, 66, 76, 77, 79, 80, 84, 86, 90, 92, 97–103

N Neighborhoods and place, 11–13 P Physical disorder, 75, 76, 80–82, 98, 99, 102 Police behavior, 3, 5, 8, 10, 11, 13–14, 17, 21, 54, 75, 76, 102

V Video-based SSO (VBSSO), v, ix, 2, 4, 11, 14, 20, 21, 23, 47–71, 97–99, 101–103 Video data analysis (VDA), 61, 69, 98

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. McCluskey et al., Systematic Social Observation of the Police in the 21st Century, SpringerBriefs in Criminology, https://doi.org/10.1007/978-3-031-31482-7

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