- Henning. (2022). Policing and Trauma: The Harms of Hyper-Surveillance and Over-Policing Youth of Color. Criminal Justice (1986), 37(1), 42–45.
The author discusses the concept of hyper-surveillance, which refers to the use of advanced technologies to monitor and control the movements of certain groups of people, particularly those who are seen as potential threats. He highlights how this approach has been used disproportionately against the youth of color, leading to high levels of anxiety and fear among these communities.
- Schneider. (2022). Public Criminology and Media Debates Over Policing. Studies in Social Justice, 16(1), 227–244. https://doi.org/10.26522/ssj.v16i1.2694
Schneider’s article examines the intersection of public criminology and media debates over policing. Public criminology refers to the efforts of scholars and practitioners to engage with the public in discussions about crime, justice, and social control. The author argues that the media plays a crucial role in shaping public opinion about policing and crime and that criminologists have a responsibility to contribute to these debates in a constructive and informed way.
- Bandes. (2018). Video, Popular Culture, and Police Excessive Force: The Elusive Narrative of Over-Policing. The University of Chicago Legal Forum, 2018, 1–.
In this article, Bandes examines the role of video and popular culture in shaping public perceptions of police excessive force and over-policing. She argues that while video evidence of police brutality has become more prevalent in recent years, the narratives that emerge from these incidents are often contested and elusive, shaped by a range of cultural and historical factors. Bandes also discusses the limitations of video evidence as a tool for addressing police violence. She argues that video evidence is often subject to interpretation and can be used to reinforce existing biases and narratives about crime and punishment. Furthermore, she notes that the use of video evidence in court cases is often fraught with challenges, including issues of admissibility and the possibility of tampering.
- Jefferson. (2016). Broken Windows Policing and Constructions of Space and Crime: Flatbush, Brooklyn: Broken Windows Policing: Flatbush, Brooklyn. Antipode, 48(5), 1270–1291. https://doi.org/10.1111/anti.12240
The author argues that broken windows policing has a significant impact on the construction of space and crime in urban neighborhoods. By targeting minor offenses, such as littering and loitering, the police create a sense of order and control in public spaces. However, this strategy also reinforces social hierarchies and leads to the criminalization of marginalized communities, particularly people of color and low-income individuals. Jefferson uses the case study of Flatbush to explore the ways in which broken windows policing has affected the neighborhood’s physical and social landscape. She argues that the strategy has led to the displacement of low-income residents and the gentrification of the area, as well as increased police presence and surveillance.
- Porter, Rader, N. E., & Cossman, J. S. (2012). Social Disorganization and Neighborhood Fear: Examining the Intersection of Individual, Community, and County Characteristics. American Journal of Criminal Justice, 37(2), 229–245. https://doi.org/10.1007/s12103-011-9125-3
In this article, Porter, Rader, and Cossman examine the relationship between social disorganization, neighborhood fear, and individual, community, and county characteristics. Social disorganization is a theory that suggests that certain neighborhood characteristics, such as poverty, population density, and residential instability, can contribute to high levels of crime and disorder. The authors use data from the National Survey of Fear of Crime and the U.S. Census Bureau to analyze the relationship between social disorganization, neighborhood fear, and various individual and contextual factors. They find that social disorganization is significantly related to neighborhood fear, even after controlling for individual-level factors such as age, gender, race, and income.
