Intervention or Involvement : A Video Observational Analysis of Bouncers in Aggressive Encounters

Little is known about how bouncer–patron interactions may influence a bouncer’s use of physical aggression. To address this gap, we offer a micro-interactional analysis examining real-life aggressive bouncer behavior captured by venue surveillance cameras. Quantitative results show that bouncer physical aggression is associated with interactions in which bouncers are directly involved as a conflict party, but not with interactions where they solely intervene as a third-party. Further, a qualitative analysis of emotional cues identifies anger as a plausible mechanism underpinning bouncer aggression. We consider the implications of these findings for night-time economy violence prevention strategies and discuss the relevance of video data for barroom research

Methodological developments in violence research

Über Jahrzehnte wurde Gewalt durch Interviews mit Betroffenen oder Tätern, durch teilnehmende Beobachtung oder Gewaltstatistiken untersucht, meist unter Verwendung entweder qualitativer oder quantitativer Analysemethoden. Seit der Jahrhundertwende stehen Forschenden eine Reihe neuer Ansätze zur Verfügung: Es gibt immer mehr Videoaufnahmen von gewaltsamen Ereignissen, Mixed Methods-Ansätze werden stetig weiterentwickelt und durch Computational Social Sciences finden Big Data-Ansätze Einzug in immer mehr Forschungsfelder. Diese drei Entwicklungen bieten großes Potenzial für die quantitative und qualitative Gewaltforschung. Der vorliegende Beitrag diskutiert Videodatenanalyse, Triangulation und Mixed Methods-Ansätze sowie Big Data und bespricht den gegenwärtigen und zukünftigen Einfluss der genannten Entwicklungen auf das Forschungsfeld. Das Augenmerk liegt besonders darauf, (1) wie neuere Videodaten genutzt werden können, um Gewalt zu untersuchen und wo ihre Vor- und Nachteile liegen, (2) wie Triangulation und Mixed Methods-Ansätze umfassendere Analysen und theoretische Verknüpfungen in der Gewaltforschung ermöglichen und (3) wo Anwendungen von Big Data und Computational Social Science in der Gewaltforschung liegen können.For decades violence research has relied on interviews with victims and perpetrators, on participant observation, and on survey methods, and most studies focused on either qualitative or quantitative analytic strategies. Since the turn of the millennium, researchers can draw on a range of new approaches: there are increasing amounts of video data of violent incidents, triangulation and mixed methods approaches become ever more sophisticated, and computational social sciences introduce big data analysis to more and more research fields. These three developments hold great potential for quantitative and qualitative violence research. This paper discusses video data analysis, mixed methods, and big data in the context of current and future violence research. Specific focus lies on (1) potentials and challenges of new video data for studying violence; (2) the role of triangulation and mixed methods in enabling more comprehensive violence research from multiple theoretical perspectives, and (3) what potential uses of big data and computational social science in violence research may look like

Social distancing compliance:A video observational analysis

PurposeVirus epidemics may be mitigated if people comply with directives to stay at home and keep their distance from strangers in public. As such, there is a public health interest in social distancing compliance. The available evidence on distancing practices in public space is limited, however, by the lack of observational data. Here, we apply video observation as a method to examine to what extent members of the public comply with social distancing directives.DataClosed Circuit Television (CCTV) footage of interactions in public was collected in inner-city Amsterdam, the Netherlands. From the footage, we observed instances of people violating the 1.5-meter distance directives in the weeks before, during, and after these directives were introduced to mitigate the COVID-19 pandemic.ResultsWe find that people complied with the 1.5-meter distance directives when these directives were first introduced, but that the level of compliance started to decline soon after. We also find that violation of the 1.5-meter distance directives is strongly associated with the number of people observed on the street and with non-compliance to stay-at-home directives, operationalized with large-scale aggregated location data from cell phones. All three measures correlate to a varying extent with temporal patterns in the transmission of the COVID-19 virus, temperature, COVID-19 related Google search queries, and media attention to the topic.ConclusionCompliance with 1.5 meter distance directives is short-lived and coincides with the number of people on the street and with compliance to stay-at-home directives. Potential implications of these findings are that keep- distance directives may work best in combination with stay-at-home directives and place-specific crowd-control strategies, and that the number of people on the street and community-wide mobility as captured with cell phone data offer easily measurable proxies for the extent to which people keep sufficient physical distance from others at specific times and locations

Out of prison, out of crime? The complex interplay between the process of desistance and severe resource disadvantages in women‘s post-release lives

We examine the influence of social capital, subjective changes and post-release resource disadvan- tages on women‘s desistance and reentry pathways. Using a sample of 1478 formerly incarcerated women, we estimate logistic hybrid random-effects models to assess the influence of several fac- tors on offending during a 7-year follow-up period. We use interviews with a subsample of women to explore the mechanisms underlying the quantitative findings. Results show that the effect of often-studied forms of social control are to a large degree dependent on (unmeasured) individual differences and circumstances, such as pre- and post-incarceration adversities, and the quality of forms of social control. A desire to desist from crime is often blocked by severe resource advantages

“It’s illegal to buy drugs from street dealers” - A Video-Based Pre-Post Study of a Behavioral Intervention to Displace Dealers from an Amsterdam Open-Air Drug Market

Objectives: A high number of street dealers operate in the Red Light District in Amsterdam, The Netherlands. To displace the dealers, the Municipality of Amsterdam installed text-based light projections in a street attracting a high number of dealers. Methods: To evaluate the intervention, we did a pre-post analysis of video footage from two CCTV cameras located in the street. In total, we analyzed 765 one-minute segments of footage from before and after the implementation. Results: The implementation was followed by a four percentage point reduction in street dealers. However, the estimated effect shows fragileness with wide confidence intervals, a p-value just below 0.05, and a Bayesian robustness analysis suggests that the intervention was not associated with the outcome. Conclusions: Analyzing CCTV-footage offers a unique avenue for evaluating small scale interventions in open-air drug markets. While we observed a decrease in the presence of dealers, the intervention still needs further validation