The article explores the topic of outdoor rape in Stockholm, Sweden and how different geographic variables may affect the relative risk in certain areas. The location of such crime is crucial in determining the risk of the victims, and three important elements were highlighted by the authors as main consideration for the criminals. First, accessibility, in the sense of getting to, and knowing the crime scene and being able to flee it quickly. Second, opportunity, that is the presence of women, perceived as vulnerable, who either live in the neighbourhood or travel through it on their way home. Lastly, anonymity for the criminal act.
Therefore, three hypothesis were raised by the authors: 1) High counts of rape are associated with areas offering opportunity to the offender. 2) High counts of rape are associated with areas with poor surveillance and/or poor social control where residents have a high fear of crime. 3) High counts of rape are associated with areas that have good accessibility because they bring potential targets into an area and offer a quick and easy escape route from the crime scene for the offender.
Two statistical models were used in order to test how risk factors individually and jointly affect the risk of outdoor rape. 11 covariates were first identified from the three key categories which were accessibility, anonymity, and opportunity. For instance, whether subway station is present or not and the percentage of the population who fear crime and who avoid going out in the neighbourhood. The first model used was the Bayesian Hierarchical Poisson regression model for a “whole map” analysis and a Bayesian profile regression model for a localized analysis. From the first analysis, the researcher identified that the presence of a subway station in a basområde (small area) generally increases the risk of outdoor rape in an area by over 50 percent. Additionally, a basområde with a high level of population turnover tends to have an increased risk of rape.
However, risk factors such as lower average income showed a weak evidence to increased risk in outdoor rape. They also concluded that factors such as people’s fear of crime and the presence of forested or industrial areas do not appear to be associated with the risk of rape. The second model categorized the study area into seven clusters with relative risk of rape. From the result, the top 2 highest risk clusters represents area mainly in the city centre with high population turnover, small female residential populations and small numbers of schools with large number of liquor outlets. The 3 low-risk clusters represents primarily industrial areas whereas Clusters 1 and 3 are the affluent suburban areas with few alcohol outlets and few robbery cases, suggesting few micro-sites offering anonymity for the criminal act.
Overall, I believe this particular case study offered me a strong understanding to the risk factors to outdoor rape in Stockholm. Specifically, understanding certain covariates relating to the three theoretical constructs which were accessibility, opportunity and anonymity provided me information on why certain clusters represented higher rape risks. I was surprise that certain risks I had perceived as relevant resulted as insignificant in their finding such as forested area, which leads me to believe that other characteristics need to be present in order to constitute a ‘whole map’ risk factor. Therefore, I would rate this article 9/10 as they successfully identified different clusters within Stockholm and explained their relative risks using covariates which I believe were accurate factors which lead to outdoor rape.
Source:
Ceccato, V., Li, G., & Haining, R. (2019). The ecology of outdoor rape: The case of Stockholm, Sweden. European Journal of Criminology, 16(2), 210–236. https://doi.org/10.1177/1477370818770842