Risk Factors for Violent Dissident Republican Incidents in Belfast: A Comparison of Bombings and Bomb Hoaxes

Abstract

Objectives To identify risk factors for bombings and bomb hoaxes committed by dissident Republicans in Belfast, Northern Ireland. Methods Risk terrain modelling (RTM) was applied to each type of incident to identify significant risk layers. Results Previous protests and riots [relative risk value (RRV) of 14.07; spatial influence (SI) of 100 m], punishment attacks (RRV 6.56; SI 300 m) and areas dense with pubs and bars (RRV 4.98; SI 200 m) were identified as risk factors for bombings. Punishment attacks (RRV 10.77; SI 100 m), police stations (RRV 8.76; SI of 200 m) and places dense with shops (RRV 6.94; SI 400 m) were identified as risk factors for bomb hoaxes. Descriptive statistics regarding predictive accuracy concluded that half of incidents for both types occurred in high or very high risk cells in a 3-year post-study period. Conclusions RTM could be a useful tool in guiding targeted responses to the dissident Republican threat in Belfast. The results suggest that there is some assessment of risk by the offenders, and that they are selecting targets rationally. Due to the differences in risk factors for the two types of events it can be proposed that there may be differences between targets relevant to ideology and realistic targets with increased chance of success.

Systematic review and meta-analysis of risk terrain modelling (RTM) as a spatial forecasting method

“…Two studies have used RTM to examine predictive accuracy for terrorist events. Both had promising results, with hit rates of 43% (Onat & Gul, 2018) and 50% (Marchment et al, (2019). Onat and Gul (2018) used RTM to identify correlates of terrorist incidents in Turkey, using data acquired from Istanbul Police Department between 2008 and 2012.…”

“…Logistic regression results suggested that for every increased unit of risk, the likelihood of a violent terrorist incident happening at a particular place increased by 2.2%. Marchment et al, (2019) used RTM to identify correlates of dissident Republican incidents in Belfast, Northern Ireland. They compared two incident types, bombings and bomb hoaxes.…”

Assessing the Differential Impact of Vacancy on Criminal Violence in the City of St. Louis, MO

“…In this sense, RTM provides not only a means of proactively distributing police resources but also a mechanism to intervene in areas before problems manifest. Over the past 10 years, RTM has been applied in a variety of contexts to understand a range of criminal acts such as terrorism (Marchment et al, 2019; Onat, 2019), property crime (Andresen, 2018; Dugato et al, 2018; Lersch, 2017; Moreto et al, 2014), gang violence (Valasik, 2018), drug crime (Escudero & Ramírez, 2018), child abuse (Daley et al, 2016), robbery (Barnum et al, 2017; Caplan et al, 2015 , 2017; Connealy & Piza, 2019; Drawve et al, 2016), and both homicide and aggravated assault (Drawve & Barnum, 2018; Gerell, 2018; Giménez-Santana et al, 2018; Kennedy et al, 2016; Thomas & Drawve, 2018; Valasik et al, 2019).…”

Risky Business: Examining the 80-20 Rule in Relation to a RTM Framework

“…That is, we might know both bars and liquor stores influence crime, but when in close proximity to one another, the risk might be even greater, perhaps exponentially, for crime to occur. Prior research has demonstrated the utility of RTM to identifying significant CGAs for a variety of offenses including child maltreatment (Daley et al, 2016), drug dealing (Barnum et al, 2017), aggravated assault (Thomas & Drawve, 2018), gang violence (Valasik, 2018), homeless crimes (Yoo & Wheeler, 2019), robbery (Feng et al, 2019), suicide attempts (Lersch, 2020), opioid overdoses (Chichester et al, 2020), property crime (Andresen & Hodgkinson, 2018;Piza et al, 2017), and terrorism (Marchment et al, 2019). These analyses typically focus on place-based approaches to how prevention resources could be efficiently and effectively allocated based on the underlying diagnostics conducted by RTM.…”