By Mathijs Kros, Tjeerd W. Piersma & Karin A. Beijersbergen

This paper investigates criminal career characteristics and trajectories of domestic burglars, residential and commercial robbers, and street robbers in the Netherlands. We used longitudinal data which includes the criminal cases from 1997 until 2020 for all people of 12 years or older. We studied all 89,062 offenders that had at least one criminal case in the period between 2002 and 2004. Semiparametric group trajectory models were used to cluster these offenders into groups with similar criminal careers. Our results suggest that in order to predict who will follow the career path of a life-course persistent offender, it is important to distinguish between specific groups of offenders. Life-course persistent offenders are found amongst domestic burglars, residential and commercial robbers, and street robbers, but not amongst offenders of other types of crime. Furthermore, the size of the group of life-course persistent offenders varies between the domestic burglars, residential and commercial robbers, and street robbers and is largest for domestic burglars. Other criminal career characteristics, such as age of onset, age of termination, duration, and specialisation, are also compared between offender groups.

J Dev Life Course Criminology 9, 379–403 (2023).

By Christine Acosta Weirich

In the aftermath of the Arab Spring in 2011, many nations in the Cradle of Civilization faced civil unrest, much of which continues today in the form of the ongoing Syrian Civil War, the conflict in Yemen, and instability in nations such as Iraq and Turkey. As a consequence, antiquities and cultural heritage in the region are currently facing a notoriously exacerbated level of risk. Despite the looting and destruction of cultural objects and monuments presenting a longstanding global and historical trend, the field of antiquities trafficking research lacks a unique and effective perspective within its current body of work and research. Likewise, criminology as a scientific field of study has largely overlooked the complex issue of looting and trafficking of cultural objects. This thesis focuses on the issue of Antiquities Trafficking Networks from a crime prevention perspective and attempts to demonstrate the effectiveness and apt nature of Crime Script Analysis and Situational Crime Prevention. This is accomplished first with a study and analysis of the wider phenomenon of Antiquities Trafficking Networks (from looting to market), followed by a specific case study of antiquities trafficked from within Syria since the beginning of the Civil War. Following these analyses, thirteen prominent Situational Crime Prevention strategies for Antiquities Trafficking Networks, and ten strategies for future conflict zones are generated by this research project. Through these strategies, Crime Script Analysis – in conjunction with Situational Crime Prevention – has proven to be a highly effective and efficient method and framework for studying this particularly difficult field. Ultimately, this thesis proposes a new crime prevention-focused methodology, to help tackle the issue of antiquities trafficking, as well as presenting one of the first prevention-specific analyses in this area. In doing so, it offers a basic model that maps the structure and necessary elements for antiquities trafficking to occur and allows for future research projects to adapt or customize this script model to situation-specific cases of antiquities looting, transit, and marketing.

Ph.D. Thesis. Glasgow: University of Glasgow, 2018. 312p.

By  Timothy Cubitt and Anthony Morgan

Risk assessment is a growing feature of law enforcement and an important strategy for identifying high-risk individuals, places and problems. Prediction models must be developed in a transparent way, using robust methods and the best available data. But attention must also be given to implementation. In practice, the data available to law enforcement from police information systems can be limited in their completeness, quality and accessibility. Prediction models need to be tested in as close to real-world settings as possible, including using less than optimal data, before they can be implemented and used. In this paper we replicate a prediction model that was developed in New South Wales to predict high-harm offending among outlaw motorcycle gangs nationally and in other states. We find that, even with a limited pool of data from a national police information system, high-harm offending can be predicted with a relatively high degree of accuracy. However, it was not possible to reproduce the same prediction accuracy achieved in the original model. Model accuracy varied between jurisdictions, as did the power of different predictive factors, highlighting the importance of considering context. There are trade-offs in real-world applications of prediction models and consideration needs to be given to what data can be readily accessed by law enforcement agencies to identify targets for prioritisation.

Canberra: Australian Institute of Criminology. 2024, 47pg