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The purpose of this paper is to outline the process of risk assessment for terrorists and violent political extremists and to present an example of such an approach. The approach proposed is referred to as the VERA 2 or violent extremism risk assessment protocol (Consultative Version 2).

A review of the knowledge base relating to risk assessment and risk assessment methodology was undertaken with a focus on relevance to individual terrorists and violent extremists. The need for a specific approach for the risk assessment of terrorists that differs from approaches used for ordinary violent criminals was identified. A model that could be used for the risk assessment of terrorists was identified with pertinent risk indicators. This was structured into a protocol referred to as the VERA (Consultative Version 2). The approach is intended to be applied to different types of violent extremists, terrorists and unlawful violent offenders motivated by religious, political or social ideologies.

First, risk assessments of adjudicated terrorists and violent extremists should be undertaken with risk indicators that are relevant to ideological motivated violence. Indicators used for ordinary common violence differ in substantive ways from those relevant to terrorists and therefore may have questionable relevance for the assessment of risk in terrorists. Second, it is possible to construct an evidence‐based risk assessment approach for the range of violent extremists and terrorists using a structured professional judgment approach with pertinent risk indicators. The VERA 2 is an example of this type of risk assessment protocol for terrorists and unlawful violent extremists.

Risk assessment tools that have been developed for ordinary violent criminals and members of organised criminal gangs should be used with caution with terrorists, violent extremists and other perpetrators of ideologically motivated unlawful violence. Specific risk assessment approaches for terrorists with relevant indicators should be used. At this time, terrorist oriented approaches such as the VERA 2 are to be considered consultative and used as an add‐on to other established approaches.

There are few transparent, structured risk assessment approaches that use indicators specifically relevant to violent political extremists and terrorists. One new approach, the VERA 2 is outlined in the paper using risk indicators that differ in substantive ways from those used for other ordinary violent criminals.

The purpose of this paper is to consider historical shifts in the mobilisation of the concept of radical in relation to Australian schooling.

Two texts composed at two distinct points in a 40-year period in Australia relating to radicalism and education are strategically juxtaposed. These texts are: the first issue of the Radical Education Dossier (RED, 1976), and the Attorney General Department’s publication Preventing Violent Extremism and Radicalisation in Australia (PVERA, 2015). The analysis of the term radical in these texts is influenced by Raymond Williams’s examination of particular keywords in their historical and contemporary contexts.

Across these two texts, radical is deployed as adjective for a process of interrogating structured inequalities of the economy and employment, and as individualised noun attached to the “vulnerable” young person.

Reading the first issue of RED alongside the PVERA text suggests the consequences of the reconstitution of the role of schools, teachers and the re-positioning of certain young people as “vulnerable”. The juxtaposition of these two texts surfaces contemporary patterns of the therapeutisation of political concerns.

A methodological contribution is offered to historical sociological analyses of shifts and continuities of the role of the school in relation to society.

The purpose of this paper is to cut through the rhetoric that shrouds Russia's anti‐money laundering regime to uncover the reality that lies beneath.

This paper relies on both primary and secondary sources in Russian and English that deal with the problems of money laundering in the Russian context. Relevant sections of the Russian Criminal Code as well as Russia's anti‐money laundering regulations have been consulted.

Overall, the Russian anti‐money laundering regime has thus far proved ineffective in terms of meeting its stated purposes of combating organized crime and terrorism. Its limited success stems largely from structural weaknesses in the Russian banking system as well as that industry's lack of a culture of regulatory compliance. Moreover, Russian authorities have opportunistically seized on the current anti‐money laundering regime as a useful tool in the pursuit of ends unconnected to the fight against organized crime and terrorism. The Russian authorities have used the regime to attempt to reform the banking system and to extend their strategic control in the domestic political and business realms. The ineffectiveness of the anti‐money laundering regulations and their usage to achieve ulterior aims undermine the legitimacy of the regime as a whole.

The paper looks beyond the technical difficulties in applying the anti‐money laundering regulations and examines the misuses of the anti‐money laundering regime in the Russian context. However, the problems raised in the paper are not unique to Russia and have relevance to other jurisdictions, especially countries that are members of the Financial Action Task Force.

The present paper provides an educational status related to instructional days at elementary level in the districts identified as focus districts of left-wing extremism (LWE). The focus districts are those which have high intensity and presence of LWE. Educational development is not only influenced by the LWE, but many others, such as socio-economic, political and cultural, etc. Accordingly no direct correlations can be drawn between low educational development or otherwise with the influence of LWE. However, instructional days in school is an important physical indicator on school functioning.

The research is based on the secondary analysis of District Information System for Education (DISE) data, which provides comprehensive information of school-based indicators, facility indicators, enrollment based indicators and teacher-related indicators for every year. The DISE data relating to number of instructional days for the years 2005-2006 to 2009-2010 is studied among the districts identified as LWE districts. For the purpose of analysis, the number of days is classified into seven categories, and the schools functioning at district level is analyzed.

Education is critical in the LWE districts, which are areas with low literacy, large percentage of rural and backward sections of population. It was found that though there is an apparent improvement in the schools functioning, still number of schools fell under the category low/non-functional schools. In two out of five years, other districts had significantly lower average instructional days than focus districts. Hence, in terms of instructional days the situation is not all that bad.

The study is based on the secondary analysis of the DISE data. A large data related to number of students goes unaccounted and unregistered. The data is analyzed on mean instructional days at district level. Further down at sub-district and village level could provide a much more realistic picture.

The research paper analyzes the number of instructional days, which is an indicator that provides the basic empirical information related to schools functioning. Before policy makers can think of quality, it is pertinent to know whether the schools are working for the number of days that they are expected to. As of now hardly any study has taken place to provide information on the LWE districts in relation to elementary education.

This paper aims to present a case study analysing the reintegration programs of Malaysian violent extremist detainees and prisoners. It explores the ongoing challenges faced by these individuals as they strive to reintegrate and assimilate into society.

Qualitative data was collected through interviews with 12 violent extremist detainees and prisoners who had successfully reintegrated into society. The life course perspective was used as the analytical framework, and data analysis was conducted using ATLAS.ti.

The study revealed common challenges faced by the participants in gaining societal acceptance, dealing with stigma and achieving economic stability. The results also highlighted the difficulties of sustaining livelihoods due to heightened vigilance in the surrounding environment.

These findings enhance the understanding of factors influencing successful reintegration of people who were involved in violent extremism into mainstream society.

Government bodies, agencies or organisations and non-governmental organisations can implement these successful factors to prevent any issues of recidivism or resentment towards society.

This research contributes unique insights based on data from individuals who have undergone successful or partial successful reintegration. Detailed academic sharing of such information from a Southeast Asian country such as Malaysia is relatively scarce, given the specific procedures required for accessing such data.

The purpose of this paper is to provide a metric for validating the Nationwide Suspicious Activity Reporting (SAR) Initiative’s (NSI) sixteen-category instrument, which is designed to guide law enforcement in the collection and analysis of suspicious behaviors preceding serious crimes, including terrorist attacks.

Data on suspicious preoperational activities and terrorism incident outcomes in the USA between 1972 and 2013 come from the American Terrorism Study (ATS). Using a mixed-method approach, the authors conduct descriptive and multivariate analyses to examine the frequencies of the least and most prevalent suspicious activities (or SAR indicators) and how they predict the likelihood of terrorism prevention. In addition, the authors contextualize how configurations of SAR indicators are associated with the successful thwarting of terrorism incidents by law enforcement using an analytical method known as conjunctive analysis of case configurations (CACC).

The study reveals several key findings. First, certain behaviors categorized as suspicious, such as making threats, occur more frequently than others. Second, making threats, conducting surveillance and terrorist recruitment/financing predict law enforcement interdiction in terrorism plots, while misrepresentation (or the manufacturing and use of false documents) is more associated with terrorist success. Third, prevalent SAR indicators operate differently in the context of various combinations of suspicious activities to shape the likelihood for law enforcement interdiction.

The current study’s findings may not be generalizable to other forms of violent extremism and terrorism outside of the USA.

This study illuminates opportunities for the NSI to provide law enforcement with the necessary tools to reduce terrorism risk and prevent future attacks.

To our knowledge, no scholarly work to date has assessed how observable behavioral indicators of suspicious preoperational activities affect the outcomes of terrorist plots.

The purpose of this paper is to analyse the new Russian law on Money laundering. Globalisation has turned the international financial systems into a paradise for money launderers. As much as globalisation has expanded opportunities. The purpose of this paper is to analyse the new Russian law on money laundering which brought some changes to the existing system was introduced in Russia in 2002. Even though it has improved the regulation on money laundering greatly, it has failed to efficiently combat terrorism. Overall, the Russian anti-money laundering regime has proved ineffective in terms of meeting its stated purposes of combating organised crime and terrorism. The limited success of the Russian anti-money laundering law stems largely from the fact that Russian banking system is structurally weak.

This paper analyses the problems through literature review. Also, the problem will be looked at from an international law perspective, explaining why Russian efforts will not be efficient as long as no consensus is reached at international level.

This paper starts from the premise that Russian made great effort to comply with international recommendations but that its law fails to efficiently deal with terrorism finance partly due to the fact that no consensus exists at international level as to the definition of the terrorism. Furthermore, the doubt persists as to the real aim pursued by Russian Government while enacting the money laundering law.

Few papers have been published about money laundering in Russia, but none of them look at the problem of the lack of definition of terrorism at international level to explain the deficiencies of the system in place.

The purpose of this paper is to discuss the design, application and findings of a case study in which the application of a machine learning algorithm is utilised to identify the grievances in Twitter in an Arabian context.

To understand the characteristics of the Twitter users who expressed the identified grievances, data mining techniques and social network analysis were utilised. The study extracted a total of 23,363 tweets and these were stored as a data set. The machine learning algorithm applied to this data set was followed by utilising a data mining process to explore the characteristics of the Twitter feed users. The network of the users was mapped and the individual level of interactivity and network density were calculated.

The machine learning algorithm revealed 12 themes all of which were underpinned by the coalition of Arab countries blockade of Qatar. The data mining analysis revealed that the tweets could be clustered in three clusters, the main cluster included users with a large number of followers and friends but who did not mention other users in their tweets. The social network analysis revealed that whilst a large proportion of users engaged in direct messages with others, the network ties between them were not registered as strong.

Borum (2011) notes that invoking grievances is the first step in the radicalisation process. It is hoped that by understanding these grievances, the study will shed light on what radical groups could invoke to win the sympathy of aggrieved people.

In combination, the machine learning algorithm offered insights into the grievances expressed within the tweets in an Arabian context. The data mining and the social network analyses revealed the characteristics of the Twitter users highlighting identifying and managing early intervention of radicalisation.

Drawing on Shakespeare, and in particular Hamlet's psychological crisis, this paper examines the relationship between emotions and meaning, a key theme in artistic work since Aristotle but, it is argued, largely ignored in psychology and the social sciences. Now, however, against a background of international terrorism, lessons are being learned from literature's insights.