Islamophobia in the National Health Service: an ethnography of institutional racism in PREVENT's counter‐radicalisation policy

In 2015, the UK government made its counter‐radicalisation policy a statutory duty for all National Health Service (NHS) staff. Staff are now tasked to identify and report individuals they suspect may be vulnerable to radicalisation. Prevent training employs a combination of psychological and ideological frames to convey the meaning of radicalisation to healthcare staff, but studies have shown that the threat of terrorism is racialised as well. The guiding question of our ethnography is: how is counter‐radicalisation training understood and practiced by healthcare professionals? A frame analysis draws upon 2 years of ethnographic fieldwork, which includes participant observation in Prevent training and NHS staff interviews. This article demonstrates how Prevent engages in performative colour‐blindness – the active recognition and dismissal of the race frame which associates racialised Muslims with the threat of terrorism. It concludes with a discussion of institutional racism in the NHS – how racialised policies like Prevent impact the minutia of clinical interactions; how the pretence of a ‘post‐racial’ society obscures institutional racism; how psychologisation is integral to the performance of colour‐blindness; and why it is difficult to address the racism associated with colourblind policies which purport to address the threat of the Far‐Right

Keeping our mouths shut: the fear and racialized self-censorship of British healthcare professionals in PREVENT training

The PREVENT policy introduced a duty for British health professionals to identify and report patients they suspect may be vulnerable towards radicalisa- tion. Research on PREVENT’s impact in healthcare is scant, especially on the lived experiences of staff. This study examined individual interviews with 16 critical National Health Service (NHS) professionals who participated in mandatory PRE- VENT counter-radicalisation training, half of whom are Muslims. Results reveal two themes underlying the self-censorship healthcare staff. The first theme is fear, which critical NHS staff experienced as a result of the political and moral subscript underlying PREVENT training: the ‘good’ position is to accept the PREVENT duty, and the ‘bad’ position is to reject it. This fear is experienced more acutely by British Muslim healthcare staff. The second theme relates to the structures which extend beyond PREVENT but nonetheless contribute to self-censorship: distrustful settings in which the gaze of unknown colleagues stifles personal expression; reluctant trainers who admit PREVENT may be unethical but nonetheless relinquish responsibility from the act of training; and socio-political conditions affecting the NHS which overwhelm staff with other concerns. This paper argues that counter- terrorism within healthcare settings may reveal racist structures which dispropor- tionality impact British Muslims, and raises questions regarding freedom of conscience

Fourier transforms of Lipschitz functions on certain Lie groups

We study the order of magnitude of the Fourier transforms of certain Lipschitz functions on the special linear group of real matrices of order two

Weighted Mahalanobis Distance for Hyper-Ellipsoidal Clustering

Cluster analysis is widely used in many applications, ranging from image and speech coding to pattern recognition. A new method that uses the weighted Mahalanobis distance (WMD) via the covariance matrix of the individual clusters as the basis for grouping is presented in this thesis. In this algorithm, the Mahalanobis distance is used as a measure of similarity between the samples in each cluster. This thesis discusses some difficulties associated with using the Mahalanobis distance in clustering. The proposed method provides solutions to these problems. The new algorithm is an approximation to the well-known expectation maximization (EM) procedure used to find the maximum likelihood estimates in a Gaussian mixture model. Unlike the EM procedure, WMD eliminates the requirement of having initial parameters such as the cluster means and variances as it starts from the raw data set. Properties of the new clustering method are presented by examining the clustering quality for codebooks designed with the proposed method and competing methods on a variety of data sets. The competing methods are the Linde-Buzo-Gray (LBG) algorithm and the Fuzzy c-means (FCM) algorithm, both of them use the Euclidean distance. The neural network for hyperellipsoidal clustering (HEC) that uses the Mahalnobis distance is also studied and compared to the WMD method and the other techniques as well. The new method provides better results than the competing methods. Thus, this method becomes another useful tool for use in clustering

Prevent: what is pre-criminal space?

Prevent is a UK-wide programme within the government’s anti-terrorism strategy aimed at stopping individuals from supporting or taking part in terrorist activities. NHS England’s Prevent Training and Competencies Framework requires health professionals to understand the concept of pre-criminal space. This article examines pre-criminal space, a new term which refers to a period of time during which a person is referred to a specific Prevent-related safeguarding panel, Channel. It is unclear what the concept of pre-criminal space adds to the Prevent programme. The term should be either clarified or removed from the Framework

Controversial debates about workforce nationalisation: Perspectives from the Qatari higher education industry

Workforce nationalisation in the Gulf Corporation Council (GCC) countries is a crucial challenge for their development plans. The current study explores controversial debates about workforce nationalisation to understand the existing threats from the views of less examined key stakeholders, namely, educators and senior students. The study argues that the identified obstacles relate not only to policy flaws but also to the education – employability gap, phantom employment, and detrimental social and community perceptions. Given its exploratory nature, the study adopts a qualitative approach and uses 28 semi-structured interviews to identify critical obstacles to effective workforce nationalisation from human development, legal development, and socio-cultural perspectives. The findings contribute to the literature on GCC workforce nationalisation by unpacking educators’ and senior students’ views

Development of Gulf Cooperation Council human resources: an evidence-based review of workforce nationalization

Purpose – This study aimed to contribute to the field of Human Resource Management (HRM) by providing a critical review of existing scholarly research and a thematic analysis of the workforce nationalization domain in the Gulf Cooperation Council (GCC) countries. To strengthen the literature on this topic, it seeks to identify key gaps and areas for further exploration. Design/methodology/approach – A two-step systematic research methodology (qualitative and quantitative) and a thematic analysis of empirical and theoretical studies were used in this study. The quantitative review was conducted using a predesigned coding framework. Findings – The study identified and discussed four perspectives of workforce nationalization in the GCC countries. These were (1) the conceptualization of workforce nationalization; (2) the role of institutional policies in achieving it; (3) the practices and outcomes of nationalization efforts and (4) the impact of gender and women in the nationalization process. Research limitations/implications – This study has several limitations, which the authors have addressed by proposing several future research avenues. For example, the reviewed studies are skewed toward certain countries (e.g. UAE and Saudi Arabia), which limits the generalizability of their findings. Practical implications – A more comprehensive definition of nationalization, development of qualitative and quantitative measures to enhance HRM practices and outcomes, and the identification of alternative approaches to improve the employment of locals are emphasized as needs. Additionally, revised measures and mechanisms to rectify negative perceptions about entitlement and the revision of policies to integrate females in the national labor force are suggested. Originality/value – Workforce nationalization initiatives in the GCC region offer a unique and rich research phenomenon replete with managerial, organizational, economic and political dilemmas. The investigation of this phenomenon would profoundly enlighten employers, policymakers and scholars. Keywords GCC countries, Workforce nationalization, Localization, Human resource management Paper type Literature revie

The benefit of high-resolution operational weather forecasts for flash flood warning

International audienceIn Mediterranean Europe, flash flooding is one of the most devastating hazards in terms of human life loss and infrastructures. Over the last two decades, flash floods brought losses of a billion Euros of damage in France alone. One of the problems of flash floods is that warning times are very short, leaving typically only a few hours for civil protection services to act. This study investigates if operationally available shortrange numerical weather forecasts together with a rainfall-runoff model can be used as early indication for the occurrence of flash floods. One of the challenges in flash flood forecasting is that the watersheds are typically small and good observational networks of both rainfall and discharge are rare. Therefore, hydrological models are difficult to calibrate and the simulated river discharges cannot always be compared with ground "truth". The lack of observations in most flash flood prone basins, therefore, lead to develop a method where the excess of the simulated discharge above a critical threshold can provide the forecaster with an indication of potential flood hazard in the area with leadtimes of the order of the weather forecasts. This study is focused on the Cévennes-Vivarais region in the Southeast of the Massif Central in France, a region known for devastating flash floods. The critical aspects of using numerical weather forecasting for flash flood forecasting are being described together with a threshold – exceedance. As case study the severe flash flood event which took place on 8–9 September 2002 has been chosen. The short-range weather forecasts, from the Lokalmodell of the German national weather service, are driving the LISFLOOD model, a hybrid between conceptual and physically based rainfall-runoff model. Results of the study indicate that high resolution operational weather forecasting combined with a rainfall-runoff model could be useful to determine flash floods more than 24 hours in advance