“Heave Half a Brick at Him”: Hate Crimes and Discrimination against Muslim Converts in Late Victorian Liverpool

Throughout the existence of the Liverpool Moslem Institute, 1887–1908, there were many incidents of discrimination, intimidation, violence, and other acts of hate directed toward the British converts to Islam. This was particularly evident during the first decade after the group’s founding. The band of Muslims, led by Sheik Abdullah William Henry Quilliam, faced continued opposition, be it disruptions of events and religious services, or violent street fighting. This article explores the incidents of hate and discrimination, the milieu in which they occurred, and the reaction of the Muslim community. A brief comparison to the experience of the contemporaneous American Muslim converts also is presented.     

Muslims’ social inclusion and exclusion in France,Québec,and Canada: does national context matter?*

This article compares the social experiences of Muslim minorities in three contexts – France, Québec, and English Canada – each reflecting a different approach to immigrant integration. France’s republican model emphasises cultural assimilation and the exclusion of religion from the public sphere; Canada’s multicultural model advocates official recognition of minority cultures; Québec shares Canada’s tradition of large-scale permanent immigration but embodies a unique intercultural discourse of integration, in some ways resembling France. We compare the social experiences of Muslim and non-Muslim minorities in these three settings using the French ‘Trajectories and Origins’ survey (2009) and the Canadian ‘Ethnic Diversity Survey’ (2002) data on reports of discrimination, friendship networks, social trust, voluntarism, and national identity. We find the Muslim/non-Muslim gap in social inclusion is significant in all three settings and results from ethnic, cultural, or racial differences, more than religion. In assessing immigrants’ social inclusion, we suggest consideration be given to: (i) the reality of ‘national models’ in the community, (ii) a tendency for minorities to locate in more accepting segments of mainstream society, and (iii) the limited impact of policies based on national models.     

A Blueprint for Full Collective Flood Risk Estimation: Demonstration for European River Flooding

Floods are a natural hazard evolving in space and time according to meteorological and river basin dynamics, so that a single flood event can affect different regions over the event duration. This physical mechanism introduces spatio‐temporal relationships between flood records and losses at different locations over a given time window that should be taken into account for an effective assessment of the collective flood risk. However, since extreme floods are rare events, the limited number of historical records usually prevents a reliable frequency analysis. To overcome this limit, we move from the analysis of extreme events to the modeling of continuous stream flow records preserving spatio‐temporal correlation structures of the entire process, and making a more efficient use of the information provided by continuous flow records. The approach is based on the dynamic copula framework, which allows for splitting the modeling of spatio‐temporal properties by coupling suitable time series models accounting for temporal dynamics, and multivariate distributions describing spatial dependence. The model is applied to 490 stream flow sequences recorded across 10 of the largest river basins in central and eastern Europe (Danube, Rhine, Elbe, Oder, Waser, Meuse, Rhone, Seine, Loire, and Garonne). Using available proxy data to quantify local flood exposure and vulnerability, we show that the temporal dependence exerts a key role in reproducing interannual persistence, and thus magnitude and frequency of annual proxy flood losses aggregated at a basin‐wide scale, while copulas allow the preservation of the spatial dependence of losses at weekly and annual time scales.     

Data-driven operations management: organisational implications of the digital transformation in industrial practice

Abstract

The ongoing digital transformation on industry has so far mostly been studied from the perspective of cyber-physical systems solutions as drivers of change. In this paper, we turn the focus to the changes in data management resulting from the introduction of new digital technologies in industry. So far, data processing activities in operations management have usually been organised according to the existing business structures inside and in-between companies. With increasing importance of Big Data in the context of the digital transformation, the opposite will be the case: business structures will evolve based on the potential to develop value streams offered on the basis of new data processing solutions. Based on a review of the extant literature, we identify the general different fields of action for operations management related to data processing. In particular, we explore the impact of Big Data on industrial operations and its organisational implications.     

An integrative model of leadership behavior

Decades of questionnaire and interview studies have revealed various leadership behaviors observed in successful leaders. However, little is known about the actual behaviors that cause those observations. Given that lay observers are prone to cognitive biases, such as the halo effect, the validity of theories that are exclusively based on observed behaviors is questionable. We thus follow the call of leading scientists in the field and derive a parsimonious model of leadership behavior that is informed by established psychological theories. Building on the taxonomy of Yukl (2012), we propose three task-oriented behavior categories (enhancing understanding, strengthening motivation and facilitating implementation) and three relation-oriented behavior categories (fostering coordination, promoting cooperation and activating resources), each of which is further specified by a number of distinct behaviors. While the task-oriented behaviors are directed towards the accomplishment of shared objectives, the relation-oriented behaviors support this process by increasing the coordinated engagement of the team members. Our model contributes to the advancement of leadership behavior theory by (1) consolidating current taxonomies, (2) sharpening behavioral concepts of leadership behavior, (3) specifying precise relationships between those categories and (4) spurring new hypotheses that can be derived from existing findings in the field of psychology. To test our model as well as the hypotheses derived from this model, we advocate the development of new measurements that overcome the limitations associated with questionnaire and interview studies.     

Generating a smallest binary tree by proper selection of the longest edges to bisect in a unit simplex refinement

In several areas like global optimization using branch-and-bound methods for mixture design, the unit n-simplex is refined by longest edge bisection (LEB). This process provides a binary search tree. For \(n>2\), simplices appearing during the refinement process can have more than one longest edge (LE). The size of the resulting binary tree depends on the specific sequence of bisected longest edges. The questions are how to calculate the size of one of the smallest binary trees generated by LEB and how to find the corresponding sequence of LEs to bisect, which can be represented by a set of LE indices. Algorithms answering these questions are presented here. We focus on sets of LE indices that are repeated at a level of the binary tree. A set of LEs was presented in Aparicio et al. (Informatica 26(1):17–32, 2015), for \(n=3\). An additional question is whether this set is the best one under the so-called \(m_k\)-valid condition.     

$$D_s$$-optimality in copula models

Optimum experimental design theory has recently been extended for parameter estimation in copula models. The use of these models allows one to gain in flexibility by considering the model parameter set split into marginal and dependence parameters. However, this separation also leads to the natural issue of estimating only a subset of all model parameters. In this work, we treat this problem with the application of the \(D_s\)-optimality to copula models. First, we provide an extension of the corresponding equivalence theory. Then, we analyze a wide range of flexible copula models to highlight the usefulness of \(D_s\)-optimality in many possible scenarios. Finally, we discuss how the usage of the introduced design criterion also relates to the more general issue of copula selection and optimal design for model discrimination.     

Control‐based imputation for sensitivity analyses in informative censoring for recurrent event data

In clinical trials, missing data commonly arise through nonadherence to the randomized treatment or to study procedure. For trials in which recurrent event endpoints are of interests, conventional analyses using the proportional intensity model or the count model assume that the data are missing at random, which cannot be tested using the observed data alone. Thus, sensitivity analyses are recommended. We implement the control‐based multiple imputation as sensitivity analyses for the recurrent event data. We model the recurrent event using a piecewise exponential proportional intensity model with frailty and sample the parameters from the posterior distribution. We impute the number of events after dropped out and correct the variance estimation using a bootstrap procedure. We apply the method to an application of sitagliptin study.     

(Sub) Optimality and (non) optimal satisficing in risky decision experiments

We implement a risky choice experiment based on one-dimensional choice variables and risk neutrality induced via binary lottery incentives. Each participant confronts many parameter constellations with varying optimal payoffs. We assess (sub)optimality, as well as (non)optimal satisficing by eliciting aspirations in addition to choices. Treatments differ in the probability that a binary random event, which are payoff—but not optimal choice—relevant is experimentally induced and whether participants choose portfolios directly or via satisficing, i.e., by forming aspirations and checking for satisficing before making their choice. By incentivizing aspiration formation, we can test satisficing, and in cases of satisficing, determine whether it is optimal.