Exploring the intersection of transnationalism and critical race theory: a critical race analysis of international student experiences in the United States

International student mobility to the United States (US) has increased over the past two decades. Despite the increase in numbers, international students may experience racism, nativism, and other forms of discrimination within the US context. Much of the existing literature focus on how international students can assimilate and cope with these issues rather than interrogating the systems of oppression that create negative student experiences. Thus, we utilized critical race theory (CRT) as a framework for interrogating how international student experiences are portrayed in current literature. Although CRT is grounded in US-based legal theory, we argue that CRT must move beyond the rigid confinement within US borders and expand to consider how transnationalism and global exchange contributes to the fluidity and applicability of this theory. We also provide recommendations for critical race praxis, with an emphasis on implications for practice, theory, and future research.     

An audit of received international business corruption literature for logic,consistency, completeness of coverage

This analysis of International Business (IB) corruption literature identifies gaps and inconsistencies in how corruption is perceived or deliberated in top academic journals. The reviewed articles tend to focus on one of the three key themes of IB corruption (Contributing factors, Consequences, and Combating) and are categorised into the six sub-domains of the IB framework. The content of the articles is categorised into the respective themes and discussed in relation to underpinning theories and key constructs. The process is intended to be less a synthesis of the literature than an audit revealing that IB corruption research is weakened by tendencies to: 1) Be siloed within its subtheme and to not cross-tie to work in other key themes—this issue is very severe in the Combating theme; 2) Have a short-term focus that disregards the cumulative effects of total graft, and; 3) Asymmetrically focus (predominantly) on the supply side of corruption. These finding suggest several avenues for further research.     

Islamophobia and the Problematization of Mosques: A Critical Exploration of Hate Crimes and the Symbolic Function of “Old” and “New” Mosques in the United Kingdom

Most scholarly studies have tended to focus on the building of new and proposed mosques, and in particular how they are sites of conflict and contestation symbolic of wider “problems” associated with Muslims and Islam in the United Kingdom. This study focuses on an overlooked aspect within this, the extent to which attacks on mosques that are neither new nor proposed perform a similar symbolic function. Presenting new empirical evidence from research undertaken with ten mosques across the United Kingdom that had been targeted for attack, we begin by exploring the existing literature on the problematization of mosques using the lens of critical Islamophobia studies to do so. Setting out what is known about attacks on mosques in the British setting, empirical findings from the research are used to illustrate the type and manifestation of attacks experienced, going on to consider the drivers and catalysts for them. Exploring the similarities and differences between the conflict and contestation associated with new mosques and the attacks on mosques that are not new, this study concludes that some resonance exists in the symbolic function mosques continue to serve in the community. In conclusion, the significant resonance between Islamophobically motivated attacks against mosques with those against the individuals is considered.     

Integrating Behavioral Science with Human Factors to Address Process Safety

ABSTRACT

Applying the science of human factors to eliminate error across all aspects of process design, management, operation, and maintenance has been a focus in the process safety area for many years. Human error has been attributed as a major cause of many high profile catastrophic accidents around the world. These accidents have resulted in national and international attention, which has led to a focus on improving organizational capabilities, systems, and in many cases, governmental regulations around human factors. This article provides a review of the field of human factors highlighting various topics in the literature, and introduces governmental regulatory bodies currently engaging organizations in a scientific approach to human factors. Finally, the need for integrating behavioral science methodologies with human factors is addressed. This is done with specific focus on how Organizational Behavior Management methodologies can work in concert with human factors to optimize process safety.     

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.     

A heuristic for the time constrained asymmetric linear sum assignment problem

The linear sum assignment problem is a fundamental combinatorial optimisation problem and can be broadly defined as: given an \(n \times m, m \ge n\) benefit matrix \(B = (b_{ij})\), matching each row to a different column so that the sum of entries at the row-column intersections is maximised. This paper describes the application of a new fast heuristic algorithm, Asymmetric Greedy Search, to the asymmetric version (\(n \ne m\)) of the linear sum assignment problem. Extensive computational experiments, using a range of model graphs demonstrate the effectiveness of the algorithm. The heuristic was also incorporated within an algorithm for the non-sequential protein structure matching problem where non-sequential alignment between two proteins, normally of different numbers of amino acids, needs to be maximised.     

On the Assessment of Monte Carlo Error in Simulation-Based Statistical Analyses

Statistical experiments, more commonly referred to as Monte Carlo or simulation studies, are used to study the behavior of statistical methods and measures under controlled situations. Whereas recent computing and methodological advances have permitted increased efficiency in the simulation process, known as variance reduction, such experiments remain limited by their finite nature and hence are subject to uncertainty; when a simulation is run more than once, different results are obtained. However, virtually no emphasis has been placed on reporting the uncertainty, referred to here as Monte Carlo error, associated with simulation results in the published literature, or on justifying the number of replications used. These deserve broader consideration. Here we present a series of simple and practical methods for estimating Monte Carlo error as well as determining the number of replications required to achieve a desired level of accuracy. The issues and methods are demonstrated with two simple examples, one evaluating operating characteristics of the maximum likelihood estimator for the parameters in logistic regression and the other in the context of using the bootstrap to obtain 95% confidence intervals. The results suggest that in many settings, Monte Carlo error may be more substantial than traditionally thought.     

Using Bayesian graphical models to model biases in observational studies and to combine multiple sources of data: application to low birth weight and water disinfection by-products

Summary.  Data in the social, behavioural and health sciences frequently come from observational studies instead of controlled experiments. In addition to random errors, observational data typically contain additional sources of uncertainty such as missing values, unmeasured confounders and selection biases. Also, the research question is often different from that which a particular source of data was designed to answer, and so not all relevant variables are measured. As a result, multiple sources of data are often necessary to identify the biases and to inform about different aspects of the research question. Bayesian graphical models provide a coherent way to connect a series of local submodels, based on different data sets, into a global unified analysis. We present a unified modelling framework that will account for multiple biases simultaneously and give more accurate parameter estimates than standard approaches. We illustrate our approach by analysing data from a study of water disinfection by-products and adverse birth outcomes in the UK.     

The Orthodox Church in revolutionary Cheliabinsk: reform,counter-reform,and popular revolution in 1917

In 1917 the Cheliabinsk Vicariate, like the Church in most areas in the Russian empire, declined to support the autocracy, welcomed the February Revolution, endorsed the Provisional Government, and envisioned a broad set of reforms that even included a greater role for the laity in Church governance. The key agent for reform in Cheliabinsk – as in other dioceses – was the Assembly of Clergy and Laity, the focus of this study. Although the Assembly did adopt a radical and ostensibly popular social and administrative program, the vicariate encountered growing lay disenchantment – because of its support for an unpopular war, because of a caveat deferring social reform, but also because of the Church’s reluctance to give parishioners full power over the parish. The intensifying crises of 1917 heightened expectations for reform, and the disintegration of authority in Cheliabinsk and within the Church itself widened the chasm between the Church and parishioners. In response, diocesan authorities supported conservative measures, which deferred reform, in an attempt to re-establish order, while parishioners – frustrated by the pace of reform and the Church’s wavering support of it – led a revolution against diocesan authority aimed at making the Church subservient to their own agendas.