Critical Race Theory (CRT) has become a flashpoint of elite political discord, yet how Americans actually perceive CRT is unclear. We theorize that Republican elites utilized a strong framing strategy to re-define CRT as an “empty signifier” representing broader racial and cultural grievances. Using a survey and a pre-registered experiment among U.S. adults (N = 19,060), we find that this strategy worked. Republicans exhibit more familiarity with CRT and hold more negatively valenced (and wide ranging) sentiments toward CRT, relative to Democrats. Moreover, compared to teaching the legacy of racism in schools, Republicans are significantly more opposed to teaching CRT while Democrats express greater uncertainty. Our findings suggest that by framing CRT as a broad term that envelopes many grievances (including those beyond the scope of CRT), Republican elites have shaped a subset of Americans’ understanding of and attitudes toward CRT.

The rise and proliferation of International Commercial Courts has become a perceptible trend across the European and Asian continents over the past two decades. One such dispute resolution hub exists within the Astana International Financial Centre, a special jurisdiction within the Republic of Kazakhstan that operates on the basis of common law principles. The Astana International Financial Centre and its Court were modelled on the international financial centres of Dubai and Qatar; however, there are substantial differences between the legal systems of the Gulf States and that of the Republic of Kazakhstan. As a result, the creation of a new court has led to considerable criticism within the local legal community, raising serious doubts as to whether the Kazakh state should be maintaining and financing a ‘caviar-court’ instead of using resources to reform and develop the national judicial system. Nevertheless, despite the scepticism surrounding the financial centre, there is potential for the Astana International Financial Centre and its Court to become a regional dispute resolution hub for post-Soviet countries and the Central Asian region, following the example of Singapore and Dubai.

In their timely article, Andrew Little and Anne Meng make an important point. Despite widespread alarm over democratic backsliding, objective evidence suggests that the scale of the phenomenon is much more limited than many seem to think. Recent power holders around the world have not been entrenching themselves more effectively than in the past. Incumbents continue to lose elections about as often as they used to, and those who win have not been doing so by larger margins. Opposition parties are allowed to compete about as frequently today as 10 or 20 years ago. Moreover, there has been no increase in leaders’ ability to evade term limits.

This paper proposes a robust control approach to achieve high-precision trajectory tracking for permanent magnet linear motor (PMLM) system containing uncertainties by describing the dynamic model of PMLM based on the Udwadia-Kalaba equation combined with constraint-following method. First, the system of PMLM is described as a constraint-following system by adding the generalized constraint force to the unconstrained Udwadia-Kalaba equation of PMLM system. Second, the robust constraint-following controller is designed based on the proposed model after uncertainty analysis. Moreover, the proposed controller is verified to guarantee deterministic performance for uncertain systems: uniformly bounded and uniformly ultimately bounded. Third, the numerical simulation and experimental validation demonstrate the effectiveness of proposed controller. Finally, the design approach of constraint-following can be applied to other systems with uncertainties.

In a short, accessible book Linguistics: Why it Matters, Geoffrey Pullum, a leader in the field, offered an overview of what the study of linguistics is for the lay reader. In the penultimate chapter, titled ‘Machines that understand us’, Pullum (2018) set out to show what it would mean for computers to be able to use language like a human. He argued it would have to go beyond simple spoken or written word recognition and include processing of complex and novel structures. In this article, using ChatGPT, I revisit the tests that Pullum originally ran with Google and Microsoft Word, likewise for an audience curious about, but unfamiliar with, large language models.

In Standard Yiddish, -s and -ən are used as default allomorphs for plural word formation. It is argued here that the choice is left to the phonology, with -s acting as a default within a default. This status is used to explain the exclusive use of -s in the pluralization of proper names, which are claimed to be formed with no sensitivity to the phonological form of the base.

We present a unified approach to the processes of inversion and duality for quasilinear and $1$-quasilinear maps; in particular, for centralizers and differentials generated by interpolation methods.

This review aims to emphasise the impact of poor nutrition on children’s health and psychological well-being, urging those involved in childhood obesity or nutrition services to broaden their intervention approach. Poor nutrition and childhood obesity affect physical and psychological health. The stress of living with obesity further impacts quality of life, well-being and self-esteem. Children living with obesity may experience adverse childhood events and stress, and young people are able to recall the impact of psychosocial issues such as experiencing stigma and discrimination. Food is often a coping mechanism for managing negative emotions, perpetuating cycles of emotional coping and unhealthy eating behaviours. UK guidelines recommend family-based, multi-component weight management interventions for children living with obesity. Interventions mainly target health behaviours and utilise behaviour change techniques attempting to directly improve diet and physical activity as behavioural outcomes. Whilst these interventions may show some improvements in psychological well-being, there is limited consideration or understanding of the underlying mechanisms of action which indirectly influence engagement and the sustainability of the behaviour change. Lack of attention and inclusion of psychosocial variables in intervention implementation may help explain the variable effectiveness reported across childhood obesity interventions. In conclusion, enhancing the effectiveness of childhood obesity interventions requires a broader approach that fully incorporates psychosocial factors. Those responsible for commissioning, designing and implementing these interventions should adopt a holistic approach that addresses psychological and emotional needs while incorporating underlying mechanisms of action. This shift in focus could result in more sustainable and comprehensive treatment for childhood obesity.

The adjective χλωρός appears in the Septuagint to translate Hebrew terms that not only denote color, but state as well. In fact, in biblical Hebrew color is not a quality, but rather a “state” of the entities it describes. It is logical to wonder, then, whether it also expresses this in the Septuagint or if it denotes only color. To answer this question, it is necessary to carry out an interdisciplinary study of color and color language. The methodology followed will first study the concept of color in the Hellenistic world and in the Septuagint, as well as the cultural context in which the Septuagint translators lived. Subsequently, an approximate account of the “encyclopedic knowledge” that those translators possessed will be given, followed, finally, by a semantic analysis of χλωρός in the Septuagint. After applying this methodology, it will be shown that in the Septuagint, as in the Hellenistic world in general, natural color expresses both color and state, with color being the visual reflection of that state.

In recent years, scholars of global politics have shown that issues of race and white supremacy lie at the centre of international history, the birth of the field of International Relations, and contemporary theory. In this article, I argue that race plays an equally central role in the 21st century’s current and future crises: the set of systemic risks that includes intensifying climate change, deepening inequality, the endemic instabilities of capitalism, and migration. To make this argument, I describe the contours of the current crisis and show how racism amplifies its effects. In short, capitalism’s winners and losers and the effects of climate change fall along racial lines, amplifying both direct and indirect racial discrimination against non-white migrants and states in the Global South. These interdependent crises will shape the next 50 years of international politics and will likely perpetuate the vicious cycle of global racial inequality. Accordingly, this article presents a research agenda for all IR scholars to explore the empirical implications of race in the international system, integrate marginalised perspectives on global politics from the past and present into their scholarship, and address the most pressing political issues of the 21st century.

Simultaneous localization and mapping systems based on rigid scene assumptions cannot achieve reliable positioning and mapping in a complex environment with many moving objects. To solve this problem, this paper proposes a novel dynamic multi-object lidar odometry (MLO) system based on semantic object recognition technology. The proposed system enables the reliable localization of robots and semantic objects and the generation of long-term static maps in complex dynamic scenes. For ego-motion estimation, the proposed system extracts environmental features that take into account both semantic and geometric consistency constraints. Then, the filtered features can be robust to the semantic movable and unknown dynamic objects. In addition, we propose a new least-squares estimator that uses geometric object points and semantic box planes to realize the multi-object tracking (SGF-MOT) task robustly and precisely. In the mapping module, we implement dynamic semantic object detection using the absolute trajectory tracking list. By using static semantic objects and environmental features, the system eliminates accumulated localization errors and produces a purely static map. Experiments on the public KITTI dataset show that the proposed MLO system provides more accurate and robust object tracking performance and better real-time localization accuracy in complex scenes compared to existing technologies.