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Chapter 5 addresses the puzzle of reversing state size, which is inconsistent with a Tillyan account of European history. We argue that border-change processes triggered by ethnic nationalism are the main drivers of this development. While unification nationalism increased states’ size in the nineteenth century, its effects were dominated by secessionism, which shrinks states. Irredentism, in turn, had no effect on average state size. Focusing on deviations from the nation-state ideal, we postulate that internal ethnic fragmentation leads to secession and reductions in state sizes and that the cross-border presence of dominant ethnic groups makes state expansion through unification or irredentism more likely. Conducted at the systemic and state levels in Europe and globally, our analysis exploits information at the interstate dyadic level to capture these border-change processes. We find that while nationalism exerts both integrating and disintegrating effects on states’ territories, it is the latter effect that has dominated since the twentieth century.
This Reflection draws from an ongoing collaboration among the three authors, investigating mutual enlistment between the United States Department of Defense and research communities devoted to the advancement of the AI project. We are interested in the intersecting concerns and resonant sensibilities that draw us together – what we argue is the necessary starting point for interdisciplinary thinking – and in the differences that are the collaboration’s generative possibilities. Among the threads that join us are intersecting pathways between academic and commercial positionings within and against the AI project. Each of us has moved between locations in industry and the university, as researchers, practitioners, and students/faculty. Drawing on these experiences, we explore the possibilities that different positionings afford and what they preclude, how we have attempted to navigate these institutions within their frames of reference, and what has drawn us into relations beyond their putative boundaries. Based on Philip Agre’s call for a “critical technical practice” as a path towards more radical shifts in knowledge practices, we consider how we might weave together our biographical trajectories, disciplinary affiliations, political commitments, subjectivities, and skills into what Andrew Barry and Georgina Born name a more “auspicious interdisciplinarity”.
Fourier methods for the analysis are developed and used for the analysis of the kernel of Green’s operators, the causal fundamental solution and the kernel of the fermionic projector.
Transonic buffet presents time-dependent aerodynamic characteristics associated with shock, turbulent boundary layer and their interactions. Despite strong nonlinearities and a large degree of freedom, there exists a dominant dynamic pattern of a buffet cycle, suggesting the low dimensionality of transonic buffet phenomena. This study seeks a low-dimensional representation of transonic airfoil buffet at a high Reynolds number with machine learning. Wall-modelled large-eddy simulations of flow over the OAT15A supercritical airfoil at two Mach numbers, $M_\infty = 0.715$ and 0.730, respectively producing non-buffet and buffet conditions, at a chord-based Reynolds number of ${Re} = 3\times 10^6$ are performed to generate the present datasets. We find that the low-dimensional nature of transonic airfoil buffet can be extracted as a sole three-dimensional latent representation through lift-augmented autoencoder compression. The current low-order representation not only describes the shock movement but also captures the moment when the separation occurs near the trailing edge in a low-order manner. We further show that it is possible to perform sensor-based reconstruction through the present low-dimensional expression while identifying the sensitivity with respect to aerodynamic responses. The present model trained at ${Re} = 3\times 10^6$ is lastly evaluated at the level of a real aircraft operation of ${Re} = 3\times 10^7$, exhibiting that the phase dynamics of lift is reasonably estimated from sparse sensors. The current study may provide a foundation towards data-driven real-time analysis of transonic buffet conditions under aircraft operation.
The Hadamard expansion of the kernel of the fermionic projector is derived. The connection to the light-cone expansion and the wave front set is worked out.
We explore the mechanisms and regimes of mixing in yield-stress fluids by simulating the stirring of an infinite, two-dimensional domain filled with a Bingham fluid. A cylindrical stirrer moves along a circular path at constant speed, with the path radius fixed at twice the stirrer diameter; the domain is initially quiescent and marked by a passive dye in the lower half. We first examine the mixing process in Newtonian fluids, identifying three key mechanisms: interface stretching and folding around the stirrer’s path, diffusion across streamlines and dye advection and interface stretching due to vortex shedding. Introducing yield stress leads to notable mixing localisation, manifesting through three mechanisms: advection of vortices within a finite distance of the stirrer, vortex entrapment near the stirrer and complete suppression of vortex shedding at high yield stresses. Based on these mechanisms, we classify three distinct mixing regimes: (i) regime SE, where shed vortices escape the central region, (ii) regime ST, where shed vortices remain trapped near the stirrer and (iii) regime NS, where no vortex shedding occurs. These regimes are quantitatively distinguished through spectral analysis of energy oscillations, revealing transitions and the critical Bingham and Reynolds numbers. The transitions are captured through effective Reynolds numbers, supporting the hypothesis that mixing regime transitions in yield-stress fluids share fundamental characteristics with bluff-body flow dynamics. The findings provide a mechanistic framework for understanding and predicting mixing behaviours in yield-stress fluids, suggesting that the localisation mechanisms and mixing regimes observed here are archetypal for stirred-tank applications.
Adding temporal depth, Chapter 8 evaluates the influence of past golden ages on nationalist claims and conflict. It extends Chapter 7’s analysis of the nexus between nationalism and conflict by adding temporal depth and assessing whether restorative nationalism increases the risk of conflict. Taking nationalist narratives seriously, we study how the wish to restore past golden ages can be used to legitimize territorial claims and mobilize resources for action, as it did for the Polish nationalists who repeatedly rebelled against Russian occupation throughout the nineteenth century. The goal is to reconstruct plausible golden ages by combining ethnic settlement data with information on European state borders going back to 1100 CE. The analysis shows that the availability of a plausible golden age during which a group enjoyed political independence increases the risk of both domestic and interstate conflict. These findings suggest that specific historical legacies make some modern nationalisms more consequential than others, an interpretation that challenges radically modernist takes on nationalist mobilization.
Chapter 2 introduces the main theoretical framework as well as the core concepts supporting the empirical analyses. It starts by outlining our response to the four weaknesses of the nationalism literature, followed by a depiction of the causal scheme that constitutes the analytical core of the book. The chapter also discusses key causal mechanisms supporting this framework before turning to alternative explanations and extensions to the scheme.
Evolutionary theory and especially evolutionary psychology have been recruited to explain and justify women’s constrained social roles and the restrictions historically placed upon them in mass societies. This chapter, on scientific grounds, challenges three myths allegedly emerging from empirical research: the myth of female intellectual inferiority, the myth of female domesticity, and the myth of female natural monogamy. While there are anatomical, physiological, and psychological differences between men and women, reflecting their different reproductive strategies, the overuse of the principle of comparative advantage has resulted in the subjection and exploitation of women in nearly all known societies.
This research introduces an adapted multidimensional fractional optimal control problem, developed from a newly established framework that combines first-order partial differential equations (PDEs) with inequality constraints. We methodically establish and demonstrate the optimality conditions relevant to this framework. Moreover, we illustrate that, under certain generalized convexity assumptions, there exists a correspondence between the optimal solution of the multidimensional fractional optimal control problem and a saddle point related to the Lagrange functional of the revised formulation. To emphasize the significance and practical implications of our findings, we present several illustrative examples.
This chapter reflects on how international organizations may affect the legal position of non-members – and the international legal system more generally – by imposing or exporting norms. It considers the aspiration latent in universal international organizations to bend the outside world to their will, looking at examples from the practice of the UN Security Council and the International Criminal Court. It then turns to the practice of the OECD and the EU to examine some of the ways in which regional international organizations may export norms to non-members through international cooperation and unilateral action, and some of the normative concerns that this form of engagement raises.
With ambitious action required to achieve global climate mitigation goals, climate change has become increasingly salient in the political arena. This article presents a dataset of climate change salience in 1,792 political manifestos of 620 political parties across different party families in forty-five OECD, European, and South American countries from 1990 to 2022. Importantly, our measure uniquely isolates climate change salience, avoiding the conflation with general environmental and sustainability content found in other work. Exploiting recent advances in supervised machine learning, we developed the dataset by fine-tuning a pre-trained multilingual transformer with human coding, employing a resource-efficient and replicable pipeline for multilingual text classification that can serve as a template for similar tasks. The dataset unlocks new avenues of research on the political discourse of climate change, on the role of parties in climate policy making, and on the political economy of climate change. We make the model and the dataset available to the research community.
A functional analytic method is developed, which gives rise to a canonical decomposition of the Dirac solution space into two subspaces, even in a time-dependent situation.