Accurate reduced models of turbulence are desirable to facilitate the optimisation of magnetic-confinement fusion reactor designs. As a first step towards higher-dimensional turbulence applications, we use reservoir computing, a machine-learning (ML) architecture, to develop a closure model for a limiting case of electrostatic gyrokinetics. We implement a pseudo-spectral Eulerian code to solve the one-dimensional Vlasov–Poisson system on a basis of Fourier modes in configuration space and Hermite polynomials in velocity space. When cast onto the Hermite basis, the Vlasov equation becomes an infinitely coupled hierarchy of fluid moments, presenting a closure problem. We exploit the locality of interactions in the Hermite representation to introduce an ML closure model of the small-scale dynamics in velocity space. In the linear limit, when the kinetic Fourier–Hermite solver is augmented with the reservoir closure, the closure permits a reduction of the velocity resolution, with a relative error within 2 % for the Hermite moment where the reservoir closes the hierarchy. In the strongly nonlinear regime, the ML closure model more accurately resolves the low-order Fourier and Hermite spectra when compared with a naive closure by truncation and reduces the required velocity resolution by a factor of 16.

Recent voter turnout data has revealed a consistent and growing turnout gap between Black and White Americans since the 2012 Presidential election. Scholars have attributed this gap to an increase in restrictive voting laws. However, few have considered the decreased effectiveness of long-standing models of political behavior on Black voter turnout as the American political landscape has shifted. This note seeks to uncover patterns in recent Presidential elections that display a lack of effectiveness of prominent voter turnout models for Black Americans due to disparate socializing experiences in a post-Obama context like voter suppression and a global pandemic. It employs models previously used by Leighley and Vedlitz (1999) to evaluate and compare turnout models for Black and White individuals with mini-meta analysis. This paper utilizes the 2016 and 2020 Collaborative Multiracial Post-election Survey (CMPS) and the 2016 and 2020 American National Election Study to establish models and measure their impact on Black and White voter turnout. I find support that prominent turnout models behave differently in a post-Obama context like income, length of residence, group consciousness, and group threat while some models behave differently for Black and white voters like political interest and political efficacy. These findings assert that new turnout models need to be established to better understand the Black electorate in a post-Obama context.

Research has shown that the mental representations evoked by Dutch masculine pronouns, even when intended as generic, can be male-biased (Redl, 2021). Such bias can perpetuate gender inequalities in society (e.g., Stout & Dasgupta, 2011), prompting language users to seek more inclusive alternatives, such as gender-neutral pronouns. This study investigates the effect of Dutch gender-neutral pronouns as generic referential strategies on perceived text quality, and maps familiarity with and attitudes toward Dutch gender-neutral pronouns. The first experiment was conducted among a representative sample of Belgian participants, while the second experiment involved a mixed sample of Belgian and Dutch participants, thus facilitating a comparison between the two varieties of Dutch. The results show that gender-neutral pronouns do not affect text comprehensibility. However, the pronoun combination die-die-diens (subject-object-possessive) may impair text appreciation, even among young, highly educated participants familiar with gender-neutral pronouns. This study documents increasing familiarity with gender-neutral pronouns in Flanders and is the first to map familiarity in the Netherlands. Taking into account attitude measures, hen in subject position has little potential to be accepted, but the combination die-hen-hun does show potential. Additionally, our study suggests that plural forms are a viable gender-inclusive referential strategy for those who seek to avoid masculine generics.

This article investigates Berita Filem, one of the key Malay film magazines published in the 1960s, through the lens of minor fame: a form of temporary, localized celebrity status granted to aspiring actors, beauty pageant contestants, and other participants in the magazine’s interactive features. It charts some of the ways in which Berita Filem constructed fandom as a participatory endeavour, and how that participation was tied to ideas of modernity and Muslim belonging. Fan magazines were instructive in circulating images of stars, as well as forging a sense of collective culture for moviegoers before the advent of social media. While the last decade has witnessed a proliferation of historiographies centred on fan magazines and their content, both visual and textual, such studies remain largely limited to the Global North. In aiming to close this gap, this article examines three of Berita Filem’s regular columns, which took distinctive formats. ‘Our autograph column’ (Ruangan autograph kita) modelled itself after school yearbook pages, ‘Queen of Berita Filem’ (Ratu Berita Filem) was a beauty pageant, and ‘From heart to heart with Latifah Omar’ (Dari hati ke hati oleh Latifah Omar) was an advice column written by a movie star. At the core of this investigation is the question of historical readership at a time when Malaysia was a newly independent and rapidly changing nation.

This article examines how the International Labour Office (ILO) tried to disseminate one of its statistical tools, the International Standard Classification of Occupations (ISCO), in sub-Saharan Africa, in the context of decolonization and development planning. It sheds light on the changing relations in the late 1950s and early 1960s between the ILO, late colonial and then national administrations, and a regional organization, the Combined Commission for Technical Cooperation in Africa South of the Sahara (CCTA). Although characterized by rivalry, misunderstandings, and sometimes indifference, these relations were also marked by partially overlapping interests. Focusing on the successive ILO experts responsible for developing occupational classifications, this paper shows how their interactions with local actors reshaped the project which they had to carry out. For instance, it gave a greater place to the training of national civil servants or contributed to the realization of the 1962 Nigerian census. In particular, the article analyzes the connections made with other international programs (relating to demography and economic planning) on the ground, and the resulting interdependence among them. By doing so, the ILO expert responsible for the project on occupational classifications benefited from the resources of other technical assistance programs and tried to demonstrate to national authorities the importance of the project which could apply in various fields. While unexpected difficulties limited the scope of the initial project to Nigeria alone, the paper discusses how ILO officials inscribed occupational classifications in the general framework of development planning.

The Cape Town Convention is widely regarded as the most successful international convention in terms of ratifications. This essay aims to explore the fundamental reasons behind this success. While it is undeniable that the Cape Town Convention receives substantial industrial support in response to urgent market demands and the innovative protocols it established, this essay argues that this alone does not fundamentally explain its success.

Instead, the underlying reason lies in the Convention’s ability to avoid the trap of a false dichotomy – where one side seeks to convince the other to agree with its viewpoint. Rather, the key is to strive for a viable compromise that accommodates the perspectives of both, or even multiple stakeholders. This proposition will be illustrated by drawing on the social science concept of coordination, through a comparative analysis of the drafting processes of the Cape Town Convention and the Hague Securities Convention.

In this article, we develop a novel high-dimensional coefficient estimation procedure based on high-frequency data. Unlike usual high-dimensional regression procedures such as LASSO, we additionally handle the heavy-tailedness of high-frequency observations as well as time variations of coefficient processes. Specifically, we employ the Huber loss and a truncation scheme to handle heavy-tailed observations, while $\ell _{1}$-regularization is adopted to overcome the curse of dimensionality. To account for the time-varying coefficient, we estimate local coefficients which are biased due to the $\ell _{1}$-regularization. Thus, when estimating integrated coefficients, we propose a debiasing scheme to enjoy the law of large numbers property and employ a thresholding scheme to further accommodate the sparsity of the coefficients. We call this robust thresholding debiased LASSO (RED-LASSO) estimator. We show that the RED-LASSO estimator can achieve a near-optimal convergence rate. In the empirical study, we apply the RED-LASSO procedure to the high-dimensional integrated coefficient estimation using high-frequency trading data.