This paper explores the transformative potential of artificial intelligence (AI), particularly generative AI (GenAI), in supporting the teaching, learning, and assessment of second language (L2) listening and speaking. It examines how AI technologies, such as spoken dialogue systems and intelligent personal assistants, can refine existing practices, offer innovative solutions, and address challenges related to spoken language competencies, as well as drawbacks they present. It highlights the role of GenAI, explores its capabilities and limitations, and offers insights into the evolving role of GenAI in language education. This paper discusses actionable insights for educators and researchers, outlining practical considerations and future research directions for optimizing GenAI integration in the learning and assessment of listening and speaking.

Past research alerts to the increasingly unpleasant climate surrounding public debate on social media. Female politicians, in particular, are reporting serious attacks targeted at them. Yet, research offers inconclusive insights regarding the gender gap in online incivility. This paper aims to address this gap by comparing politicians with varying levels of prominence and public status in different institutional contexts. Using a machine learning approach for analyzing over 23 million tweets addressed to politicians in Germany, Spain, the United Kingdom, and the United States, we find little consistent evidence of a gender gap in the proportion of incivility. However, more prominent politicians are considerably and consistently more likely than others to receive uncivil attacks. While prominence influences US male and female politicians’ probability to receive uncivil tweets the same way, women in our European sample receive incivility regardless of their status. Most importantly, the incivility varies in quality and across contexts, with women, especially in more plurality contexts, receiving more identity-based attacks than other politicians.

Exchangeable partitions of the integers and their corresponding mass partitions on $\mathcal{P}_{\infty} = \{\mathbf{s} = (s_{1},s_{2},\ldots)\colon s_{1} \geq s_{2} \geq \cdots \geq 0$ and $\sum_{k=1}^{\infty}s_{k} = 1\}$ play a vital role in combinatorial stochastic processes and their applications. In this work, we continue our focus on the class of Gibbs partitions of the integers and the corresponding stable Poisson–Kingman-distributed mass partitions generated by the normalized jumps of a stable subordinator with an index $\alpha \in (0,1)$, subject to further mixing. This remarkable class of infinitely exchangeable random partitions is characterized by probabilities that have Gibbs (product) form. These partitions have practical applications in combinatorial stochastic processes, random tree/graph growth models, and Bayesian statistics. The most notable class consists of random partitions generated from the two-parameter Poisson–Dirichlet distribution $\mathrm{PD}(\alpha,\theta)$. While the utility of Gibbs partitions is recognized, there is limited understanding of the broader class. Here, as a continuation of our work, we address this gap by extending the dual coagulation/fragmentation results of Pitman (1999), developed for the Poisson–Dirichlet family, to all Gibbs models and their corresponding Poisson–Kingman mass partitions, creating nested families of Gibbs partitions and mass partitions. We focus primarily on fragmentation operations, identifying which classes correspond to these operations and providing significant calculations for the resulting Gibbs partitions. Furthermore, for completion, we provide definitive results for dual coagulation operations using dependent processes. We demonstrate the applicability of our results by establishing new findings for Brownian excursion partitions, Mittag-Leffler, and size-biased generalized gamma models.

Take two positions, both of which we take to be popular ways of thinking about law. First, some norm N is part of the law only if, and in virtue of, N being ultimately recognized or validated by the rule of recognition. Call this Hartian Orthodoxy. Second, statements about legal rights are best understood as claims about the existence of moral rights according to law. Call this legal perspectivalism. Here we show that the two are incompatible. Our argument is that, to account for certain arguments that mix legal and factual claims, perspectivalism must close the legal perspective according to some inference rule. As it happens, however, the only defensible candidates render perspectivalism incompatible with Hartian Orthodoxy.

Only months after starting as KPFA’s music director, Charles Amirkhanian launched the radio show Ode to Gravity in March 1970. The evocative name referred to his 1968 experimental theatre piece that involved dropping objects such as a marble and car fender into a circle of spectators. The radio programme similarly released a range of avant-garde music and sound objects over the airwaves, reflecting Amirkhanian’s preferred title as KPFA’s ‘Sound Sensitivity Information Director’. Informed by analyses of archival broadcasts and other primary sources, this article frames Ode to Gravity as a conceptual extension of the 1968 piece and long-running ‘sound sensitivity’ experiment that sought to make sense of the contemporary musical landscape by collecting and propagating sonic data. Ode to Gravity’s consciousness-raising mission broadly, and the changes in content and presentation style over its twenty-five-year history specifically, add further texture to our understanding of post-war avant-garde impulses in music and sound.

The present study relied on internet memes as a tool to possibly fight ageism and shape public views in a positive manner. Data collection took place between May and June 2024, recruiting 160 Israeli Arabs, aged 13 to 16, from 3 different schools. In total, 105 memes addressed ageism towards older people. Visual and written contents were described, followed by more interpretative analysis. The memes were classified into two main themes. The first concerned negative ageist stereotypes of older persons (n = 66). The second theme concerned attempts to combat ageism (n = 39). Even though students received explicit instructions to fight ageism via their meme production, most students produced memes which depicted older age and ageing in a negative stereotypical light. The study highlights the relatively high levels of ageism in this group of participants and points to areas needing further attention in future interventions to alleviate ageism. The present findings are important as they question the current thinking of the Arab population as characterized by familistic values of high levels of respect towards older persons.