Arguably, recent and prospective developments within artificial intelligence are a fascination within contemporary technoculture. The dawning of a new era that is characterised by the various impacts of these technological and scientific advances leads to questions about the type of subject that will inherit and inhabit the consequences of these developments. This paper will examine the role that speculative fiction plays as a site of critical engagement in investigating some of the more urgent questions posed by the intersection between humans and technology, such as the social consequences of projected technologies and the possibilities of changing embodiment, and particularly how these issues prove to be of immense importance for the gendered subject. The essays contained within Jeanette Winderson’s non-fictional publication 12 Bytes: How We Got Here. Where We Might Go Next (2021) provide a perceptive insight into both the promises and the pitfalls of AI technology for the future female and embodied experience. Winterson’s thought-provoking contemplations will be read alongside her fictional novels, The Stone Gods (2007) and Frankissstein (2019), to consider how she utilises the genre of speculative fiction to explore existing representations of gender whilst working to define new transhuman subjects. A recurring theme throughout these novels is the way in which AI, despite its liberating and transcendent potential, is imagined as the inevitable perpetuation of female subjugation.

Kim’s book is rich with thought-provoking ideas that are relevant to contemporary societies. I focus on its discussion of the “pluralism dilemma” and Kim’s appeal to “public reason Confucianism” as a response. The pluralism dilemma is the dilemma that a Confucian democratic theory has to meet both “the pluralist demand” and “the Confucian demand” (70). While the “Confucian” part of the theory is supposed to prefer Confucian doctrines over other doctrines, the “democratic” part is supposed to “accommodate as many reasonable conceptions of the good and comprehensive doctrines as possible” (70). What is original about Kim’s theory is that it seeks to accommodate both.

In this article we present a methodological framework for integrating nondigital legacy excavation data with modern stratigraphic datasets in a 3D-GIS environment. Using a case study from the Late Bronze Age site of Hala Sultan Tekke (Cyprus), we demonstrate how georeferenced photogrammetric models can be combined with digitized legacy documentation to overcome inconsistencies in archival records. The approach enables the correction of elevation data, the reconstruction of stratigraphic layers that are no longer preserved, and the interpolation of missing contexts. By aligning old section drawings with high-resolution 3D models of recent sondages, we created a coherent spatial and chronological framework that facilitates new archaeological interpretations. This integrated model also supports cross-disciplinary collaboration and long-term digital preservation. The study contributes to wider discussions on the sustainable use of unpublished or fragmentary excavation records, offering a practical, step-by-step guide for researchers working with similar datasets. Ultimately, this approach underscores the potential of 3D modeling to revitalize underused archaeological archives and transform them into dynamic analytical tools, in line with current best practices in digital archaeology and open data sharing.

Direct-seeding of rice by sowing dry seeds on dry soils often results in poor seedling emergence due to erratic rainfall. Adjusting the sowing depth to a given rainfall pattern may improve rice emergence. To assess risks of crop failure in direct-seeded rice, we developed a platform for modeling and simulation of rice emergence at different sowing depths. We combined the HYDRUS-1D soil simulation model, which simulates the surface soil’s moisture dynamics, with two rice emergence models recently developed by our research group. The platform used 48 years of daily weather data (1977–2024) for the study site as inputs for the soil model to simulate soil moisture and temperature at designated depths. We then input the simulated values and sowing depths into the emergence models to simulate final emergence and the emergence date. The simulated soil water tension at a depth of 1 cm showed huge interannual variation, reaching 10 MPa in dry years. The simulation showed that relative to a 1-cm sowing depth, depths of 4 and 6 cm greatly reduce the probability of crop failure under rainfed conditions (from 8% to between 1% and 2%). Our novel platform for risk assessment should therefore facilitate the use of direct-seeded rice in suboptimal environments. The platform also fills a knowledge gap for simulation of crop establishment in direct-seeded rice under future climate scenarios.

Although all presidents pursue their agendas unilaterally, President Donald Trump’s early second-term actions shocked the political system for their scope and breadth. One of Trump’s boldest moves was a frontal assault on Congress’s constitutional power of the purse through unprecedented impoundments and unilateral tariffs. Despite widespread public opposition to Trump’s gambits and clear statutory violations, Congress has offered little resistance, marking a stark departure from historical precedent. This analysis situates Trump’s actions within broader debates over the scope of executive authority and the weakening of institutional checks and balances. Partisan incentives and Trump’s dominance of the Republican Party have muted congressional resistance, raising urgent questions about the future of the separation of powers in an era of unprecedented executive overreach.

Transitioning to a sustainable economy requires firms to transform their business models in accordance with circular economy principles. Circular economy scholarship has predominantly examined resource-rich large firms and circular startups, leaving established, resource-constrained small-to-medium-sized enterprises (SMEs) underexplored. Facing capability constraints regarding resources, knowledge, and organizational capacity, government policy intervention plays an important role. Through interviews with 15 experts and analysis of seven government programs, we reveal the transition dynamics that shape SME circular engagement and how government intervention can reinforce the optimization of linear business models or facilitate moving toward circular business model transformation.

Understanding the values held by negotiating parties is central to the design and success of international climate change agreements. However, empirical understandings of these values – and the manners by which they structure negotiating countries’ value networks and interactions over time – are severely limited. In addressing this shortcoming, this paper uses keyword-assisted topic models to extract value networks for the 13 most recent Conferences of the Parties (COPs) to the United Nations Framework Convention on Climate Change (UNFCCC). It then uses network analysis tools to unpack these networks in relation to influential values, countries, and time. In doing so, it demonstrates that countries’ core climate change values (i) can be accurately recovered from COP High-level Segment (HLS) speeches and (ii) can, in turn, be used to understand the structure of negotiation networks at the UNFCCC. Analysis of the corresponding value networks for COPs 16–28 indicates that initially central values of “Fairness” and “Power” have increasingly given way to values associated with the “Environment” and “Achievement.” Thus, countries at the UNFCCC have increasingly eschewed values associated with common but differentiated responsibilities in favor of a consensus over the urgency of collectively combating climate change. These and related insights illustrate our approach’s potential for recovering and understanding value networks within climate change negotiations – a critical first step for any successful climate change agreement.

In 2025, President Donald Trump expanded his own powers through unprecedented interpretations of congressional statutes and Article II of the US Constitution. Ensuing waves of litigation and a record number of emergency-relief applications by the administration to the US Supreme Court placed extraordinary pressure on the federal judiciary. Although US district judges have delayed or halted a range of significant administrative actions, this article’s overview of Trump 47 in court highlights three different scholarly approaches that doubt that the US Supreme Court alone can or ultimately will reverse the administration’s agenda. First, the Roberts Court’s emergency docket decisions thus far comport with recent polarization trends in presidential-power cases. Second, the US Supreme Court lacks institutional capacity and consistent jurisprudence to challenge each area of alleged presidential overreach. Third, the administration’s use of broad authorities previously delegated by Congress serves as a reminder that constitutional interpretation and executive-branch powers are rooted in the broader political system. Congress cannot easily retract granted authority but curtailing presidential unilateralism requires more than litigation.

The role of data and automated (non-artificial intelligence [AI]) algorithmic targeting in adaptive social cash systems is gaining increasing significance, but few governments have yet leveraged on AI technologies to reap its benefits. Hence, there is mounting pressure on social cash policymakers and practitioners to rapidly embrace the opportunities arising from AI applications, especially in times of crisis. While data and algorithmic targeting (non-AI and AI) are efficient in enrolling beneficiaries in emergency social cash systems, it may also pose serious challenges. Through a qualitative case study of an adaptive social cash programme in Pakistan, the research critically examines the data/algorithmic targeting process, and unveils the shortcomings prevalent in design, data and algorithmic decision-making that lead to certain exclusionary outcomes. The study makes several contributions to the data and policy literature. Drawing on the limitations, it first offers a set of practical recommendations for greater enrolment, and hence inclusion of beneficiaries. Second, it discusses novel opportunities that AI technologies may present in adaptive social cash systems, whilst carefully assessing the risks. Third, the study proposes an organisational AI governance framework to guide the development of responsible and ethical AI practices. The study affords policy and practical implications for governments, social cash policymakers, and practitioners in providing invaluable insights into how changing targeting practices, via AI technologies, under a governance framework can direct ethical practices that positively impacts on beneficiaries, social cash organisations, and stakeholders.