Environmental water delivery is implemented globally to redress the ecological impacts of river regulation and consumptive water use. Allocation must balance the competing (and often conflicting) needs of humans, a diversity of water-dependent species and abiotic processes in the managed system. To optimize water allocation for conservation we developed a novel optimization framework that integrated a genetic algorithm with an integrated systems model to refine near-optimal allocations that maximize outcomes for a shrub (Duma florulenta), tree (Eucalyptus camaldulensis) and tree frog (Ranoidea raniformis) in one of the world’s most regulated catchments: the Murray–Darling Basin (Australia). Our algorithm weighted 16 wetland attributes and optimized those weights to prioritize allocation over a 25-year forecast window. The best-performing solutions required no additional resources but improved outcomes for the two priority plants and doubled the surviving frog populations. Modifying the multi-user model to only consider R. raniformis improved outcomes for that species at the expense of the two plant species, highlighting the risks of allocating a shared resource through a single-species lens. We demonstrate the value of optimization and multi-species approaches as decision-support tools for environmental water allocation and similar resource allocation problems in conservation.

The introduction to this forum outlines the many ways neoliberal thinkers have apprehended nature over the past century and why this oeuvre has been largely overlooked by historians. The intellectual history of neoliberalism and the study of the environmental crisis have both become sprawling but largely unconnected academic corpuses. This forum has been assembled to act as a conduit and thus help cultivate a new subfield of neoliberal environmental thought. By studying neoliberals as a “thought collective,” an approach pioneered two decades ago by Dieter Plehwe and Bernhard Walpen, it becomes possible to perceive how their environmental frameworks were conceived, debated, and disseminated. The existence of a neoliberal thought collective does not mean that there is a single market-conforming approach to managing environmental problems; rather, there is a wide array of frameworks cohered by a shared canon and worldview. The articles in this forum hint at the creativity and eclecticism of neoliberal bricoleurs, whose arguments range from climate denial, to selfish bees, to privatizing the Moon. As editors, we suggest three reasons for studying neoliberal environmental thought: to better perceive and thwart the thought collective’s objectives, to guard oneself against unconsciously adopting “green” neoliberal frameworks, and to engage fruitfully with the work of a worthy adversary to further the construction of post-neoliberal frameworks and their adjunct intellectual infrastructure.

This research sought to update understanding following improvements to treatment and deepen the understanding of the mortality risk associated with Type 1 or Type 2 diabetes, including relative risk in the presence of co-morbidities. Specifically, we developed a model to provide mortality predictions at a granular level for lives with and without diabetes. The model is tailored for use by the insurance industry to provide an updated source from which to appreciate the risk posed when underwriting people with diabetes. By providing an updated and deeper understanding of mortality risk, the research’s aim is to improve access to insurance for those individuals living with diabetes. The model combines industry standard underwriting risk factors, such as age, gender, deprivation index, body mass index (BMI), smoker status, blood pressure (BP) and cholesterol level, with various co-morbidities related to diabetes. A comprehensive analysis of mortality risk factors, between 2010 and 2019, for people with and without diabetes is undertaken on over 1.2 million records based on Clinical Practice Research Datalink (CPRD), Hospital Episode Statistics (HES) and Office for National Statistics (ONS) death registrations data. Cox proportional hazards models are used to estimate the probability of death, stratified by gender across three distinct populations: Type 1 diabetes, Type 2 diabetes and a general population sample. The model outputs produced are permutations of the following: gender; population split by general sample, Type 1 and Type 2 diabetes; and a time-dependent exponential model and a time-invariant homogeneous model. A Shiny model application allows interaction with the model outputs (https://0jv7e6-scott-reid.shinyapps.io/diabmdl/) and spreadsheets provide additional explanation. Useful insights were obtained through industry discussions on the variation of existing market practice against that implied by the results. Key rating factors were generally aligned with market practice, such as age, BMI, BP, cholesterol and years since a diabetes diagnosis. However, for a few significant mortality risks impacting co-morbidities, the results did not adhere to prior expectations. Exploratory work suggested that the order and sequencing of key co-morbidities for diabetes must be included in future model development.

The advancement of AI relies on text and data mining (TDM) to acquire training data, yet its large-scale algorithmic crawling activities fundamentally conflict with copyright regimes. Through comparative legal research, this article reveals the divergent governance approaches and efficacy deficiencies within the three major jurisdictions of the European Union, the United States and China. We argue that the current regulatory model adopted by the EU may adversely affect the dynamism of Europe’s AI industry. At the policy level, the EU should construct a synergistic “Cost-Benefit-Governance” framework, reducing compliance costs through differentiated regulation, collective licensing, and fiscal support measures. It should also leverage unified internal rules and international multilateral platforms to foster governance consensus. In legal practice, the EU should advance the clarification and tiered application of copyright exceptions. This can be achieved by refining rules, implementing data classification governance and innovating safe harbour liability mechanisms to enhance legal predictability, thereby balancing technological innovation and copyright protection. This framework aims to mitigate the inhibitory effect of current systems on AI innovation and address jurisdictional barriers through international cooperation.

Public humanities often require an expert in one area to learn another field or skill on-the-fly or to collaborate effectively across boundaries of specialization. Fear of the unknown combines with taken-for-granted assumptions about standard forms of humanities work to prevent our pursuit of promising public humanities projects and careers. Even veteran scholars with expertise important to public life shrink when going outside the comfort zone of academia to engage with audiences via new formats and professional pathways. A recognition of this need to upskill has emerged from a recent surge of research on public humanities in practice. This comic introduces The How-To Issue of Public Humanities, which provides instruction manuals for doing public humanities, meeting people where they are via media, formats, and professions that require conceptual understanding of what these new platforms offer and technical training in the nuts-and-bolts of these spaces. The piece identifies four pillars of public humanities (upskilling, teaming, universal design, and authority sharing), maps the phases of a public humanities project (dream, plan, create, improve), provides a toolkit of key concepts and strategies for the field, includes a directory of examples and instruction manuals, and provides guidance for sustainability and evaluation in public humanities.

While Structural Health Monitoring (SHM) has been widely studied, its reliability in real-world applications remains challenged by pronounced operational variability, particularly when system behavior changes discretely between operating regimes. Such methods generally rely on baseline comparisons; however, under multiple operating regimes, the baseline becomes distributed across several distinct regions, each associated with a specific regime. This multi-baseline behavior complicates anomaly detectability, as variations induced by changing operating conditions may mask the subtle changes caused by structural degradation. The challenge is particularly pronounced for systems exhibiting regime-dependent behavior, where transitions between approximately stationary conditions occur frequently and are difficult to isolate. To address this, an efficient probabilistic multi-model framework is proposed, in which each operating regime is represented by a locally Vector Autoregressive (VAR) model. A Bayesian formulation is adopted to account for parameter uncertainty explicitly and to enable sequential updating, allowing the regime models to adapt as additional data become available—an important feature for early-stage SHM. New observations are evaluated against the ensemble of regime-specific VAR models using the marginal likelihood, enabling assessment of statistical consistency with the learned reference behavior. Persistently low consistency is interpreted as indicative of anomalies, which may reflect structural changes or evolving degradation. The proposed method is demonstrated using vibration data from gearboxes onboard a Crew Transfer Vessel operating under multiple regimes. Despite the limitations and uncertainties inherent to early-phase SHM, the framework successfully identifies deviations from the learned reference behavior within consistent operating conditions, demonstrating its potential for SHM under realistic, time-varying operation.

Across global and Pacific contexts, inclusive education policies often struggle to move from adoption to practice, leaving a persistent gap between commitments and classroom realities. In Vanuatu, inclusive education is both a constitutional and a statutory obligation: the Constitution of the Republic of Vanuatu guarantees equal rights without discrimination, the Education Act No. 9 of 2014 mandates culturally relevant schooling, and Vanuatu 2030: The People’s Plan: National Sustainable Development Plan 2016–2030 positions inclusion as central to national progress. Building on this foundation, the Ministry of Education and Training has launched the Inclusive Education and Training (IET) Policy 2025–2030, which sets ambitious goals for equitable access, teacher development, and systemic transformation. This article applies the Kokonas Research Methodology (KRM), a Vanuatu-born Indigenous implementation framework grounded in kastom (customary knowledge) and storian (dialogue), to the IET Policy. KRM structures implementation through five stages — initiation, validation, intervention, monitoring and support, and replication — which are mapped to policy priorities to demonstrate how culturally grounded processes can guide enactment in practice. Findings highlight the national significance of KRM in strengthening legitimacy and ownership of reforms in Vanuatu, while also offering transferable lessons for other Pacific countries and contributing to wider Asia-Pacific debates on inclusive education.

We examine how relative exposure to negative economic shocks across racial groups impacts racial animus and voting patterns. Guided by group position theory, we argue that when dominant groups experience greater economic harm than nondominant groups within the same labor markets, racial animus intensifies. In the US context, the historically central boundary between white and Black Americans provides the most meaningful test of this mechanism. Using data from US commuting zones (2000 to 2020), we focus on the impact of the China shock on anti-Black racial animus. We measure relative exposure as the gap in import exposure between white and Black workers. Our findings show that negative economic shocks disproportionately affecting white workers, compared to Black workers, lead to increased anti-Black animus and increased Republican presidential vote share, even when controlling for overall import exposure. Taken together, these findings suggest that it is economic decline relative to another group that generates racial animus and outwardly racist behavior, as well as influences political behavior.

To mark the 10th Anniversary of BJPsych Open, we explore the contributions of papers published in BJPsych Open to advance cultural psychiatry practice and policy. In our overview of papers published in BJPsych Open, we found examples of good practice where authors detailed the translation methods and interpretation models in the research. The task facing clinicians and public health practitioners is to evolve applied, locally relevant, culturally competent interventions in which specific adaptations are shaped by the potential beneficiaries, alongside theoretical and practical issues of cultural adaptation. Researchers and clinicians will need to provide evidence of acceptability and effectiveness of adapted interventions, alongside considering financial and implementation realities.

We develop the Tannakian theory of (analytic) prismatic F-crystals on a smooth formal scheme $\mathfrak {X}$ over the ring of integers of a discretely valued field with perfect residue field. Our main result gives an equivalence between the $\mathcal {G}$-objects of prismatic F-crystals on $\mathfrak {X}$ and $\mathcal {G}$-objects on a newly defined category of $\mathbb {Z}_p$-local systems on $\mathfrak {X}_\eta $: those of prismatically good reduction. Additionally, we develop a shtuka realization functor for (analytic) prismatic F-crystals on p-adic (formal) schemes and show it satisfies several compatibilities with previous work on the Tannakian theory of shtukas over such objects.

We argue that repugnance can, in some cases, be strategically used as a resource by some ‘entrepreneurs’ who can use it to advance their own goals. To understand the conditions in which repugnance can be strategically used, we first propose a conceptual framework to characterize repugnance-related transactions and emphasize how concerned individuals devise narratives to manage these situations, increase (or even decrease) artificially their acceptability, and ultimately justify their behaviour. This framework, which combines relational proximity and the strength of social consensus surrounding a transaction, allows for predicting the costs of developing appropriate narratives. Then, we analyse four rationales by which entrepreneurial individuals exploit and use strategically repugnant dimensions. Repugnance can be strategically leveraged as a barrier to entry, a tool for niche differentiation, a mechanism of political and market polarization, and a means of attracting attention, thereby shaping competition, regulation, and visibility across markets and platforms.

Platform firms have disrupted markets and challenged regulatory frameworks, but a new phase is emerging in which governments increasingly regulate these firms and firms engage with regulation strategically. This article examines how interactions between governments and firms shape the employment classification of platform workers. Drawing on case studies of California (United States), Spain, and Denmark, I show that welfare regime characteristics structure the regulatory environment that firms confront, whereas their competitive calculations shape their strategic responses. The analysis identifies three distinct configurations: successful firm override of government initiatives to classify workers as employees, resulting in a hybrid worker category (California); mixed firm responses to government initiatives aimed at employee classification, ultimately leading to universal employee status (Spain); and voluntary employee classification in the absence of specific government mandates (Denmark). These findings challenge assumptions that platform firms uniformly resist regulation and demonstrate how welfare state institutions and firms’ competitive strategies jointly shape worker classification outcomes.

Oil palm is a commercially important crop cultivated across 27 tropical regions of Africa, Asia, and Latin America. Due to favorable climatic conditions, oil palm cultivation is concentrated in Southeast Asia, with Indonesia, Malaysia, and Thailand accounting for approximately 87% of the global palm oil supply. Effective weed management is essential for maintaining oil palm productivity; however, excessive reliance on herbicides has raised concerns regarding herbicide resistance and environmental sustainability. This review evaluates current weed management strategies in oil palm plantations, including chemical, mechanical, cultural, and biological, with an emphasis on integrated weed management (IWM) strategies suitable for Southeast Asian production systems. Particular attention is given to the differing weed management constraints faced by industrial plantations and smallholder producers, including variations in labor availability, operational scale, and access to weed management technologies. Current evidence suggests that combining complementary control tactics, such as integrating mechanical and cultural practices with chemical and biological control methods, offers greater long-term sustainability than reliance on herbicides alone. Individual approaches, however, face significant limitations, including economic constraints, labor shortages, and inconsistent effectiveness, highlighting the importance of integrated strategies. We conclude that adaptive, multi-tactic IWM programs tailored to local production scales will be critical for sustainable weed management in future oil palm production.

Ageing of the population is an ineluctable process with major implications. We review effects of ageing on housing markets and related policy issues. Demographic effects are detectable for housing, with the working population tending to drive prices up while retired groups restrain it but only to a limited degree. The elderly desire bequests and precautionary saving and prefer not to sell or borrow against existing property. Among policy issues are availability of equity extraction loans, transaction costs for elderly households wishing to trade down and factors underlying availability of alternative and more suitable housing for elderly people.