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Over the last century, the Clinical Pathological Conferences (CPC) have enabled the Case Records database to provide valuable information regarding the diagnosis and treatment of various diseases. Diseases involving Staphylococcus aureus, Influenza, or Tuberculosis are some of the most prominent infectious diseases that have appeared throughout the database, and which were investigated. Cases with a final diagnosis for each disease were chosen and the amount tracked and compared to case data from the CDC. The average time to diagnosis and time in hospital were analyzed and used to see how our understanding of each disease had evolved over the past 100 years. Over the course of the span, the time for diagnosis and time in hospital decreased overall for all three diseases, but with some outliers present. Additionally, patient survivability also increased. Furthermore, the usage of AI models in medical diagnosis was commented on, and which presents a potentially revolutionary ability to positively affect the CPC/Case Records as it enters its second century.

The recent publication of Manichaean manuscripts preserved by the Mingshi ritual tradition in Qingtian, Zhejiang, has brought to light substantial materials ultimately deriving from texts transmitted in Tang China. This article examines pages 23–48 of the Mingshi Yinglun jing ke 明氏應輪經科 (Ritual Manual of the Gospel of the Mingshi Tradition), a composite ritual manuscript centered on Mani’s Living Gospel. Its most significant feature is a sequence of eleven passages transcribing Middle Persian in Chinese characters. Building on previous identifications of sections (5)–(11), the article proposes new readings of sections (1)–(4) and the concluding words of section (11), and presents all eleven passages in six corresponding layers: Chinese transcription, reconstructed Middle Chinese pronunciation, normalized Middle Persian reading, Middle Persian transliteration, word-for-word English translation, and an English translation of the accompanying Tang Chinese interpretive rendering. The article further compares the Chinese text following these transcriptions with surviving witnesses to the Living Gospel in Middle Persian and Sogdian, quotations preserved in the Greek Cologne Mani Codex, and related materials in the Coptic Synaxeis. These comparisons indicate that a substantial textual core of pages 23–41 derives from a Tang Chinese translation or adaptation of the Living Gospel, although it has been combined with Chinese hymnic renderings and later ritual materials. Pages 41–48 praise the scripture, enumerate the benefits of copying, reciting, expounding, hearing, and preserving it, and conclude with ritual benedictions. The Qingtian manuscript thus preserves both previously unknown evidence for the Chinese transmission of Mani’s Living Gospel and a record of its continuing transformation within a local ritual tradition.

Governments across the world are exploring how generative AI might improve their ability to effectively pass legislation and deliver public services. This includes the UK government, which has stated that utilising AI to reduce costs and improve public services is a national priority. Current efforts to deploy AI tools are focused on streamlining internal bureaucracy, such as writing ministerial briefings or analysing public consultations, and supporting the direct delivery of public services. In contrast, there has been limited exploration of the role generative AI could play in directly improving policy development and implementation, in support of a government’s high-level agenda or manifesto commitments.

This project seeks to add practical context to hypothetical considerations of how generative AI might impact policymaking. Published articles and commentary provide insights and recommendations, with varying degrees of specificity, on the opportunities, risks, and limitations of using AI to support national policymaking. However, there does not appear to be any instances of meaningful ‘direct experimentation’ with currently available generative AI tools, to explore the potential role of generative AI in more detail, identifying context-specific areas of strength, weakness, or risk.

This project is designed as an initial first step towards addressing this research gap. Using our direct experience of government policymaking, we begin to assess the performance and relative ‘value-add’ of using publicly available generative AI tools to support typical policymaking functions. This is conducted through ‘policy simulations’ in which we assessed how useful (or problematic) AI tools were in helping us to perform a range of policymaking tasks.

Our simulated ‘performance assessments’ were conducted in two phases. Firstly, we undertook basic assessments of the utility of publicly available generative AI across typical policymaking tasks for three different high-level policy contexts. Secondly, we conducted a more granular and in-depth assessment in an area where we have domain expertise (Regional Growth and Development), to explore the impact of output verification (by experts) and corpus design on the utility of generative AI in a national policymaking context.

From this research, we have identified an indicative set of policymaking functions for which generative AI appears to offer significant value (provided this deployment is specific, deliberate, and targeted). We also found that the use of generative AI does not replace the need for in-depth policy expertise but rather increases the utilisation of this expertise by a wider range of government stakeholders, and significant risks may be introduced in the absence of meaningful human engagement with AI outputs. Significant limitations of using generative AI to support policymaking also emerged from this preliminary research, alongside the well-documented broader risks associated with generative AI (such as unclear provenance, biased outputs, hallucinations, and broader security risks). The full set of our indicative findings are below, which we use to inform a proposed set of basic recommendations for governments seeking to better utilise generative AI to support national policymaking.

Most importantly, we judge that the findings from this preliminary exploratory research were sufficiently informative to indicate that there would be meaningful benefit in pursuing further ‘direct experimentation’ with generative AI tools in a policymaking context. We propose that this would be an effective way to develop more detailed understanding and subsequently inform government guidance and adoption initiatives (including for professional training purposes). We conclude this report with a set of proposals for how this further research could be conducted, including how to address the limitations of our initial exploratory research project.

This research is likely to deliver the greatest benefit if conducted in close collaboration with government stakeholders, incorporating direct domain expertise and adjusting for real-world policymaking requirements and constraints. This includes wider considerations on ensuring AI tools are used in accordance with democratic principles and core national values, including retaining sovereignty over internal government data and maintaining sufficient control over AI enabled decision-making. Further, as set out in the Cabinet Secretary’s Future Civil Service initiative, achieving the widespread utilisation and adoption of AI across the UK government will require a whole-of-institution approach, incorporating changes to workforce design and development, novel procurement models, risk management and governance mechanisms, and fundamentally redesigning government processes. Future research on the role of generative AI in policymaking should account for these broader institutional considerations and align closely with existing government initiatives.

Under conditions of polycrisis — the compound, reinforcing external shocks of the post-2022 period — the European Union has come under sustained stress that the inherited concept of convergence is only partially equipped to absorb. Convergence had largely been studied and developed under conditions of relative stability; the reviewed scholarship therefore offers a limited account of what convergence becomes under sustained external pressure, limited attention to the peripheral member states most exposed to divergence, and limited qualitative insight into the purposes and meanings of convergence. This study addresses that threefold gap through the research question: how do U.S. trade policy and Russia’s war policy influence convergence in the European Union? The study adopts a mixed-methods design weighted toward the qualitative component through the single case of Romania. The primary data originate from ten expert interviews with senior figures across Romanian public life, analyzed through grounded theory collected through an original semi-structured instrument. The study proposes three original contributions: the Neo-Convergence model, which recasts convergence as a crisis-activated, multidimensional, and reciprocal mode; the Technological Clubs framework, which reclassifies member states by command over technology into four clubs; and governance-mediated convergence, which identifies domestic governance capacity as the transmission through which external pressure is integrated as convergence or divergence, reframing Romania from a peripheral member state to a strategic frontier.

The thesis seeks to understand the major influencers behind Ukraine’s denuclearization outcome in the form of the Budapest Memorandum of 1994, which stipulated vague security assurances from the US, the UK, and Russia to respect Ukraine’s sovereignty and territorial integrity in exchange for returning to Russia the Soviet nuclear weapons Ukraine inherited after the collapse of the USSR in 1991. The thesis discusses five influencers or independent variables and their impact on the denuclearization outcome. Specifically, the variables involve Ukraine’s inability to control the inherited Soviet nuclear weapons, the nuclear weapons’ fast-approaching expiration dates, a multi-billion-dollar compensation for the inherited Soviet nuclear weapons, the US diplomatic and financial support, and security and economic threats posed by Russia. Furthermore, to support the premise that a nuclear Ukraine was feasible, the thesis explores a counterfactual scenario of Ukraine managing to retain and operate the inherited tactical nuclear weapons before their removal to Russia from 1991 to 1992. The thesis concludes that the inherited tactical nuclear weapons were the only route for Ukraine to become a nuclear power in the early 1990s, as obtaining the long-sought security guarantees from the US and the UK to deter Russia was not feasible. The thesis also points out that with the tactical and strategic nuclear weapons’ fast-approaching expiration dates, Ukraine would have to develop its own nuclear deterrent eventually. Such a scenario would have likely prevented the annexation of Crimea and a full-scale Russian-Ukrainian war with millions of casualties.