欧洲联盟（德语：Europäische Union，法语：Union européenne），简称欧盟（EU），总部设在比利时首都布鲁塞尔（Brussels），是由欧洲共同体发展而来的，创始成员国有6个，分别为德国、法国、意大利、荷兰、比利时和卢森堡。现拥有27个会员国，正式官方语言有24种。 1991年12月，欧洲共同体马斯特里赫特首脑会议通过《欧洲联盟条约》，通称《马斯特里赫特条约》。1993年11月1日，《马斯特里赫特条约》正式生效，欧盟正式诞生。2012年，欧盟获得诺贝尔和平奖。 欧洲理事会主席为夏尔·米歇尔， 欧洲议会议长为大卫·萨索利。 欧盟委员会主席为乌尔苏拉·冯·德莱恩。 欧盟的条约经过多次修订，运作方式依照《里斯本条约》。政治上所有成员国均为议会民主国家（2008年《经济学人》民主状态调查），经济上为世界上第二大经济实体（其中德国、法国、意大利为八国集团成员），军事上除瑞典、芬兰、爱尔兰、奥地利、马耳他与塞浦路斯六国以外（其中前五国是国际公认的永久中立国），其余21个欧盟成员国均为北大西洋公约组织成员。
In 2012, 22 EU countries signed the Fiscal Compact, an intergovernmental agreement aimed at backing EU fiscal rules with national arrangements. The main goal of the initiative was to strengthen compliance through an automatic correction mechanism triggering fiscal adjustment in case public finances deviate from 'the path of virtue'. Although the Compact de facto ceased to exist with the 2024 reform of the EU fiscal framework, it still offers useful insights for the future. Our analysis shows that better compliance was associated with a superior design of the correction mechanism, higher government efficiency and a stronger media presence of independent fiscal institutions. Economic growth can make up for a less sophisticated design. We also show that many countries had linked the trigger of the correction mechanism to decisions at the EU level. This choice defeated the original purpose of correction mechanisms to decouple key fiscal policy decisions from political considerations and discretion and bodes ill for 2024 reform of the Stability and Growth Pact (SGP).
The recent advancements in artificial intelligence (AI), and data science more broadly, have led to a proliferation of new methods and tools, such as machine learning (ML), that are used in all kinds of scientific research, from biomedical research through to environmental and education research. Research ethics review bodies are increasingly required to review AI research protocols that cover these different fields of enquiry. Questions have been raised regarding the appropriateness of existing ethics governance principles, practices, and processes to deal with the ethical challenges that AI and data science are introducing to research. Universities and research institutions across the world are trying to understand how to translate and practically implement broad AI ethical principles into research ethics governance guidelines and processes. In this article, we report on an expert stakeholders’ workshop organised at the University of Oxford as part of the process of reviewing its ethics governance for AI research. We describe the workshop and present the reflections and recommendations that emerged from it. The aim of the article is to share the approach taken by the University of Oxford CUREC in reviewing its ethics governance processes, and the insights gained with the broader research community, as a way of contributing to this scarce body of literature, facilitating further dialogue, promoting debate and collaboration on this important issue.
Research on democratic backsliding and on EU counter‐actions is growing rapidly, but we have only begun to understand how EU actions are taken up in domestic political debates in backsliding member states. Our research builds on the assumption that the framing of these debates contributes to the (de‐)legitimation of EU actions and thus has indirect effects on the EU's ability to intervene in processes of democratic backsliding. Conceptually, we distinguish three types of frames political parties use to support or oppose EU actions against democratic backsliding: crisis diagnosis frames, polity frames and value frames. We deduce hypotheses on the framing strategies of government and opposition parties and their evolution over time from theories of democratic backsliding and ethnopopulism. Our analysis relies on an original dataset of about 1400 news articles on democratic backsliding in Hungary (since 2010), including around 1350 frames parties used during domestic debates.
ShowVoc is a web-based, multilingual, platform for publication of linked datasets of different nature and scope: OWL ontologies, SKOS/SKOS-XL thesauri, OntoLex-Lemon lexicons, generic RDF datasets and linksets (EDOAL, XKOS). Born in the context of the ISA2 European programme for the development of digital solutions for interoperable cross-border and cross-sector public services, ShowVoc aims at providing a one-stop shop for maximizing the diffusion of semantic and lexical resources as Linked Open Data. To this end, ShowVoc combines traditional data provisioning following LOD policies, an advanced browsing interface and inter-dataset functionalities (e.g. global search, navigation of dataset relationships/alignments, translation API benefiting from multilingual datasets and linksets) into a thorough platform for data provisioning. A metadata registry completes the offer combining different metadata vocabularies into an advanced catalog that can be inspected through a convenient user interface and LOD best practices. ShowVoc's mission, requirements and its collocation within the SoTA are discussed in the paper.
